chore: bump version to 1.2.0a2

- Fix IntentJudge.__init__() control flow: model override block was
  dangling inside try/except instead of being a separate branch
- Remove provider/base_url/api_key kwargs from server.py and cli.py
  JudgeConfig construction (fields removed in prior commit)
- Remove stale TOML mapping entries from config.py
- Remove --judge-provider CLI argument
- Fix Judge settings font sizes to match Settings tab (12px keys,
  11px descriptions, tighter spacing, --fg instead of --accent)

.github/renovate.json

@@ -41,6 +41,14 @@
       "matchStrings": ["mermaid-(?<currentValue>[\\d.]+)/"],
       "depNameTemplate": "mermaid",
       "datasourceTemplate": "npm"
+    },
+    {
+      "customType": "regex",
+      "description": "Track vendored hls.js version",
+      "managerFilePatterns": ["/pyproject\\.toml$/"],
+      "matchStrings": ["hls-(?<currentValue>[\\d.]+)/"],
+      "depNameTemplate": "hls.js",
+      "datasourceTemplate": "npm"
     }
   ],
   "packageRules": [
@@ -91,7 +99,7 @@
     {
       "description": "Vendored JS — CI workflow downloads files automatically",
       "groupName": "Vendored JS",
-      "matchPackageNames": ["katex", "highlight.js", "mermaid"],
+      "matchPackageNames": ["katex", "highlight.js", "mermaid", "hls.js"],
       "schedule": ["before 9am on the first day of the month"],
       "automerge": false
     },

.github/workflows/ci.yml

@@ -7,6 +7,9 @@ on:
   pull_request:
     branches: [main, "stable/*"]
 
+permissions:
+  contents: read
+
 jobs:
   lint:
     runs-on: ubuntu-latest
@@ -74,6 +77,53 @@ jobs:
         env:
           TURNSTONE_TEST_PG_URL: postgresql+psycopg://postgres:postgres@localhost:5432/turnstone_test
 
+  wheel-completeness:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
+      - uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6
+        with:
+          python-version: "3.14"
+      - run: pip install build
+      - run: python -m build --wheel
+      - name: Check all data files are in wheel
+        run: |
+          SOURCE=$(find turnstone -type f \
+            ! -name '*.py' ! -name '*.pyc' ! -path '*__pycache__*' \
+            | sort)
+          WHEEL=$(python -m zipfile -l dist/*.whl \
+            | awk '{print $1}' \
+            | grep -v '\.py$' | grep -v '\.dist-info' | grep -v '\.pyc' | grep -v '^File$' \
+            | sort)
+
+          # Files intentionally excluded from the wheel (one per line)
+          ALLOW="
+          turnstone/core/storage/migrations/script.py.mako
+          "
+
+          MISSING=$(comm -23 <(echo "$SOURCE") <(echo "$WHEEL") \
+            | grep -vFxf <(echo "$ALLOW" | sed '/^[[:space:]]*$/d; s/^[[:space:]]*//' ) || true)
+
+          if [ -n "$MISSING" ]; then
+            echo "::error::Data files in source tree but missing from wheel:"
+            echo "$MISSING"
+            echo ""
+            echo "Add them to [tool.hatch.build.targets.wheel] in pyproject.toml"
+            echo "or to the ALLOW list in this job if intentionally excluded."
+            exit 1
+          fi
+          echo "All source data files present in wheel"
+      - name: Smoke-test entry points from installed wheel
+        run: |
+          python -m venv /tmp/smoke
+          /tmp/smoke/bin/pip install dist/*.whl
+          /tmp/smoke/bin/turnstone --help
+          /tmp/smoke/bin/turnstone-server --help
+          /tmp/smoke/bin/turnstone-console --help
+          /tmp/smoke/bin/turnstone-admin --help
+          /tmp/smoke/bin/turnstone-channel --help
+          /tmp/smoke/bin/turnstone-bootstrap --help
+
   lock-check:
     runs-on: ubuntu-latest
     steps:

.github/workflows/docker-publish.yml

@@ -5,6 +5,10 @@ on:
     workflows: ["CI"]
     types: [completed]
 
+concurrency:
+  group: docker-${{ github.event.workflow_run.head_sha }}
+  cancel-in-progress: true
+
 permissions:
   contents: read
   packages: write
@@ -15,7 +19,9 @@ env:
 
 jobs:
   docker:
-    if: github.event.workflow_run.conclusion == 'success'
+    if: >-
+      github.event.workflow_run.conclusion == 'success' &&
+      github.event.workflow_run.head_repository.full_name == github.repository
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
@@ -37,7 +43,7 @@ jobs:
 
       - name: Log in to GHCR
         if: steps.tag.outputs.skip == 'false'
-        uses: docker/login-action@74a5d142397b4f367a81961eba4e8cd7edddf772 # v3
+        uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4
         with:
           registry: ${{ env.REGISTRY }}
           username: ${{ github.actor }}
@@ -61,12 +67,12 @@ jobs:
           fi
           echo "tags=${TAGS}" >> "$GITHUB_OUTPUT"
 
-      - uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 # v3
+      - uses: docker/setup-buildx-action@4d04d5d9486b7bd6fa91e7baf45bbb4f8b9deedd # v4
         if: steps.tag.outputs.skip == 'false'
 
       - name: Build and push
         if: steps.tag.outputs.skip == 'false'
-        uses: docker/build-push-action@14487ce63c7a62a4a324b0bfb37086795e31c6c1 # v6
+        uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7
         with:
           context: .
           push: true

.github/workflows/publish.yml

@@ -5,6 +5,10 @@ on:
     workflows: ["CI"]
     types: [completed]
 
+concurrency:
+  group: publish-${{ github.event.workflow_run.head_sha }}
+  cancel-in-progress: true
+
 permissions:
   contents: write
   id-token: write

THIRD-PARTY-NOTICES

@@ -95,3 +95,22 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
+
+================================================================================
+
+hls.js 1.6.15
+https://github.com/video-dev/hls.js
+
+Copyright 2017 Dailymotion
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.

compose.yaml

@@ -1,5 +1,10 @@
 # =============================================================================
-# Turnstone Docker Compose Stack
+# Turnstone Docker Compose Stack — Development
+#
+# This file is for local development from a git clone. It builds images
+# locally from the Dockerfile. If you installed via pip/pipx, run
+# `turnstone-bootstrap` instead — it writes a production compose.yaml
+# that pulls pre-built images from ghcr.io.
 #
 # Usage:
 #   Infra only:           docker compose up
@@ -60,9 +65,7 @@ services:
   # turnstone-server — Web UI + chat workstreams + LLM interaction
   # -------------------------------------------------------------------
   server:
-    build:
-      context: .
-      dockerfile: Dockerfile
+    image: turnstone:local
     profiles:
       - production
     command:
@@ -115,6 +118,7 @@ services:
   # turnstone-console — Cluster dashboard
   # -------------------------------------------------------------------
   console:
+    image: turnstone:local
     build:
       context: .
       dockerfile: Dockerfile
@@ -145,9 +149,7 @@ services:
   # Requires TURNSTONE_DISCORD_TOKEN to enable Discord adapter
   # -------------------------------------------------------------------
   channel:
-    build:
-      context: .
-      dockerfile: Dockerfile
+    image: turnstone:local
     profiles:
       - production
       - cluster
@@ -164,7 +166,7 @@ services:
       # Generate with: python -c "import secrets; print(secrets.token_hex(32))"
       - TURNSTONE_JWT_SECRET=${TURNSTONE_JWT_SECRET:?Set TURNSTONE_JWT_SECRET in .env}
       - TURNSTONE_DB_BACKEND=${DB_BACKEND:-postgresql}
-      - TURNSTONE_DB_URL=${DATABASE_URL:-postgresql://${POSTGRES_USER:-turnstone}:${POSTGRES_PASSWORD:-turnstone}@postgres:5432/turnstone}
+      - TURNSTONE_DB_URL=${DATABASE_URL:-postgresql+psycopg://${POSTGRES_USER:-turnstone}:${POSTGRES_PASSWORD:-turnstone}@postgres:5432/turnstone}
       - TURNSTONE_CHANNEL_ADVERTISE_URL=http://channel:8091
     networks:
       - turnstone-net
@@ -214,7 +216,7 @@ services:
       MODEL: ${MODEL:-}
       MCP_CONFIG: ${MCP_CONFIG:-}
       TURNSTONE_DB_BACKEND: ${DB_BACKEND:-postgresql}
-      TURNSTONE_DB_URL: ${DATABASE_URL:-postgresql://${POSTGRES_USER:-turnstone}:${POSTGRES_PASSWORD:?}@postgres:5432/turnstone}
+      TURNSTONE_DB_URL: ${DATABASE_URL:-postgresql+psycopg://${POSTGRES_USER:-turnstone}:${POSTGRES_PASSWORD:?}@postgres:5432/turnstone}
       TURNSTONE_NODE_ID: node-1
       TURNSTONE_ADVERTISE_URL: http://server-1:8080
     extra_hosts: ["host.docker.internal:host-gateway"]

docs/architecture.md

@@ -547,6 +547,21 @@ expanded tools).
 **Tool naming:** `mcp__{server}__{tool}` — double underscore delimiter, validated
 at connection time (server names with `__` are rejected).
 
+**Resilience:** Each MCP server has an independent circuit breaker that opens
+after 3 consecutive transport failures (timeouts, broken pipes, connection
+resets). Cooldown uses capped exponential backoff (30 s base, 5 min max) with
+per-server jitter to avoid thundering herd. Protocol-level errors (`McpError`)
+from a healthy connection do not trip the breaker. When the cooldown expires
+(half-open), the next operation attempt triggers automatic reconnection. Manual
+`/mcp refresh` also clears the circuit on success. All sync bridge methods
+(`call_tool_sync`, `read_resource_sync`, `get_prompt_sync`, `refresh_sync`)
+cancel orphaned futures on timeout to prevent coroutine accumulation on the
+background event loop. Push notification refreshes are debounced (5 s per
+server) to protect against notification storms. The periodic refresh loop
+attempts reconnection for disconnected servers with exponential backoff
+(60 s–1 h). Transport stream references are pre-closed before stack teardown to
+work around the MCP SDK's anyio cancel-scope CPU busy-loop (SDK #2147).
+
 **Error isolation:** Per-server connection/refresh failures are caught and logged; other
 servers are unaffected. Tool execution errors return error strings to the LLM
 rather than crashing the session.

docs/diagrams/20-mcp-architecture.puml

@@ -152,10 +152,34 @@ MCPMgr -> MCPSrv : prompts/get
 MCPSrv --> MCPMgr : GetPromptResult
 MCPMgr --> Session : messages [{role, content}]
 
+== Resilience: Circuit Breaker & Stream Safety ==
+
+note over MCPMgr
+  **Per-server circuit breaker**
+  CLOSED --(3 failures)--> OPEN
+  OPEN --(cooldown expires)--> half-open probe
+  Probe success --> CLOSED (trip_count decays by 1)
+  Probe failure --> OPEN (cooldown doubles, max 5 min)
+
+  McpError (protocol) does NOT trip breaker.
+  BrokenPipeError / EOFError evicts dead session.
+  All sync methods cancel orphaned futures on timeout.
+  Transport streams pre-closed before stack teardown
+  to avoid anyio cancel-scope CPU busy-loop (SDK #2147).
+end note
+
+Session -> MCPMgr : call_tool_sync()
+MCPMgr -> MCPMgr : _cb_gate(server)\n[reject if circuit open]
+MCPMgr -> MCPMgr : _cb_auto_reconnect()\n[if session gone + cooldown expired]
+MCPMgr -> MCPSrv : tools/call
+MCPSrv --> MCPMgr : result or error
+MCPMgr -> MCPMgr : _cb_record_success()\nor _cb_record_failure()
+
 == Three-Tier Refresh ==
 
-group Push Notifications
+group Push Notifications (debounced 5s per server)
   MCPSrv -> MCPMgr : ToolListChangedNotification
+  MCPMgr -> MCPMgr : debounce check\n(skip if < 5s since last)
   MCPMgr -> MCPMgr : _refresh_server_tools()
 
   MCPSrv -> MCPMgr : ResourceListChangedNotification
@@ -172,6 +196,9 @@ group Periodic Polling (default 4h)
     Only polls capabilities
     without push support.
     Staggered per-server.
+    Disconnected servers get
+    reconnect attempts with
+    exponential backoff (60s-1h).
   end note
 end
 

docs/diagrams/png/20-mcp-architecture.png

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a6b7769aa7e732ffbeb1eb7f5b65273a135fb3a78d9802ec36d3b92801c34f6b
-size 427745
+oid sha256:7623df33be9baf7647ca1c2450640df57e1cd73e8be1f8168aae16e546ad683c
+size 459941

docs/releasing.md

@@ -6,8 +6,8 @@ Turnstone uses two parallel release tracks published from a single PyPI package.
 
 | Track | Versions | Branch | Docker tags | PyPI install |
 |-------|----------|--------|-------------|--------------|
-| **Stable** | `1.0.0`, `1.0.1` | `stable/1.0` | `:1.0.1`, `:1.0`, `:stable`, `:latest` | `pip install turnstone` |
-| **Experimental** | `1.1.0a1`, `1.1.0a2` | `main` | `:1.1.0a1`, `:experimental` | `pip install turnstone --pre` |
+| **Stable** | `1.1.0`, `1.1.1` | `stable/1.1` | `:1.1.0`, `:1.1`, `:stable`, `:latest` | `pip install turnstone` |
+| **Experimental** | `1.2.0a1`, `1.2.0a2` | `main` | `:1.2.0a1`, `:experimental` | `pip install turnstone --pre` |
 
 - **Stable** receives bugfixes only. Production-grade.
 - **Experimental** receives new features. May be rough around the edges.

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "turnstone"
-version = "1.0.0"
+version = "1.2.0a2"
 description = "Multi-node AI orchestration platform with tool use, agent routing, and cluster simulation."
 readme = "README.md"
 license = "BUSL-1.1"
@@ -67,6 +67,7 @@ turnstone-bootstrap = "turnstone.bootstrap:main"
 [tool.hatch.build.targets.wheel]
 include = [
   "turnstone/**/*.py",
+  "turnstone/prompts/**/*.md",
   "turnstone/tools/*.json",
   "turnstone/ui/static/*.html",
   "turnstone/ui/static/*.css",
@@ -79,7 +80,9 @@ include = [
   "turnstone/shared_static/katex-0.16.44/**/*",
   "turnstone/shared_static/hljs-11.11.1/**/*",
   "turnstone/shared_static/mermaid-11.14.0/**/*",
+  "turnstone/shared_static/hls-1.6.15/**/*",
   "turnstone/sdk/py.typed",
+  "turnstone/deploy/*.yaml",
 ]
 
 [tool.pytest.ini_options]

scripts/update-vendored-js.sh

@@ -5,6 +5,7 @@
 #   scripts/update-vendored-js.sh katex 0.16.39
 #   scripts/update-vendored-js.sh hljs 11.12.0
 #   scripts/update-vendored-js.sh mermaid 11.14.0
+#   scripts/update-vendored-js.sh hls 1.6.15
 #
 # This script:
 #   1. Downloads the new version from CDN
@@ -18,7 +19,7 @@ STATIC_DIR="turnstone/shared_static"
 CDN="https://cdn.jsdelivr.net/npm"
 
 usage() {
-    echo "Usage: $0 <katex|hljs|mermaid> <version>"
+    echo "Usage: $0 <katex|hljs|mermaid|hls> <version>"
     echo "Example: $0 katex 0.16.39"
     exit 1
 }
@@ -147,6 +148,32 @@ case "$LIB" in
         echo "Done. Old directory removed: ${OLD_DIR}"
         ;;
 
+    hls)
+        OLD_VERSION=$(detect_old_version "hls")
+        check_same_version "$OLD_VERSION" "$VERSION" "hls"
+        OLD_DIR="${STATIC_DIR}/hls-${OLD_VERSION}"
+        NEW_DIR="${STATIC_DIR}/hls-${VERSION}"
+
+        echo "Updating hls.js ${OLD_VERSION} -> ${VERSION}"
+        mkdir -p "${NEW_DIR}"
+
+        echo "  Downloading hls.min.js..."
+        curl -sSfL "${CDN}/hls.js@${VERSION}/dist/hls.min.js" -o "${NEW_DIR}/hls.min.js"
+
+        echo "  Downloading LICENSE..."
+        if ! curl -sSfL "${CDN}/hls.js@${VERSION}/LICENSE" -o "${NEW_DIR}/LICENSE" 2>/dev/null; then
+            if [[ -f "${OLD_DIR}/LICENSE" ]]; then
+                cp "${OLD_DIR}/LICENSE" "${NEW_DIR}/LICENSE"
+            else
+                echo "  WARNING: Could not obtain LICENSE for hls.js ${VERSION}"
+            fi
+        fi
+
+        update_refs "hls-${OLD_VERSION}" "hls-${VERSION}"
+        rm -rf "${OLD_DIR}"
+        echo "Done. Old directory removed: ${OLD_DIR}"
+        ;;
+
     *)
         echo "Unknown library: ${LIB}"
         usage

sdk/typescript/package-lock.json

@@ -14,22 +14,22 @@
       }
     },
     "node_modules/@emnapi/core": {
-      "version": "1.9.1",
-      "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.9.1.tgz",
-      "integrity": "sha512-mukuNALVsoix/w1BJwFzwXBN/dHeejQtuVzcDsfOEsdpCumXb/E9j8w11h5S54tT1xhifGfbbSm/ICrObRb3KA==",
+      "version": "1.9.2",
+      "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.9.2.tgz",
+      "integrity": "sha512-UC+ZhH3XtczQYfOlu3lNEkdW/p4dsJ1r/bP7H8+rhao3TTTMO1ATq/4DdIi23XuGoFY+Cz0JmCbdVl0hz9jZcA==",
       "dev": true,
       "license": "MIT",
       "optional": true,
       "peer": true,
       "dependencies": {
-        "@emnapi/wasi-threads": "1.2.0",
+        "@emnapi/wasi-threads": "1.2.1",
         "tslib": "^2.4.0"
       }
     },
     "node_modules/@emnapi/runtime": {
-      "version": "1.9.1",
-      "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.9.1.tgz",
-      "integrity": "sha512-VYi5+ZVLhpgK4hQ0TAjiQiZ6ol0oe4mBx7mVv7IflsiEp0OWoVsp/+f9Vc1hOhE0TtkORVrI1GvzyreqpgWtkA==",
+      "version": "1.9.2",
+      "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.9.2.tgz",
+      "integrity": "sha512-3U4+MIWHImeyu1wnmVygh5WlgfYDtyf0k8AbLhMFxOipihf6nrWC4syIm/SwEeec0mNSafiiNnMJwbza/Is6Lw==",
       "dev": true,
       "license": "MIT",
       "optional": true,
@@ -39,9 +39,9 @@
       }
     },
     "node_modules/@emnapi/wasi-threads": {
-      "version": "1.2.0",
-      "resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.2.0.tgz",
-      "integrity": "sha512-N10dEJNSsUx41Z6pZsXU8FjPjpBEplgH24sfkmITrBED1/U2Esum9F3lfLrMjKHHjmi557zQn7kR9R+XWXu5Rg==",
+      "version": "1.2.1",
+      "resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.2.1.tgz",
+      "integrity": "sha512-uTII7OYF+/Mes/MrcIOYp5yOtSMLBWSIoLPpcgwipoiKbli6k322tcoFsxoIIxPDqW01SQGAgko4EzZi2BNv2w==",
       "dev": true,
       "license": "MIT",
       "optional": true,

sdk/typescript/src/types.ts

@@ -284,7 +284,6 @@ export interface CreateSkillResourceRequest {
 
 export interface BackendStatus {
   status: string;
-  circuit_state: string;
 }
 
 export interface WorkstreamCounts {

tests/test_bootstrap.py

@@ -19,6 +19,7 @@ from turnstone.bootstrap import (
     _tool_generate_secret,
     _tool_read_file,
     _tool_validate_api_key,
+    _tool_write_compose,
     _tool_write_file,
     execute_tool,
 )
@@ -103,6 +104,52 @@ class TestWriteFile:
         assert (tmp_path / "changed.txt").read_text() == "new\n"
 
 
+class TestWriteCompose:
+    def test_writes_compose_file(self, tmp_path: Path) -> None:
+        with patch("builtins.input", return_value="y"):
+            result = _tool_write_compose(tmp_path, {})
+        assert "written successfully" in result
+        assert "ghcr.io" in result
+        content = (tmp_path / "compose.yaml").read_text()
+        assert "ghcr.io/turnstonelabs/turnstone" in content
+        assert "TURNSTONE_IMAGE_TAG" in content
+
+    def test_user_declines(self, tmp_path: Path) -> None:
+        with patch("builtins.input", return_value="n"):
+            result = _tool_write_compose(tmp_path, {})
+        assert "declined" in result
+        assert not (tmp_path / "compose.yaml").exists()
+
+    def test_identical_content_skipped(self, tmp_path: Path) -> None:
+        # Write it once
+        with patch("builtins.input", return_value="y"):
+            _tool_write_compose(tmp_path, {})
+        # Second call should skip
+        result = _tool_write_compose(tmp_path, {})
+        assert "already exists" in result
+
+    def test_no_build_blocks(self, tmp_path: Path) -> None:
+        with patch("builtins.input", return_value="y"):
+            _tool_write_compose(tmp_path, {})
+        content = (tmp_path / "compose.yaml").read_text()
+        assert "build:" not in content
+        assert "dockerfile:" not in content.lower()
+
+    def test_overwrites_different_content(self, tmp_path: Path) -> None:
+        (tmp_path / "compose.yaml").write_text("old content\n")
+        with patch("builtins.input", return_value="y"):
+            result = _tool_write_compose(tmp_path, {})
+        assert "written successfully" in result
+        content = (tmp_path / "compose.yaml").read_text()
+        assert "ghcr.io" in content
+
+    def test_no_local_image_references(self, tmp_path: Path) -> None:
+        with patch("builtins.input", return_value="y"):
+            _tool_write_compose(tmp_path, {})
+        content = (tmp_path / "compose.yaml").read_text()
+        assert "turnstone:local" not in content
+
+
 class TestGenerateSecret:
     def test_default_length(self) -> None:
         secret = _tool_generate_secret({})
@@ -620,7 +667,7 @@ class TestConstants:
             assert func["parameters"]["type"] == "object"
 
     def test_tool_count(self) -> None:
-        assert len(TOOLS) == 7
+        assert len(TOOLS) == 8
 
     def test_all_tools_have_implementations(self) -> None:
         from turnstone.bootstrap import TOOL_FUNCTIONS

tests/test_channel_discord.py

@@ -8,6 +8,13 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
+# discord.utils.escape_markdown passes 'count' as positional to re.sub,
+# which is deprecated in Python 3.13+.  This is a discord.py bug (fixed
+# in newer releases); suppress here to keep the test output clean.
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:.*'count' is passed as positional argument:DeprecationWarning"
+)
+
 discord = pytest.importorskip("discord")
 
 
@@ -886,6 +893,192 @@ class TestFormatToolResult:
         assert result.count("```") == 2
 
 
+# ---------------------------------------------------------------------------
+# Media embed detection and rendering
+# ---------------------------------------------------------------------------
+
+
+class TestTryParseMedia:
+    """Tests for try_parse_media in _formatter.py."""
+
+    def test_stream_url_detected(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = json.dumps({"stream_url": "http://jf:8096/Videos/abc/stream", "container": "mp4"})
+        result = try_parse_media(data)
+        assert result is not None
+        assert result["stream_url"] == "http://jf:8096/Videos/abc/stream"
+
+    def test_media_details_detected(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = json.dumps({"id": "abc", "name": "Test Movie", "type": "Movie", "year": 2024})
+        result = try_parse_media(data)
+        assert result is not None
+        assert result["name"] == "Test Movie"
+
+    def test_search_results_detected(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = json.dumps({"results": [{"id": "1", "name": "Hit"}], "total_count": 1})
+        result = try_parse_media(data)
+        assert result is not None
+        assert len(result["results"]) == 1
+
+    def test_sessions_detected(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = json.dumps({"sessions": [{"id": "s1", "user_name": "ptrck"}]})
+        result = try_parse_media(data)
+        assert result is not None
+
+    def test_empty_results_returns_none(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        assert try_parse_media(json.dumps({"results": []})) is None
+
+    def test_plain_text_returns_none(self):
+        from turnstone.channels._formatter import try_parse_media
+
+        assert try_parse_media("just a string") is None
+
+    def test_non_dict_json_returns_none(self):
+        from turnstone.channels._formatter import try_parse_media
+
+        assert try_parse_media("[1, 2, 3]") is None
+
+    def test_unrelated_dict_returns_none(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        assert try_parse_media(json.dumps({"foo": "bar"})) is None
+
+
+class TestIsSafeImageUrl:
+    """Tests for _is_safe_image_url in _formatter.py."""
+
+    def test_http_url(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("http://jellyfin:8096/Items/abc/Images/Primary") is True
+
+    def test_https_url(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("https://jellyfin.example.com/Items/abc/Images/Primary") is True
+
+    def test_ftp_rejected(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("ftp://evil.com/image.jpg") is False
+
+    def test_file_rejected(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("file:///etc/passwd") is False
+
+    def test_userinfo_rejected(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("http://user:pass@jellyfin:8096/image") is False
+
+    def test_empty_rejected(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("") is False
+
+    def test_private_ip_allowed(self):
+        from turnstone.channels._formatter import _is_safe_image_url
+
+        assert _is_safe_image_url("http://192.168.0.6:8096/Items/abc/Images/Primary") is True
+
+
+class TestBuildMediaEmbed:
+    """Tests for try_build_media_embed and embed builders."""
+
+    def test_single_item_embed_uses_web_url_not_stream_url(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = {
+            "name": "Test Movie",
+            "type": "Movie",
+            "year": 2024,
+            "stream_url": "http://jf:8096/Videos/abc/stream?api_key=SECRET",
+            "web_url": "http://jf:8096/web/#/details?id=abc",
+            "overview": "A test movie.",
+        }
+        parsed = try_parse_media(json.dumps(data))
+        assert parsed is not None
+
+        from turnstone.channels._formatter import _build_single_media_embed
+
+        embed = _build_single_media_embed(parsed, "mcp__mediamcp__get_stream_url")
+        # web_url should be the embed URL, never stream_url
+        assert embed.url == "http://jf:8096/web/#/details?id=abc"
+        assert "SECRET" not in str(embed.to_dict())
+
+    def test_search_results_embed_format(self):
+        import json
+
+        from turnstone.channels._formatter import try_parse_media
+
+        data = {
+            "results": [
+                {"name": "Movie A", "year": 2020, "type": "Movie", "runtime_minutes": 120},
+                {"name": "Movie B", "year": 2021, "type": "Movie"},
+            ],
+            "total_count": 2,
+        }
+        parsed = try_parse_media(json.dumps(data))
+
+        from turnstone.channels._formatter import _build_search_results_embed
+
+        embed = _build_search_results_embed(parsed)
+        assert "Movie A" in embed.description
+        assert "Movie B" in embed.description
+        assert "2 of 2" in embed.footer.text
+
+    def test_build_media_embed_returns_none_for_plain_text(self):
+        from turnstone.channels._formatter import try_build_media_embed
+
+        http = MagicMock()
+        result = _run(try_build_media_embed("tool", "plain text", http=http))
+        assert result is None
+
+    def test_season_episode_string_values(self):
+        """Season/episode numbers as strings should not raise."""
+
+        from turnstone.channels._formatter import _build_search_results_embed
+
+        data = {
+            "results": [
+                {
+                    "name": "Pilot",
+                    "type": "Episode",
+                    "series_name": "Show",
+                    "season_number": "1",
+                    "episode_number": "1",
+                },
+            ],
+            "total_count": 1,
+        }
+        embed = _build_search_results_embed(data)
+        assert "S01E01" in embed.description
+
+
 # ---------------------------------------------------------------------------
 # Thinking indicator lifecycle
 # ---------------------------------------------------------------------------
@@ -1103,6 +1296,7 @@ class TestToolResultEvent:
         bot._tool_info_msgs = {}
         bot._pending_approval_msgs = {}
         bot._notify_reply_channels = {}
+        bot._http_client = MagicMock()
         bot._should_auto_approve = MagicMock(return_value=False)
         bot._on_ws_event = TurnstoneBot._on_ws_event.__get__(bot, TurnstoneBot)
         return bot

tests/test_config_store.py

@@ -105,7 +105,8 @@ class TestDelete:
         assert store.get("tools.timeout") == defn.default
 
     def test_returns_false_for_non_existent(self, store):
-        assert store.delete("tools.timeout") is False
+        result = store.delete("tools.timeout")
+        assert result is False
 
     def test_rejects_unknown_key(self, store):
         with pytest.raises(ValueError, match="Unknown setting"):

tests/test_console.py

@@ -39,7 +39,7 @@ class MockStorage:
         self.services: list[dict[str, str]] = []
 
     def list_services(self, service_type: str, max_age_seconds: int = 120) -> list[dict[str, str]]:
-        return [s for s in self.services if True]  # all services match
+        return list(self.services)
 
 
 # ---------------------------------------------------------------------------
@@ -418,13 +418,12 @@ class TestCollectorDelta:
         c._nodes["node-a"] = NodeSnapshot(
             node_id="node-a",
             server_url="http://a:8080",
-            health={"status": "ok", "backend": {"status": "up", "circuit_state": "closed"}},
+            health={"status": "ok", "backend": {"status": "up"}},
         )
 
-        c._apply_delta("node-a", {"type": "health_changed", "circuit_state": "open"})
+        c._apply_delta("node-a", {"type": "health_changed", "backend_status": "degraded"})
 
         health = c._nodes["node-a"].health
-        assert health["backend"]["circuit_state"] == "open"
         assert health["backend"]["status"] == "down"
         assert health["status"] == "degraded"
 

tests/test_edit_file.py

@@ -154,7 +154,7 @@ class TestSingleEdit:
         )
         assert result["needs_approval"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "applied 1 edit" in msg
         with open(path) as f:
             assert f.read() == "foo\nbar\nbaz\n"
@@ -172,7 +172,7 @@ class TestSingleEdit:
         assert result["needs_approval"]
         assert "deletion" in result["preview"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         with open(sample_file) as f:
             assert f.read() == "line1\nline2\nline4\nline5\n"
 
@@ -196,7 +196,7 @@ class TestBatchEdit:
         assert result["needs_approval"]
         assert "2 edits" in result["header"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "applied 2 edits" in msg
         with open(sample_file) as f:
             assert f.read() == "first\nline2\nline3\nline4\nlast\n"
@@ -216,7 +216,7 @@ class TestBatchEdit:
         )
         assert result["needs_approval"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "applied 3 edits" in msg
         with open(sample_file) as f:
             assert f.read() == "line1\nsecond\nthird\nfourth\nline5\n"
@@ -238,7 +238,7 @@ class TestBatchEdit:
         )
         assert result["needs_approval"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "overlap" in msg.lower()
         # File should be untouched
         with open(path) as f:
@@ -305,7 +305,7 @@ class TestBatchEdit:
         )
         assert result["needs_approval"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "applied 2 edits" in msg
         with open(path) as f:
             assert f.read() == "first_foo\nbar\nsecond_foo\nbaz\n"
@@ -324,7 +324,7 @@ class TestBatchEdit:
         )
         assert result["needs_approval"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         with open(sample_file) as f:
             assert f.read() == "line1\nline3\nline5\n"
 
@@ -344,7 +344,7 @@ class TestBatchEdit:
         # Single edit — no "(N edits)" count in header
         assert "edits)" not in result["header"]
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "applied 1 edit" in msg
         with open(sample_file) as f:
             assert f.read() == "line1\nline2\nmiddle\nline4\nline5\n"
@@ -414,7 +414,7 @@ class TestExecEdgeCases:
         with open(sample_file, "w") as f:
             f.write("completely different content\n")
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "no longer found" in msg
 
     def test_file_deleted_between_prepare_and_exec(self, session, sample_file):
@@ -431,7 +431,7 @@ class TestExecEdgeCases:
 
         os.unlink(sample_file)
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "Error" in msg
 
     def test_batch_file_changed_partial_match(self, session, sample_file):
@@ -453,7 +453,7 @@ class TestExecEdgeCases:
         with open(sample_file, "w") as f:
             f.write("line1\nline2\nline3\nline4\n")
 
-        call_id, msg = session._exec_edit_file(result)
+        _, msg = session._exec_edit_file(result)
         assert "no longer found" in msg
         # line1 should NOT have been edited (atomic failure)
         with open(sample_file) as f:

tests/test_governance_endpoints.py

@@ -57,6 +57,7 @@ class _InjectAuthMiddleware(BaseHTTPMiddleware):
                     "admin.users",
                     "admin.orgs",
                     "admin.policies",
+                    "admin.prompt_policies",
                     "admin.skills",
                     "admin.usage",
                     "admin.audit",

tests/test_hash_ring_storage.py

@@ -41,6 +41,21 @@ class TestHashRingBuckets:
         # Empty list returns 0
         assert storage.assign_buckets([], "node-x") == 0
 
+    def test_assign_large_list_exceeds_chunk_size(self, storage):
+        """Regression: lists larger than chunk_size must not hit param limits."""
+        n = 1200  # exceeds SQLite chunk_size (500) and exercises multi-chunk path
+        storage.seed_ring_buckets([(i, "node-a") for i in range(n)])
+        count = storage.assign_buckets(list(range(n)), "node-b")
+        assert count == n
+        rows = storage.list_ring_buckets()
+        assert all(r["node_id"] == "node-b" for r in rows)
+
+    def test_assign_deduplicates_input(self, storage):
+        """Duplicates in the input list should not inflate rowcount."""
+        storage.seed_ring_buckets([(0, "node-a"), (1, "node-a")])
+        count = storage.assign_buckets([0, 1, 0, 1, 0], "node-b")
+        assert count == 2
+
 
 class TestBucketStats:
     def test_increment_creates_row(self, storage):

tests/test_healthcheck.py

@@ -1,4 +1,4 @@
-"""Tests for turnstone.core.healthcheck — backend health monitor with circuit breaker."""
+"""Tests for turnstone.core.healthcheck — passive backend health tracking."""
 
 from __future__ import annotations
 
@@ -10,39 +10,16 @@ import pytest
 if TYPE_CHECKING:
     from collections.abc import Generator
 
-from turnstone.core.healthcheck import BackendHealthMonitor, CircuitState
+from turnstone.core.healthcheck import BackendHealthTracker, HealthTrackerRegistry
 
 # ---------------------------------------------------------------------------
-# CircuitState enum
+# Fixtures
 # ---------------------------------------------------------------------------
 
 
-class TestCircuitState:
-    def test_closed(self) -> None:
-        assert CircuitState.CLOSED.value == "closed"
-
-    def test_open(self) -> None:
-        assert CircuitState.OPEN.value == "open"
-
-    def test_half_open(self) -> None:
-        assert CircuitState.HALF_OPEN.value == "half_open"
-
-
-# ---------------------------------------------------------------------------
-# BackendHealthMonitor
-# ---------------------------------------------------------------------------
-
-
-@pytest.fixture
-def mock_client() -> MagicMock:
-    client = MagicMock()
-    client.models.list.return_value.data = [MagicMock(id="test-model")]
-    return client
-
-
 @pytest.fixture
 def mock_metrics() -> Generator[MagicMock]:
-    """Patch the metrics singleton so set_backend_status / set_circuit_state exist."""
+    """Patch the metrics singleton so set_backend_status exists."""
     m = MagicMock()
     with (
         patch("turnstone.core.healthcheck.metrics", m, create=True),
@@ -51,240 +28,185 @@ def mock_metrics() -> Generator[MagicMock]:
         yield m
 
 
-def _make_monitor(
-    client: MagicMock,
-    failure_threshold: int = 3,
-    cooldown: float = 60.0,
-) -> BackendHealthMonitor:
-    return BackendHealthMonitor(
-        client=client,
-        probe_interval=1.0,
-        probe_timeout=1.0,
-        failure_threshold=failure_threshold,
-        cooldown=cooldown,
-    )
+def _make_tracker(failure_threshold: int = 3) -> BackendHealthTracker:
+    return BackendHealthTracker(failure_threshold=failure_threshold)
 
 
-class TestBackendHealthMonitor:
-    def test_starts_closed(self, mock_client: MagicMock) -> None:
-        mon = _make_monitor(mock_client)
-        assert mon.circuit_state == CircuitState.CLOSED
-        assert mon.is_healthy is True
+# ---------------------------------------------------------------------------
+# BackendHealthTracker
+# ---------------------------------------------------------------------------
 
-    def test_record_failure_increments(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """Failures below threshold do not open the circuit."""
-        mon = _make_monitor(mock_client, failure_threshold=5)
+
+class TestBackendHealthTracker:
+    def test_starts_healthy(self) -> None:
+        t = _make_tracker()
+        assert t.is_healthy is True
+        assert t.is_degraded is False
+        assert t.consecutive_failures == 0
+
+    def test_failures_below_threshold(self, mock_metrics: MagicMock) -> None:
+        """Failures below threshold do not degrade."""
+        t = _make_tracker(failure_threshold=5)
         for _ in range(4):
-            mon.record_failure()
-        assert mon.circuit_state == CircuitState.CLOSED
+            t.record_failure()
+        assert t.is_healthy is True
+        assert t.consecutive_failures == 4
 
-    def test_opens_after_threshold(self, mock_client: MagicMock, mock_metrics: MagicMock) -> None:
-        mon = _make_monitor(mock_client, failure_threshold=3)
+    def test_degrades_at_threshold(self, mock_metrics: MagicMock) -> None:
+        t = _make_tracker(failure_threshold=3)
         for _ in range(3):
-            mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
-        assert mon.is_healthy is False
+            t.record_failure()
+        assert t.is_degraded is True
+        assert t.is_healthy is False
 
-    def test_should_reject_when_open(self, mock_client: MagicMock, mock_metrics: MagicMock) -> None:
-        mon = _make_monitor(mock_client, failure_threshold=1, cooldown=9999.0)
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
-        assert mon.acquire_request_permit() is False
+    def test_stays_degraded_on_more_failures(self, mock_metrics: MagicMock) -> None:
+        t = _make_tracker(failure_threshold=2)
+        for _ in range(5):
+            t.record_failure()
+        assert t.is_degraded is True
+        assert t.consecutive_failures == 5
 
-    @patch("turnstone.core.healthcheck.time")
-    def test_half_open_after_cooldown(
-        self, mock_time: MagicMock, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """After cooldown elapses, should_allow_request transitions to HALF_OPEN."""
-        t = 1000.0
-        mock_time.monotonic.return_value = t
+    def test_success_clears_degraded(self, mock_metrics: MagicMock) -> None:
+        t = _make_tracker(failure_threshold=2)
+        t.record_failure()
+        t.record_failure()
+        assert t.is_degraded is True
+        t.record_success()
+        assert t.is_healthy is True
+        assert t.consecutive_failures == 0
 
-        mon = _make_monitor(mock_client, failure_threshold=1, cooldown=60.0)
-        # Override _last_state_change to use our mocked time
-        mon._last_state_change = t
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+    def test_success_resets_failure_count(self, mock_metrics: MagicMock) -> None:
+        t = _make_tracker(failure_threshold=5)
+        for _ in range(4):
+            t.record_failure()
+        t.record_success()
+        assert t.consecutive_failures == 0
+        # Should need 5 more failures to degrade
+        for _ in range(4):
+            t.record_failure()
+        assert t.is_healthy is True
 
-        # Advance past cooldown
-        mock_time.monotonic.return_value = t + 61.0
-        assert mon.acquire_request_permit() is True
-        assert mon.circuit_state == CircuitState.HALF_OPEN  # type: ignore[comparison-overlap]
+    def test_state_changed_callback_on_degrade(self, mock_metrics: MagicMock) -> None:
+        events: list[str] = []
+        t = BackendHealthTracker(failure_threshold=2, on_state_changed=events.append)
+        t.record_failure()
+        assert events == []
+        t.record_failure()
+        assert events == ["degraded"]
 
-    def test_success_resets(self, mock_client: MagicMock, mock_metrics: MagicMock) -> None:
-        """record_success resets failures and closes circuit from any state."""
-        mon = _make_monitor(mock_client, failure_threshold=1)
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+    def test_state_changed_callback_on_recover(self, mock_metrics: MagicMock) -> None:
+        events: list[str] = []
+        t = BackendHealthTracker(failure_threshold=1, on_state_changed=events.append)
+        t.record_failure()
+        assert events == ["degraded"]
+        t.record_success()
+        assert events == ["degraded", "healthy"]
 
-        mon.record_success()
-        assert mon.circuit_state == CircuitState.CLOSED  # type: ignore[comparison-overlap]
-        assert mon.is_healthy is True
-        # Internal counter should be reset
-        assert mon._consecutive_failures == 0
+    def test_no_callback_when_already_degraded(self, mock_metrics: MagicMock) -> None:
+        """Extra failures after degraded don't fire again."""
+        events: list[str] = []
+        t = BackendHealthTracker(failure_threshold=1, on_state_changed=events.append)
+        t.record_failure()
+        t.record_failure()
+        t.record_failure()
+        assert events == ["degraded"]  # only once
 
-    def test_should_allow_when_closed(self, mock_client: MagicMock) -> None:
-        mon = _make_monitor(mock_client)
-        assert mon.acquire_request_permit() is True
+    def test_no_callback_when_already_healthy(self, mock_metrics: MagicMock) -> None:
+        """Success while healthy doesn't fire."""
+        events: list[str] = []
+        t = BackendHealthTracker(failure_threshold=3, on_state_changed=events.append)
+        t.record_success()
+        t.record_success()
+        assert events == []
 
-    def test_half_open_allows_only_one_request(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """HALF_OPEN permits exactly one probe; subsequent callers are blocked."""
-        mon = _make_monitor(mock_client, failure_threshold=1)
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+    def test_no_direct_metrics_calls(self) -> None:
+        """Tracker does not touch metrics — the server callback handles it."""
+        t = _make_tracker(failure_threshold=1)
+        t.record_failure()
+        t.record_success()
+        # No assertion on metrics — the tracker delegates metric updates
+        # to the server-level callback via on_state_changed
 
-        # Force into HALF_OPEN with permit
-        with mon._lock:
-            mon._state = CircuitState.HALF_OPEN
-            mon._half_open_permit = True
 
-        # First caller gets through
-        assert mon.acquire_request_permit() is True
-        # Second caller is blocked
-        assert mon.acquire_request_permit() is False
-        # Third caller is also blocked
-        assert mon.acquire_request_permit() is False
+# ---------------------------------------------------------------------------
+# HealthTrackerRegistry
+# ---------------------------------------------------------------------------
 
-    def test_half_open_success_reopens_to_all(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """After probe succeeds in HALF_OPEN, circuit closes and all requests pass."""
-        mon = _make_monitor(mock_client, failure_threshold=1)
-        mon.record_failure()
-        with mon._lock:
-            mon._state = CircuitState.HALF_OPEN
-            mon._half_open_permit = False  # permit already consumed
 
-        # Probe succeeds
-        mon.record_success()
-        assert mon.circuit_state == CircuitState.CLOSED  # type: ignore[comparison-overlap]
-        # All callers pass now
-        assert mon.acquire_request_permit() is True
-        assert mon.acquire_request_permit() is True
+class TestHealthTrackerRegistry:
+    def test_same_backend_shares_tracker(self, mock_metrics: MagicMock) -> None:
+        """Two aliases on the same (provider, base_url) share a tracker."""
+        reg = HealthTrackerRegistry(failure_threshold=5)
+        t1 = reg.get_tracker("openai", "https://api.openai.com/v1")
+        t2 = reg.get_tracker("openai", "https://api.openai.com/v1")
+        assert t1 is t2
 
-    def test_half_open_failure_blocks_all(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """After probe fails in HALF_OPEN, circuit reopens and all requests blocked."""
-        mon = _make_monitor(mock_client, failure_threshold=1, cooldown=9999.0)
-        mon.record_failure()
-        with mon._lock:
-            mon._state = CircuitState.HALF_OPEN
-            mon._half_open_permit = False
+    def test_different_backends_independent(self, mock_metrics: MagicMock) -> None:
+        """Different (provider, base_url) pairs get independent trackers."""
+        reg = HealthTrackerRegistry(failure_threshold=5)
+        t_cloud = reg.get_tracker("openai", "https://api.openai.com/v1")
+        t_local = reg.get_tracker("openai-compatible", "http://localhost:8000/v1")
+        assert t_cloud is not t_local
 
-        # Probe fails
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
-        assert mon.acquire_request_permit() is False
+    def test_trailing_slash_normalized(self, mock_metrics: MagicMock) -> None:
+        """Trailing slashes on base_url are normalized away."""
+        reg = HealthTrackerRegistry(failure_threshold=5)
+        t1 = reg.get_tracker("openai", "https://api.openai.com/v1/")
+        t2 = reg.get_tracker("openai", "https://api.openai.com/v1")
+        assert t1 is t2
 
-    def test_half_open_failure_reopens(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """A failure in HALF_OPEN re-opens the circuit immediately."""
-        mon = _make_monitor(mock_client, failure_threshold=1)
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+    def test_degraded_isolation(self, mock_metrics: MagicMock) -> None:
+        """Degrading one backend does not affect another."""
+        reg = HealthTrackerRegistry(failure_threshold=2)
+        t_cloud = reg.get_tracker("openai", "https://api.openai.com/v1")
+        t_local = reg.get_tracker("openai-compatible", "http://localhost:8000/v1")
+        # Degrade the cloud tracker
+        t_cloud.record_failure()
+        t_cloud.record_failure()
+        assert t_cloud.is_degraded is True
+        # Local should be unaffected
+        assert t_local.is_healthy is True
 
-        # Force into HALF_OPEN
-        with mon._lock:
-            mon._state = CircuitState.HALF_OPEN
-            mon._update_metrics()
+    def test_get_tracker_for_alias(self, mock_metrics: MagicMock) -> None:
+        """get_tracker_for_alias looks up by model config's backend."""
+        from turnstone.core.model_registry import ModelConfig, ModelRegistry
 
-        # Another failure should reopen
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+        models = {
+            "cloud": ModelConfig(
+                "cloud", "https://api.openai.com/v1", "sk", "gpt-4o", provider="openai"
+            ),
+            "local": ModelConfig(
+                "local", "http://localhost:8000/v1", "x", "qwen", provider="openai-compatible"
+            ),
+        }
+        model_reg = ModelRegistry(models=models, default="cloud")
 
-    def test_probe_success_closes(self, mock_client: MagicMock, mock_metrics: MagicMock) -> None:
-        """A successful probe closes the circuit."""
-        mon = _make_monitor(mock_client, failure_threshold=1)
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+        reg = HealthTrackerRegistry(failure_threshold=5)
+        # No tracker created yet — should return None
+        assert reg.get_tracker_for_alias(model_reg, "cloud") is None
 
-        # Simulate probe success
-        assert mon._probe_once() is True
-        mon.record_success()
-        assert mon.circuit_state == CircuitState.CLOSED  # type: ignore[comparison-overlap]
+        # Create a tracker for the cloud backend
+        t = reg.get_tracker("openai", "https://api.openai.com/v1")
+        assert reg.get_tracker_for_alias(model_reg, "cloud") is t
 
-    def test_probe_failure_opens(self, mock_client: MagicMock, mock_metrics: MagicMock) -> None:
-        """Enough probe failures open the circuit."""
-        mock_client.with_options.return_value.models.list.side_effect = ConnectionError("down")
-        mon = _make_monitor(mock_client, failure_threshold=2)
+        # Local alias should still return None (no tracker for that backend)
+        assert reg.get_tracker_for_alias(model_reg, "local") is None
 
-        assert mon._probe_once() is False
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.CLOSED  # only 1 failure
-
-        assert mon._probe_once() is False
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN  # type: ignore[comparison-overlap]
-
-    def test_probe_loop_autonomous_recovery(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """_probe_loop transitions OPEN → HALF_OPEN → CLOSED without user requests."""
-        # Use very short intervals so the test is fast
-        mon = BackendHealthMonitor(
-            client=mock_client,
-            probe_interval=0.05,
-            probe_timeout=1.0,
-            failure_threshold=1,
-            cooldown=0.1,
+    def test_state_changed_callback(self, mock_metrics: MagicMock) -> None:
+        """on_state_changed fires with backend key and state."""
+        events: list[tuple[str, str]] = []
+        reg = HealthTrackerRegistry(
+            failure_threshold=2,
+            on_state_changed=lambda backend, state: events.append((backend, state)),
         )
-        # Trip the circuit
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
+        t = reg.get_tracker("openai", "https://api.openai.com/v1")
+        t.record_failure()
+        t.record_failure()  # triggers degraded
+        assert len(events) == 1
+        assert events[0][0] == "openai:https://api.openai.com/v1"
+        assert events[0][1] == "degraded"
 
-        # Backend is healthy — probe_once will succeed
-        mock_client.with_options.return_value.models.list.return_value = MagicMock()
-
-        # Start the probe loop and wait for autonomous recovery
-        mon.start()
-        try:
-            import time
-
-            deadline = time.monotonic() + 5.0
-            while mon.circuit_state != CircuitState.CLOSED and time.monotonic() < deadline:
-                time.sleep(0.05)
-            assert mon.circuit_state == CircuitState.CLOSED
-            # User requests should flow again without anyone calling acquire_request_permit
-            assert mon.acquire_request_permit() is True
-        finally:
-            mon.stop()
-            if mon._thread:
-                mon._thread.join(timeout=2.0)
-
-    def test_probe_loop_no_user_permit_during_probe(
-        self, mock_client: MagicMock, mock_metrics: MagicMock
-    ) -> None:
-        """While background probe is in HALF_OPEN, user requests are blocked."""
-        mon = BackendHealthMonitor(
-            client=mock_client,
-            probe_interval=0.05,
-            probe_timeout=1.0,
-            failure_threshold=1,
-            cooldown=0.1,
-        )
-        mon.record_failure()
-        assert mon.circuit_state == CircuitState.OPEN
-
-        # Force into HALF_OPEN as the probe loop would
-        with mon._lock:
-            mon._state = CircuitState.HALF_OPEN
-            mon._half_open_permit = False  # probe consumes it
-
-        # User requests should be blocked — only the probe gets through
-        assert mon.acquire_request_permit() is False
-
-    def test_stop_thread(self, mock_client: MagicMock) -> None:
-        """stop() signals the probe loop to exit."""
-        mon = _make_monitor(mock_client)
-        mon.start()
-        assert mon._thread is not None
-        assert mon._thread.is_alive()
-
-        mon.stop()
-        mon._thread.join(timeout=3.0)
-        assert not mon._thread.is_alive()
+    def test_backend_key_static(self) -> None:
+        """backend_key is a static method returning normalized tuple."""
+        key = HealthTrackerRegistry.backend_key("anthropic", "https://api.anthropic.com/")
+        assert key == ("anthropic", "https://api.anthropic.com")

tests/test_html.py

@@ -37,3 +37,55 @@ class TestStripHtml:
     def test_self_closing_tags(self):
         result = strip_html("hello<br/>world")
         assert result == "helloworld"
+
+    # -- invisible element stripping -----------------------------------------
+
+    def test_strips_script_content(self):
+        html = "<p>before</p><script>var x = 1;</script><p>after</p>"
+        result = strip_html(html)
+        assert "var x" not in result
+        assert "before" in result
+        assert "after" in result
+
+    def test_strips_style_content(self):
+        html = "<style>.foo { color: red; }</style><p>visible</p>"
+        result = strip_html(html)
+        assert "color" not in result
+        assert "visible" in result
+
+    def test_strips_template_content(self):
+        html = "<template><div>hidden</div></template><p>shown</p>"
+        result = strip_html(html)
+        assert "hidden" not in result
+        assert "shown" in result
+
+    def test_strips_noscript_content(self):
+        html = "<noscript>Enable JS</noscript><p>content</p>"
+        result = strip_html(html)
+        assert "Enable JS" not in result
+        assert "content" in result
+
+    def test_strips_multiple_script_blocks(self):
+        html = "<script>a()</script><p>middle</p><script>b()</script>"
+        result = strip_html(html)
+        assert "a()" not in result
+        assert "b()" not in result
+        assert "middle" in result
+
+    def test_strips_multiline_script(self):
+        html = "<script>\nfunction foo() {\n  return 1;\n}\n</script><p>ok</p>"
+        result = strip_html(html)
+        assert "function" not in result
+        assert "ok" in result
+
+    def test_strips_script_case_insensitive(self):
+        html = "<SCRIPT>code()</SCRIPT><p>text</p>"
+        result = strip_html(html)
+        assert "code()" not in result
+        assert "text" in result
+
+    def test_strips_script_with_attributes(self):
+        html = '<script type="text/javascript" src="app.js">init();</script><p>done</p>'
+        result = strip_html(html)
+        assert "init()" not in result
+        assert "done" in result

tests/test_judge_heuristic.py

@@ -453,3 +453,66 @@ class TestEdgeCases:
     def test_cargo_install(self):
         v = evaluate_heuristic("bash", {"command": "cargo install ripgrep"}, "bash")
         _assert_verdict(v, risk_level="medium", recommendation="review")
+
+
+# ---------------------------------------------------------------------------
+# Custom rules parameter
+# ---------------------------------------------------------------------------
+
+
+class TestCustomRulesParam:
+    """Tests for evaluate_heuristic() with custom rules kwarg."""
+
+    def test_custom_rules_override_builtins(self):
+        """Custom rules list is used instead of built-in rules."""
+        from turnstone.core.judge import _HeuristicRule, evaluate_heuristic
+
+        custom = [
+            _HeuristicRule(
+                name="custom-test",
+                risk_level="high",
+                confidence=0.95,
+                recommendation="deny",
+                tool_pattern="bash",
+                arg_patterns=[r"custom_dangerous_cmd"],
+                intent_template="Custom danger: {arg_snippet}",
+                reasoning_template="Custom rule matched.",
+            ),
+        ]
+        # Should match custom rule
+        verdict = evaluate_heuristic(
+            "bash",
+            {"command": "custom_dangerous_cmd --flag"},
+            "bash",
+            rules=custom,
+        )
+        assert verdict.risk_level == "high"
+        assert verdict.recommendation == "deny"
+        assert "custom-test" in verdict.evidence[0]
+
+    def test_custom_rules_no_match_default(self):
+        """When custom rules don't match, default medium/review verdict returned."""
+        from turnstone.core.judge import evaluate_heuristic
+
+        verdict = evaluate_heuristic(
+            "bash",
+            {"command": "ls"},
+            "bash",
+            rules=[],
+        )
+        assert verdict.risk_level == "medium"
+        assert verdict.recommendation == "review"
+        assert verdict.confidence == 0.5
+
+    def test_none_rules_uses_builtins(self):
+        """When rules=None, built-in rules are used (backward compat)."""
+        from turnstone.core.judge import evaluate_heuristic
+
+        verdict = evaluate_heuristic(
+            "bash",
+            {"command": "rm -rf /etc"},
+            "bash",
+            rules=None,
+        )
+        assert verdict.risk_level == "critical"
+        assert "rm-root" in verdict.evidence[0]

tests/test_judge_rules_storage.py

@@ -0,0 +1,429 @@
+"""Tests for heuristic_rules and output_guard_patterns storage CRUD operations."""
+
+from __future__ import annotations
+
+import uuid
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from turnstone.core.storage._sqlite import SQLiteBackend
+
+
+def _make_id() -> str:
+    return uuid.uuid4().hex
+
+
+class TestHeuristicRuleStorage:
+    def test_create_and_get_heuristic_rule(self, db: SQLiteBackend) -> None:
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="dangerous-exec",
+            risk_level="critical",
+            confidence=0.95,
+            recommendation="deny",
+            tool_pattern="execute_code",
+            arg_patterns='[".*exec.*", ".*eval.*"]',
+            intent_template="User wants to run code",
+            reasoning_template="Executing arbitrary code is dangerous",
+            tier="critical",
+            priority=100,
+            builtin=True,
+            enabled=True,
+            created_by="admin",
+        )
+        r = db.get_heuristic_rule(rid)
+        assert r is not None
+        assert r["rule_id"] == rid
+        assert r["name"] == "dangerous-exec"
+        assert r["risk_level"] == "critical"
+        assert r["confidence"] == 0.95
+        assert r["recommendation"] == "deny"
+        assert r["tool_pattern"] == "execute_code"
+        assert r["arg_patterns"] == '[".*exec.*", ".*eval.*"]'
+        assert r["intent_template"] == "User wants to run code"
+        assert r["reasoning_template"] == "Executing arbitrary code is dangerous"
+        assert r["tier"] == "critical"
+        assert r["priority"] == 100
+        assert r["builtin"] is True
+        assert r["enabled"] is True
+        assert r["created_by"] == "admin"
+
+    def test_get_heuristic_rule_by_name(self, db: SQLiteBackend) -> None:
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="by-name-lookup",
+            risk_level="high",
+            confidence=0.8,
+            recommendation="review",
+            tool_pattern="file_write",
+        )
+        r = db.get_heuristic_rule_by_name("by-name-lookup")
+        assert r is not None
+        assert r["rule_id"] == rid
+        assert r["name"] == "by-name-lookup"
+
+    def test_get_heuristic_rule_by_name_not_found(self, db: SQLiteBackend) -> None:
+        assert db.get_heuristic_rule_by_name("nonexistent") is None
+
+    def test_list_heuristic_rules(self, db: SQLiteBackend) -> None:
+        db.create_heuristic_rule(
+            rule_id=_make_id(),
+            name="low-tier-rule",
+            risk_level="low",
+            confidence=0.5,
+            recommendation="approve",
+            tool_pattern="read_file",
+            tier="low",
+            priority=10,
+        )
+        db.create_heuristic_rule(
+            rule_id=_make_id(),
+            name="critical-tier-rule",
+            risk_level="critical",
+            confidence=0.99,
+            recommendation="deny",
+            tool_pattern="delete_all",
+            tier="critical",
+            priority=50,
+        )
+        db.create_heuristic_rule(
+            rule_id=_make_id(),
+            name="medium-tier-rule",
+            risk_level="medium",
+            confidence=0.7,
+            recommendation="review",
+            tool_pattern="web_search",
+            tier="medium",
+            priority=20,
+        )
+        rules = db.list_heuristic_rules()
+        assert len(rules) == 3
+        # Ordered by tier (critical=0, medium=2, low=3) then priority desc
+        assert rules[0]["name"] == "critical-tier-rule"
+        assert rules[1]["name"] == "medium-tier-rule"
+        assert rules[2]["name"] == "low-tier-rule"
+
+    def test_list_heuristic_rules_enabled_only(self, db: SQLiteBackend) -> None:
+        db.create_heuristic_rule(
+            rule_id=_make_id(),
+            name="enabled-rule",
+            risk_level="medium",
+            confidence=0.7,
+            recommendation="approve",
+            tool_pattern="tool_a",
+            enabled=True,
+        )
+        db.create_heuristic_rule(
+            rule_id=_make_id(),
+            name="disabled-rule",
+            risk_level="low",
+            confidence=0.3,
+            recommendation="deny",
+            tool_pattern="tool_b",
+            enabled=False,
+        )
+        enabled = db.list_heuristic_rules(enabled_only=True)
+        assert len(enabled) == 1
+        assert enabled[0]["name"] == "enabled-rule"
+        assert enabled[0]["enabled"] is True
+
+    def test_update_heuristic_rule(self, db: SQLiteBackend) -> None:
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="orig-name",
+            risk_level="low",
+            confidence=0.5,
+            recommendation="review",
+            tool_pattern="orig_tool",
+        )
+        ok = db.update_heuristic_rule(
+            rid,
+            name="updated-name",
+            risk_level="high",
+            confidence=0.9,
+            recommendation="deny",
+            enabled=False,
+            builtin=True,
+        )
+        assert ok is True
+        r = db.get_heuristic_rule(rid)
+        assert r is not None
+        assert r["name"] == "updated-name"
+        assert r["risk_level"] == "high"
+        assert r["confidence"] == 0.9
+        assert r["recommendation"] == "deny"
+        assert r["enabled"] is False
+        assert r["builtin"] is True
+
+    def test_update_heuristic_rule_not_found(self, db: SQLiteBackend) -> None:
+        ok = db.update_heuristic_rule("nonexistent", name="x")
+        assert ok is False
+
+    def test_delete_heuristic_rule(self, db: SQLiteBackend) -> None:
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="delete-me",
+            risk_level="low",
+            confidence=0.3,
+            recommendation="review",
+            tool_pattern="temp_tool",
+        )
+        ok = db.delete_heuristic_rule(rid)
+        assert ok is True
+        assert db.get_heuristic_rule(rid) is None
+
+    def test_delete_heuristic_rule_not_found(self, db: SQLiteBackend) -> None:
+        ok = db.delete_heuristic_rule("nonexistent")
+        assert ok is False
+
+    def test_create_duplicate_id_noop(self, db: SQLiteBackend) -> None:
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="first-insert",
+            risk_level="high",
+            confidence=0.8,
+            recommendation="approve",
+            tool_pattern="tool_orig",
+        )
+        # Second insert with same ID should be no-op (OR IGNORE)
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="second-insert",
+            risk_level="low",
+            confidence=0.1,
+            recommendation="deny",
+            tool_pattern="tool_new",
+        )
+        r = db.get_heuristic_rule(rid)
+        assert r is not None
+        assert r["name"] == "first-insert"  # original preserved
+        assert r["risk_level"] == "high"
+
+    def test_defaults(self, db: SQLiteBackend) -> None:
+        """Verify default values for optional fields."""
+        rid = _make_id()
+        db.create_heuristic_rule(
+            rule_id=rid,
+            name="defaults-test",
+            risk_level="medium",
+            confidence=0.5,
+            recommendation="review",
+            tool_pattern="some_tool",
+        )
+        r = db.get_heuristic_rule(rid)
+        assert r is not None
+        assert r["arg_patterns"] == "[]"
+        assert r["intent_template"] == ""
+        assert r["reasoning_template"] == ""
+        assert r["tier"] == "medium"
+        assert r["priority"] == 0
+        assert r["builtin"] is False
+        assert r["enabled"] is True
+        assert r["created_by"] == ""
+
+
+class TestOutputGuardPatternStorage:
+    def test_create_and_get_output_guard_pattern(self, db: SQLiteBackend) -> None:
+        pid = _make_id()
+        db.create_output_guard_pattern(
+            pattern_id=pid,
+            name="aws-key-pattern",
+            category="credentials",
+            risk_level="high",
+            pattern=r"AKIA[0-9A-Z]{16}",
+            flag_name="aws_access_key",
+            annotation="AWS access key detected",
+            pattern_flags="IGNORECASE",
+            is_credential=True,
+            redact_label="[AWS_KEY]",
+            priority=100,
+            builtin=True,
+            enabled=True,
+            created_by="system",
+        )
+        p = db.get_output_guard_pattern(pid)
+        assert p is not None
+        assert p["pattern_id"] == pid
+        assert p["name"] == "aws-key-pattern"
+        assert p["category"] == "credentials"
+        assert p["risk_level"] == "high"
+        assert p["pattern"] == r"AKIA[0-9A-Z]{16}"
+        assert p["flag_name"] == "aws_access_key"
+        assert p["annotation"] == "AWS access key detected"
+        assert p["pattern_flags"] == "IGNORECASE"
+        assert p["is_credential"] is True
+        assert p["redact_label"] == "[AWS_KEY]"
+        assert p["priority"] == 100
+        assert p["builtin"] is True
+        assert p["enabled"] is True
+        assert p["created_by"] == "system"
+
+    def test_get_output_guard_pattern_by_name(self, db: SQLiteBackend) -> None:
+        pid = _make_id()
+        db.create_output_guard_pattern(
+            pattern_id=pid,
+            name="lookup-by-name",
+            category="credentials",
+            risk_level="high",
+            pattern=r"ghp_[A-Za-z0-9_]{36}",
+            flag_name="github_pat",
+            annotation="GitHub PAT detected",
+        )
+        p = db.get_output_guard_pattern_by_name("lookup-by-name")
+        assert p is not None
+        assert p["pattern_id"] == pid
+        assert p["name"] == "lookup-by-name"
+
+    def test_get_output_guard_pattern_by_name_not_found(self, db: SQLiteBackend) -> None:
+        assert db.get_output_guard_pattern_by_name("nonexistent") is None
+
+    def test_list_output_guard_patterns(self, db: SQLiteBackend) -> None:
+        db.create_output_guard_pattern(
+            pattern_id=_make_id(),
+            name="secrets-high",
+            category="credentials",
+            risk_level="high",
+            pattern=r"secret_.*",
+            flag_name="generic_secret",
+            annotation="Secret detected",
+            priority=50,
+        )
+        db.create_output_guard_pattern(
+            pattern_id=_make_id(),
+            name="credentials-high",
+            category="credentials",
+            risk_level="high",
+            pattern=r"password=.*",
+            flag_name="password",
+            annotation="Password detected",
+            priority=100,
+        )
+        db.create_output_guard_pattern(
+            pattern_id=_make_id(),
+            name="credentials-low",
+            category="credentials",
+            risk_level="low",
+            pattern=r"token=test",
+            flag_name="test_token",
+            annotation="Test token",
+            priority=10,
+        )
+        patterns = db.list_output_guard_patterns()
+        assert len(patterns) == 3
+        # Ordered by category then priority desc
+        assert patterns[0]["name"] == "credentials-high"
+        assert patterns[1]["name"] == "secrets-high"
+        assert patterns[2]["name"] == "credentials-low"
+
+    def test_list_output_guard_patterns_enabled_only(self, db: SQLiteBackend) -> None:
+        db.create_output_guard_pattern(
+            pattern_id=_make_id(),
+            name="active-pattern",
+            category="credentials",
+            risk_level="high",
+            pattern=r"AKIA.*",
+            flag_name="aws_key",
+            annotation="AWS key",
+            enabled=True,
+        )
+        db.create_output_guard_pattern(
+            pattern_id=_make_id(),
+            name="inactive-pattern",
+            category="credentials",
+            risk_level="low",
+            pattern=r"test_.*",
+            flag_name="test",
+            annotation="Test pattern",
+            enabled=False,
+        )
+        enabled = db.list_output_guard_patterns(enabled_only=True)
+        assert len(enabled) == 1
+        assert enabled[0]["name"] == "active-pattern"
+        assert enabled[0]["enabled"] is True
+
+    def test_update_output_guard_pattern(self, db: SQLiteBackend) -> None:
+        pid = _make_id()
+        db.create_output_guard_pattern(
+            pattern_id=pid,
+            name="orig-pattern",
+            category="credentials",
+            risk_level="medium",
+            pattern=r"old_pattern",
+            flag_name="old_flag",
+            annotation="Old annotation",
+            is_credential=False,
+        )
+        ok = db.update_output_guard_pattern(
+            pid,
+            name="updated-pattern",
+            category="credentials",
+            risk_level="high",
+            pattern=r"new_pattern",
+            flag_name="new_flag",
+            annotation="Updated annotation",
+            is_credential=True,
+            enabled=False,
+            builtin=True,
+        )
+        assert ok is True
+        p = db.get_output_guard_pattern(pid)
+        assert p is not None
+        assert p["name"] == "updated-pattern"
+        assert p["category"] == "credentials"
+        assert p["risk_level"] == "high"
+        assert p["pattern"] == r"new_pattern"
+        assert p["flag_name"] == "new_flag"
+        assert p["annotation"] == "Updated annotation"
+        assert p["is_credential"] is True
+        assert p["enabled"] is False
+        assert p["builtin"] is True
+
+    def test_update_output_guard_pattern_not_found(self, db: SQLiteBackend) -> None:
+        ok = db.update_output_guard_pattern("nonexistent", name="x")
+        assert ok is False
+
+    def test_delete_output_guard_pattern(self, db: SQLiteBackend) -> None:
+        pid = _make_id()
+        db.create_output_guard_pattern(
+            pattern_id=pid,
+            name="delete-me",
+            category="credentials",
+            risk_level="low",
+            pattern=r"temp",
+            flag_name="temp_flag",
+            annotation="Temporary",
+        )
+        ok = db.delete_output_guard_pattern(pid)
+        assert ok is True
+        assert db.get_output_guard_pattern(pid) is None
+
+    def test_delete_output_guard_pattern_not_found(self, db: SQLiteBackend) -> None:
+        ok = db.delete_output_guard_pattern("nonexistent")
+        assert ok is False
+
+    def test_defaults(self, db: SQLiteBackend) -> None:
+        """Verify default values for optional fields."""
+        pid = _make_id()
+        db.create_output_guard_pattern(
+            pattern_id=pid,
+            name="defaults-test",
+            category="credentials",
+            risk_level="medium",
+            pattern=r"some_pattern",
+            flag_name="some_flag",
+            annotation="Some annotation",
+        )
+        p = db.get_output_guard_pattern(pid)
+        assert p is not None
+        assert p["pattern_flags"] == ""
+        assert p["is_credential"] is False
+        assert p["redact_label"] == ""
+        assert p["priority"] == 0
+        assert p["builtin"] is False
+        assert p["enabled"] is True
+        assert p["created_by"] == ""

tests/test_mcp_client.py

@@ -3,7 +3,9 @@
 from __future__ import annotations
 
 import asyncio
+import concurrent.futures
 import json
+import time
 from contextlib import AsyncExitStack
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
@@ -141,7 +143,7 @@ class TestMcpToOpenai:
         assert result["type"] == "function"
         func = result["function"]
         assert func["name"] == "mcp__github__search_repos"
-        assert "[MCP: github]" in func["description"]
+        assert func["description"] == "Search GitHub repos"
         assert func["parameters"]["type"] == "object"
         assert "query" in func["parameters"]["properties"]
 
@@ -164,7 +166,7 @@ class TestMcpToOpenai:
         tool.description = ""
         tool.inputSchema = {"type": "object", "properties": {}}
         result = _mcp_to_openai("test", tool)
-        assert result["function"]["description"] == "[MCP: test] "
+        assert result["function"]["description"] == ""
 
 
 # ---------------------------------------------------------------------------
@@ -304,7 +306,7 @@ class TestMCPClientManager:
     def test_call_tool_sync_disconnected_server(self):
         mgr = MCPClientManager({})
         mgr._tool_map["mcp__dead__ping"] = ("dead", "ping")
-        # No session registered for "dead"
+        # No session registered for "dead", no config/loop → reconnect fails
         with pytest.raises(RuntimeError, match="not connected"):
             mgr.call_tool_sync("mcp__dead__ping", {})
 
@@ -1553,3 +1555,407 @@ class TestSafeCloseStack:
             await MCPClientManager._safe_close_stack(stack)
 
         asyncio.run(_run())
+
+
+# ---------------------------------------------------------------------------
+# Fix 1: Cancel orphaned futures on timeout
+# ---------------------------------------------------------------------------
+
+
+class TestFutureCancellation:
+    """Verify future.cancel() is called when sync bridge methods time out."""
+
+    def _make_manager_with_session(self) -> MCPClientManager:
+        mgr = MCPClientManager({"test": {"type": "stdio", "command": "echo"}})
+        mock_session = MagicMock()
+        # Prevent auto-spec from creating async coroutines that trigger warnings
+        mock_session.call_tool = MagicMock(return_value="sentinel")
+        mock_session.read_resource = MagicMock(return_value="sentinel")
+        mock_session.get_prompt = MagicMock(return_value="sentinel")
+        mgr._sessions["test"] = mock_session
+        mgr._loop = MagicMock()
+        mgr._tool_map["mcp__test__search"] = ("test", "search")
+        mgr._resource_map["file:///a.txt"] = ("test", "file:///a.txt")
+        mgr._prompt_map["mcp__test__review"] = ("test", "review")
+        return mgr
+
+    def test_call_tool_sync_cancels_future_on_timeout(self):
+        mgr = self._make_manager_with_session()
+        mock_future = MagicMock()
+        mock_future.result.side_effect = concurrent.futures.TimeoutError()
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(TimeoutError, match="timed out"),
+        ):
+            mgr.call_tool_sync("mcp__test__search", {"query": "x"}, timeout=1)
+        mock_future.cancel.assert_called_once()
+
+    def test_read_resource_sync_cancels_future_on_timeout(self):
+        mgr = self._make_manager_with_session()
+        mock_future = MagicMock()
+        mock_future.result.side_effect = concurrent.futures.TimeoutError()
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(TimeoutError, match="timed out"),
+        ):
+            mgr.read_resource_sync("file:///a.txt", timeout=1)
+        mock_future.cancel.assert_called_once()
+
+    def test_get_prompt_sync_cancels_future_on_timeout(self):
+        mgr = self._make_manager_with_session()
+        mock_future = MagicMock()
+        mock_future.result.side_effect = concurrent.futures.TimeoutError()
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(TimeoutError, match="timed out"),
+        ):
+            mgr.get_prompt_sync("mcp__test__review", timeout=1)
+        mock_future.cancel.assert_called_once()
+
+    def test_refresh_sync_cancels_future_on_timeout(self):
+        mgr = MCPClientManager({})
+        mgr._loop = MagicMock()
+        mock_future = MagicMock()
+        mock_future.result.side_effect = concurrent.futures.TimeoutError()
+        with (
+            patch.object(mgr, "_refresh_all", return_value=MagicMock()),
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(TimeoutError, match="timed out"),
+        ):
+            mgr.refresh_sync(timeout=1)
+        mock_future.cancel.assert_called_once()
+
+
+# ---------------------------------------------------------------------------
+# Fix 2: Per-server circuit breaker
+# ---------------------------------------------------------------------------
+
+
+class TestCircuitBreaker:
+    """Verify per-server circuit breaker behavior."""
+
+    def test_circuit_stays_closed_below_threshold(self):
+        mgr = MCPClientManager({})
+        mgr._cb_record_failure("srv")
+        mgr._cb_record_failure("srv")
+        is_open, _ = mgr._cb_check("srv")
+        assert not is_open
+
+    def test_circuit_opens_at_threshold(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        is_open, cooldown_expired = mgr._cb_check("srv")
+        assert is_open
+        assert not cooldown_expired  # just opened, cooldown not expired
+
+    def test_circuit_half_open_after_cooldown(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        # Simulate cooldown expiry
+        mgr._circuit_open_until["srv"] = time.monotonic() - 1
+        is_open, cooldown_expired = mgr._cb_check("srv")
+        assert is_open
+        assert cooldown_expired
+
+    def test_circuit_resets_on_success(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        assert "srv" in mgr._circuit_open_until
+        mgr._cb_record_success("srv")
+        is_open, _ = mgr._cb_check("srv")
+        assert not is_open
+        assert mgr._consecutive_failures.get("srv") is None
+
+    def test_success_decays_trip_count(self):
+        """Success decays trip_count by 1 so flapping servers escalate backoff."""
+        mgr = MCPClientManager({})
+        mgr._circuit_trip_count["srv"] = 3
+        mgr._cb_record_success("srv")
+        assert mgr._circuit_trip_count["srv"] == 2
+        mgr._cb_record_success("srv")
+        assert mgr._circuit_trip_count["srv"] == 1
+        mgr._cb_record_success("srv")
+        assert "srv" not in mgr._circuit_trip_count
+
+    def test_cooldown_is_exponential(self):
+        mgr = MCPClientManager({})
+        # First trip (trip_count starts at 0)
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        deadline1 = mgr._circuit_open_until["srv"]
+        base1 = deadline1 - time.monotonic()
+        # Reset circuit but keep trip_count at 1 (set by first trip)
+        mgr._cb_record_success("srv")
+        # trip_count decayed from 1 to 0 — manually set to 1 for test
+        mgr._circuit_trip_count["srv"] = 1
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        deadline2 = mgr._circuit_open_until["srv"]
+        base2 = deadline2 - time.monotonic()
+        # Second trip should have longer cooldown (roughly 2x, within jitter)
+        assert base2 > base1 * 1.5
+
+    def test_cooldown_capped_at_max(self):
+        mgr = MCPClientManager({})
+        mgr._circuit_trip_count["srv"] = 100  # very high trip count
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        deadline = mgr._circuit_open_until["srv"]
+        cooldown = deadline - time.monotonic()
+        # Should not exceed max (300s) + 10% jitter = 330s
+        assert cooldown <= mgr._CB_MAX_COOLDOWN * 1.11
+
+    def test_cb_gate_rejects_when_open(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        with pytest.raises(RuntimeError, match="circuit open"):
+            mgr._cb_gate("srv")
+
+    def test_cb_gate_allows_after_cooldown(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        mgr._circuit_open_until["srv"] = time.monotonic() - 1
+        # Should not raise
+        mgr._cb_gate("srv")
+        # Deadline should be removed (half-open probe allowed)
+        assert "srv" not in mgr._circuit_open_until
+
+    def test_cb_clear_removes_all_state(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        mgr._cb_clear("srv")
+        assert "srv" not in mgr._consecutive_failures
+        assert "srv" not in mgr._circuit_open_until
+        assert "srv" not in mgr._circuit_trip_count
+
+    @pytest.mark.filterwarnings("ignore::pytest.PytestUnraisableExceptionWarning")
+    @pytest.mark.filterwarnings("ignore:coroutine.*was never awaited:RuntimeWarning")
+    def test_call_tool_sync_records_failure_on_timeout(self):
+        mgr = MCPClientManager({"test": {"type": "stdio", "command": "echo"}})
+        mock_session = MagicMock()
+        mock_session.call_tool = MagicMock(return_value="sentinel")
+        mgr._sessions["test"] = mock_session
+        mgr._loop = MagicMock()
+        mgr._tool_map["mcp__test__ping"] = ("test", "ping")
+        mock_future = MagicMock()
+        mock_future.result.side_effect = concurrent.futures.TimeoutError()
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(TimeoutError),
+        ):
+            mgr.call_tool_sync("mcp__test__ping", {}, timeout=1)
+        assert mgr._consecutive_failures.get("test", 0) == 1
+
+    def test_call_tool_sync_records_success(self):
+        mgr = MCPClientManager({"test": {"type": "stdio", "command": "echo"}})
+        mock_session = MagicMock()
+        mock_session.call_tool = MagicMock(return_value="sentinel")
+        mgr._sessions["test"] = mock_session
+        mgr._loop = MagicMock()
+        mgr._tool_map["mcp__test__ping"] = ("test", "ping")
+        # Pre-set a failure
+        mgr._consecutive_failures["test"] = 2
+        mock_result = MagicMock()
+        mock_result.content = []
+        mock_result.isError = False
+        mock_future = MagicMock()
+        mock_future.result.return_value = mock_result
+        with patch("asyncio.run_coroutine_threadsafe", return_value=mock_future):
+            mgr.call_tool_sync("mcp__test__ping", {}, timeout=5)
+        assert mgr._consecutive_failures.get("test") is None
+
+    def test_connection_error_evicts_session(self):
+        mgr = MCPClientManager({"test": {"type": "stdio", "command": "echo"}})
+        mock_session = MagicMock()
+        mock_session.call_tool = MagicMock(return_value="sentinel")
+        mgr._sessions["test"] = mock_session
+        mgr._loop = MagicMock()
+        mgr._tool_map["mcp__test__ping"] = ("test", "ping")
+        mock_future = MagicMock()
+        mock_future.result.side_effect = BrokenPipeError("dead")
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(BrokenPipeError),
+        ):
+            mgr.call_tool_sync("mcp__test__ping", {}, timeout=5)
+        assert "test" not in mgr._sessions
+
+    def test_independent_circuits_per_server(self):
+        mgr = MCPClientManager({})
+        for _ in range(3):
+            mgr._cb_record_failure("a")
+        is_open_a, _ = mgr._cb_check("a")
+        is_open_b, _ = mgr._cb_check("b")
+        assert is_open_a
+        assert not is_open_b
+
+    def test_mcp_error_does_not_trip_circuit(self):
+        """Protocol errors (McpError) should not count as transport failures."""
+        from mcp import McpError
+        from mcp.types import ErrorData
+
+        mgr = MCPClientManager({"test": {"type": "stdio", "command": "echo"}})
+        mock_session = MagicMock()
+        mock_session.call_tool = MagicMock(return_value="sentinel")
+        mgr._sessions["test"] = mock_session
+        mgr._loop = MagicMock()
+        mgr._tool_map["mcp__test__ping"] = ("test", "ping")
+        mock_future = MagicMock()
+        mock_future.result.side_effect = McpError(ErrorData(code=-32601, message="tool not found"))
+        with (
+            patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
+            pytest.raises(McpError),
+        ):
+            mgr.call_tool_sync("mcp__test__ping", {}, timeout=5)
+        # Circuit should NOT have recorded a failure
+        assert mgr._consecutive_failures.get("test", 0) == 0
+
+
+# ---------------------------------------------------------------------------
+# Fix 3: Safe transport stream pre-close
+# ---------------------------------------------------------------------------
+
+
+class TestSafeTransportStreams:
+    """Verify stream references are stored and pre-closed."""
+
+    def test_pre_close_streams_closes_both(self):
+        mgr = MCPClientManager({})
+        stream_a = MagicMock()
+        stream_b = MagicMock()
+        mgr._server_streams["srv"] = (stream_a, stream_b)
+
+        async def _run():
+            await mgr._pre_close_streams("srv")
+
+        asyncio.run(_run())
+        stream_a.aclose.assert_called_once()
+        stream_b.aclose.assert_called_once()
+        assert "srv" not in mgr._server_streams
+
+    def test_pre_close_streams_ignores_missing(self):
+        mgr = MCPClientManager({})
+
+        async def _run():
+            await mgr._pre_close_streams("nonexistent")
+
+        asyncio.run(_run())  # should not raise
+
+    def test_pre_close_streams_suppresses_errors(self):
+        mgr = MCPClientManager({})
+        stream_a = MagicMock()
+        stream_a.aclose.side_effect = RuntimeError("boom")
+        stream_b = MagicMock()
+        mgr._server_streams["srv"] = (stream_a, stream_b)
+
+        async def _run():
+            await mgr._pre_close_streams("srv")
+
+        asyncio.run(_run())  # should not raise despite stream_a error
+        stream_b.aclose.assert_called_once()
+
+    def test_shutdown_clears_stream_refs(self):
+        mgr = MCPClientManager({})
+        mgr._server_streams["srv"] = (MagicMock(), MagicMock())
+        mgr.shutdown()
+        assert len(mgr._server_streams) == 0
+
+
+# ---------------------------------------------------------------------------
+# Fix 4: Notification debounce
+# ---------------------------------------------------------------------------
+
+
+class TestNotificationDebounce:
+    """Verify notification-triggered refreshes are debounced."""
+
+    def test_debounce_within_window(self):
+        mgr = MCPClientManager({})
+        mgr._last_notification_refresh["srv"] = time.monotonic()
+        # We can't easily call _on_notification (it's a closure), so test
+        # the debounce logic directly via the timestamp check
+        now = time.monotonic()
+        last = mgr._last_notification_refresh.get("srv", 0.0)
+        assert now - last < mgr._NOTIFICATION_DEBOUNCE
+
+    def test_debounce_passes_after_window(self):
+        mgr = MCPClientManager({})
+        # Set timestamp well in the past
+        mgr._last_notification_refresh["srv"] = time.monotonic() - 10
+        now = time.monotonic()
+        last = mgr._last_notification_refresh.get("srv", 0.0)
+        assert now - last >= mgr._NOTIFICATION_DEBOUNCE
+
+    def test_debounce_is_per_server(self):
+        mgr = MCPClientManager({})
+        mgr._last_notification_refresh["srv_a"] = time.monotonic()
+        # srv_b has no timestamp — should pass debounce
+        now = time.monotonic()
+        last_b = mgr._last_notification_refresh.get("srv_b", 0.0)
+        assert now - last_b >= mgr._NOTIFICATION_DEBOUNCE
+
+
+# ---------------------------------------------------------------------------
+# Fix 5: Periodic refresh backoff
+# ---------------------------------------------------------------------------
+
+
+class TestPeriodicRefreshBackoff:
+    """Verify periodic refresh backoff and auto-reconnect."""
+
+    def test_backoff_set_on_failure(self):
+        mgr = MCPClientManager({})
+        mgr._refresh_failures["srv"] = 1
+        # Simulate what _periodic_refresh does on failure
+        failures = mgr._refresh_failures.get("srv", 0) + 1
+        mgr._refresh_failures["srv"] = failures
+        backoff = min(mgr._REFRESH_BACKOFF_BASE * (2 ** (failures - 1)), mgr._REFRESH_BACKOFF_MAX)
+        mgr._refresh_backoff_until["srv"] = time.monotonic() + backoff
+        assert mgr._refresh_backoff_until["srv"] > time.monotonic()
+        assert failures == 2
+
+    def test_backoff_doubles(self):
+        mgr = MCPClientManager({})
+        b1 = min(mgr._REFRESH_BACKOFF_BASE * (2**0), mgr._REFRESH_BACKOFF_MAX)
+        b2 = min(mgr._REFRESH_BACKOFF_BASE * (2**1), mgr._REFRESH_BACKOFF_MAX)
+        b3 = min(mgr._REFRESH_BACKOFF_BASE * (2**2), mgr._REFRESH_BACKOFF_MAX)
+        assert b1 == 60
+        assert b2 == 120
+        assert b3 == 240
+
+    def test_backoff_capped(self):
+        mgr = MCPClientManager({})
+        b = min(mgr._REFRESH_BACKOFF_BASE * (2**20), mgr._REFRESH_BACKOFF_MAX)
+        assert b == mgr._REFRESH_BACKOFF_MAX
+
+    def test_backoff_clears_on_success(self):
+        mgr = MCPClientManager({})
+        mgr._refresh_failures["srv"] = 3
+        mgr._refresh_backoff_until["srv"] = time.monotonic() + 1000
+        # Simulate success
+        mgr._refresh_failures.pop("srv", None)
+        mgr._refresh_backoff_until.pop("srv", None)
+        assert "srv" not in mgr._refresh_failures
+        assert "srv" not in mgr._refresh_backoff_until
+
+    def test_server_status_includes_circuit_info(self):
+        mgr = MCPClientManager({"srv": {"type": "stdio", "command": "echo"}})
+        status = mgr.get_server_status("srv")
+        assert "circuit_open" in status
+        assert "consecutive_failures" in status
+        assert status["circuit_open"] is False
+        assert status["consecutive_failures"] == 0
+
+    def test_server_status_shows_open_circuit(self):
+        mgr = MCPClientManager({"srv": {"type": "stdio", "command": "echo"}})
+        for _ in range(3):
+            mgr._cb_record_failure("srv")
+        status = mgr.get_server_status("srv")
+        assert status["circuit_open"] is True
+        assert status["consecutive_failures"] == 3

tests/test_model_registry.py

@@ -762,8 +762,12 @@ class TestSessionAgentModel:
     def test_agent_model_resolved(self) -> None:
         reg = ModelRegistry(
             models={
-                "main": ModelConfig("main", "http://m/v1", "k", "main-model"),
-                "agent": ModelConfig("agent", "http://a/v1", "k", "agent-model"),
+                "main": ModelConfig(
+                    "main", "http://m/v1", "k", "main-model", provider="openai-compatible"
+                ),
+                "agent": ModelConfig(
+                    "agent", "http://a/v1", "k", "agent-model", provider="openai-compatible"
+                ),
             },
             default="main",
             agent_model="agent",
@@ -948,71 +952,113 @@ class TestExtractContextWindow:
         m.model_dump.return_value = {}
         assert _extract_context_window(m, "openai") is None
 
+    # Model-change detection via active probes was removed.
+    # Backend health is now tracked passively (see test_healthcheck.py).
 
-class TestHealthMonitorModelChange:
-    def test_model_change_fires_callback(self) -> None:
-        from turnstone.core.healthcheck import BackendHealthMonitor
 
-        changes: list[tuple[str, int | None]] = []
+# ---------------------------------------------------------------------------
+# load_model_registry — DB-only startup (no CLI model)
+# ---------------------------------------------------------------------------
 
-        def on_change(model_id: str, ctx: int | None) -> None:
-            changes.append((model_id, ctx))
 
-        client = MagicMock()
-        monitor = BackendHealthMonitor(
-            client=client,
-            provider="openai",
-            initial_model="model-a",
-            on_model_changed=on_change,
+class TestLoadModelRegistryDBOnly:
+    """Tests for starting the server with models defined only in DB/config,
+    without any CLI --model argument."""
+
+    def test_db_only_no_cli_model(self) -> None:
+        """Registry builds from DB models when model='' (no CLI model)."""
+        storage = _MockStorage(
+            [
+                {
+                    "alias": "cloud",
+                    "model": "gpt-5",
+                    "provider": "openai",
+                    "base_url": "https://api.openai.com/v1",
+                    "api_key": "sk-test",
+                    "context_window": 128000,
+                    "capabilities": "{}",
+                    "enabled": True,
+                },
+            ]
         )
+        with patch("turnstone.core.model_registry.load_config", return_value={}):
+            reg = load_model_registry(model="", storage=storage)
+        assert reg.count == 1
+        assert reg.has_alias("cloud")
+        # "cloud" should be picked as default since "default" doesn't exist
+        assert reg.default == "cloud"
 
-        # Simulate probe returning a different model
-        resp = MagicMock()
-        m = MagicMock()
-        m.id = "model-b"
-        m.model_dump.return_value = {"max_model_len": 131072}
-        resp.data = [m]
-
-        monitor._check_model_change(resp)
-        assert len(changes) == 1
-        assert changes[0] == ("model-b", 131072)
-        assert monitor._last_detected_model == "model-b"
-
-    def test_same_model_no_callback(self) -> None:
-        from turnstone.core.healthcheck import BackendHealthMonitor
-
-        changes: list[tuple[str, int | None]] = []
-
-        def on_change(model_id: str, ctx: int | None) -> None:
-            changes.append((model_id, ctx))
-
-        client = MagicMock()
-        monitor = BackendHealthMonitor(
-            client=client,
-            provider="openai",
-            initial_model="model-a",
-            on_model_changed=on_change,
+    def test_db_only_with_config_default(self) -> None:
+        """Config [model].default is respected when it matches a DB alias."""
+        storage = _MockStorage(
+            [
+                {
+                    "alias": "fast",
+                    "model": "gpt-4o-mini",
+                    "provider": "openai",
+                    "base_url": "https://api.openai.com/v1",
+                    "api_key": "sk-test",
+                    "context_window": 128000,
+                    "capabilities": "{}",
+                    "enabled": True,
+                },
+                {
+                    "alias": "smart",
+                    "model": "gpt-5",
+                    "provider": "openai",
+                    "base_url": "https://api.openai.com/v1",
+                    "api_key": "sk-test",
+                    "context_window": 128000,
+                    "capabilities": "{}",
+                    "enabled": True,
+                },
+            ]
         )
+        fake_cfg: dict[str, Any] = {"model": {"default": "smart"}}
+        with patch("turnstone.core.model_registry.load_config", return_value=fake_cfg):
+            reg = load_model_registry(model="", storage=storage)
+        assert reg.default == "smart"
 
-        resp = MagicMock()
-        m = MagicMock()
-        m.id = "model-a"
-        m.model_dump.return_value = {}
-        resp.data = [m]
+    def test_config_toml_only_no_cli_model(self) -> None:
+        """Registry builds from config.toml [models.*] when model=''."""
+        fake_cfg: dict[str, Any] = {
+            "models": {
+                "local": {
+                    "model": "qwen3-32b",
+                    "base_url": "http://localhost:8000/v1",
+                    "api_key": "dummy",
+                },
+            },
+        }
+        with patch("turnstone.core.model_registry.load_config", return_value=fake_cfg):
+            reg = load_model_registry(model="")
+        assert reg.count == 1
+        assert reg.default == "local"
 
-        monitor._check_model_change(resp)
-        assert len(changes) == 0
+    def test_no_models_anywhere_raises(self) -> None:
+        """ValueError when no models from CLI, config, or DB."""
+        with (
+            patch("turnstone.core.model_registry.load_config", return_value={}),
+            pytest.raises(ValueError, match="No model definitions found"),
+        ):
+            load_model_registry(model="")
 
-    def test_no_callback_configured(self) -> None:
-        from turnstone.core.healthcheck import BackendHealthMonitor
-
-        client = MagicMock()
-        monitor = BackendHealthMonitor(client=client, initial_model="model-a")
-
-        resp = MagicMock()
-        m = MagicMock()
-        m.id = "model-b"
-        resp.data = [m]
-
-        # Should not raise
-        monitor._check_model_change(resp)
+    def test_no_default_entry_created_when_model_empty(self) -> None:
+        """When model='', no 'default' alias is created from CLI args."""
+        storage = _MockStorage(
+            [
+                {
+                    "alias": "cloud",
+                    "model": "gpt-5",
+                    "provider": "openai",
+                    "base_url": "https://api.openai.com/v1",
+                    "api_key": "sk-test",
+                    "context_window": 128000,
+                    "capabilities": "{}",
+                    "enabled": True,
+                },
+            ]
+        )
+        with patch("turnstone.core.model_registry.load_config", return_value={}):
+            reg = load_model_registry(model="", storage=storage)
+        assert not reg.has_alias("default")

tests/test_output_guard.py

@@ -224,3 +224,74 @@ class TestTimeBudget:
         )
         # Should still find the highest-priority check
         assert r.risk_level in ("none", "high")  # either found it or ran out
+
+
+class TestConfigurablePatterns:
+    """Tests for evaluate_output() with configurable patterns kwarg."""
+
+    def test_custom_patterns_detect(self):
+        """Custom patterns detect matching output."""
+        import re
+
+        from turnstone.core.output_guard import OutputGuardPatternDef, evaluate_output
+
+        custom_patterns = {
+            "prompt_injection": (
+                OutputGuardPatternDef(
+                    name="test-pattern",
+                    category="prompt_injection",
+                    risk_level="high",
+                    compiled=re.compile(r"EVIL_MARKER"),
+                    flag_name="test_flag",
+                    annotation="Test annotation",
+                ),
+            ),
+        }
+        result = evaluate_output("This contains EVIL_MARKER in output", patterns=custom_patterns)
+        assert "test_flag" in result.flags
+        assert result.risk_level == "high"
+        assert "Test annotation" in result.annotations
+
+    def test_custom_patterns_clean_output(self):
+        """Clean output produces no flags with custom patterns."""
+        from turnstone.core.output_guard import evaluate_output
+
+        result = evaluate_output("Hello world", patterns={})
+        assert result.risk_level == "none"
+        assert result.flags == []
+
+    def test_none_patterns_uses_builtins(self):
+        """When patterns=None, legacy built-in checks are used (backward compat)."""
+        from turnstone.core.output_guard import evaluate_output
+
+        result = evaluate_output("ignore your previous instructions", patterns=None)
+        assert "prompt_injection" in result.flags
+
+    def test_custom_credential_pattern_redacts(self):
+        """Custom credential patterns trigger redaction."""
+        import re
+
+        from turnstone.core.output_guard import OutputGuardPatternDef, evaluate_output
+
+        custom_patterns = {
+            "credentials": (
+                OutputGuardPatternDef(
+                    name="test-cred",
+                    category="credentials",
+                    risk_level="high",
+                    compiled=re.compile(r"SECRET_[A-Z0-9]{10,}"),
+                    flag_name="credential_leak",
+                    annotation="Test credential detected",
+                    is_credential=True,
+                    redact_label="test_secret",
+                ),
+            ),
+        }
+        result = evaluate_output(
+            "Found key: SECRET_ABCDEF1234567890",
+            patterns=custom_patterns,
+        )
+        assert "credential_leak" in result.flags
+        assert result.sanitized is not None
+        assert "[REDACTED:test_secret]" in result.sanitized
+        assert "SECRET_ABCDEF1234567890" not in result.sanitized

tests/test_prompt_templates_runtime.py

@@ -403,7 +403,7 @@ class TestMCPTemplates:
 
 
 class TestResumeDeletedTemplate:
-    def test_resume_with_deleted_template_degrades_gracefully(self, tmp_db, capsys):
+    def test_resume_with_deleted_template_degrades_gracefully(self, tmp_db, caplog):
         from turnstone.core.memory import save_message
         from turnstone.core.storage import get_storage
 
@@ -430,8 +430,7 @@ class TestResumeDeletedTemplate:
         content = _sys_content(session2)
         assert "EPHEMERAL_CONTENT" not in content
         # Warning should be logged via structlog
-        captured = capsys.readouterr()
-        assert "not_found" in captured.out or "not_found" in captured.err
+        assert "not_found" in caplog.text
 
 
 # ---------------------------------------------------------------------------

tests/test_providers.py

@@ -9,9 +9,18 @@ from unittest.mock import MagicMock, PropertyMock, patch
 import pytest
 
 from turnstone.core.providers._openai import OpenAIProvider
+from turnstone.core.providers._openai_chat import OpenAIChatCompletionsProvider
+from turnstone.core.providers._openai_common import (
+    apply_cache_retention,
+    apply_temperature_and_effort,
+    apply_tool_search,
+    format_citations,
+    sanitize_messages,
+)
 from turnstone.core.providers._protocol import (
     CompletionResult,
     LLMProvider,
+    ModelCapabilities,
     StreamChunk,
     ToolCallDelta,
     UsageInfo,
@@ -133,38 +142,38 @@ def _anthropic_event(
 
 
 class TestOpenAIProvider:
-    """Tests for the OpenAI-compatible provider adapter."""
+    """Tests for the OpenAI Chat Completions provider adapter."""
 
     def setup_method(self) -> None:
         self.provider = OpenAIProvider()
 
     def test_provider_name(self) -> None:
-        assert self.provider.provider_name == "openai"
+        assert self.provider.provider_name == "openai-compatible"
 
     # -- _sanitize_messages ---------------------------------------------------
 
     def test_sanitize_messages_none_content_no_tool_calls(self) -> None:
         msgs = [{"role": "assistant", "content": None}]
-        assert self.provider._sanitize_messages(msgs) == [{"role": "assistant", "content": ""}]
+        assert sanitize_messages(msgs) == [{"role": "assistant", "content": ""}]
 
     def test_sanitize_messages_none_content_with_tool_calls(self) -> None:
         msgs = [{"role": "assistant", "content": None, "tool_calls": [{"id": "1"}]}]
-        result = self.provider._sanitize_messages(msgs)
+        result = sanitize_messages(msgs)
         assert result[0]["content"] is None
         assert result[0]["tool_calls"] == [{"id": "1"}]
 
     def test_sanitize_messages_empty_string_passthrough(self) -> None:
         msgs = [{"role": "assistant", "content": ""}]
-        assert self.provider._sanitize_messages(msgs) == msgs
+        assert sanitize_messages(msgs) == msgs
 
     def test_sanitize_messages_non_assistant_unchanged(self) -> None:
         msgs = [{"role": "user", "content": None}]
-        result = self.provider._sanitize_messages(msgs)
+        result = sanitize_messages(msgs)
         assert result[0]["content"] is None
 
     def test_sanitize_messages_does_not_mutate_original(self) -> None:
         original = {"role": "assistant", "content": None}
-        self.provider._sanitize_messages([original])
+        sanitize_messages([original])
         assert original["content"] is None
 
     # -- convert_tools --------------------------------------------------------
@@ -992,10 +1001,10 @@ class TestProviderFactory:
     """Tests for create_provider and create_client factory functions."""
 
     def test_create_provider_openai(self) -> None:
-        from turnstone.core.providers import create_provider
+        from turnstone.core.providers import OpenAIResponsesProvider, create_provider
 
         provider = create_provider("openai")
-        assert isinstance(provider, OpenAIProvider)
+        assert isinstance(provider, OpenAIResponsesProvider)
         assert provider.provider_name == "openai"
 
     def test_create_provider_anthropic(self) -> None:
@@ -1040,6 +1049,24 @@ class TestProviderFactory:
 
         assert not isinstance(NotAProvider(), LLMProvider)
 
+    def test_create_provider_openai_compatible(self) -> None:
+        from turnstone.core.providers import create_provider
+
+        provider = create_provider("openai-compatible")
+        assert isinstance(provider, OpenAIChatCompletionsProvider)
+        assert provider.provider_name == "openai-compatible"
+
+    def test_create_provider_openai_vs_compatible_distinct(self) -> None:
+        from turnstone.core.providers import OpenAIResponsesProvider, create_provider
+
+        openai_prov = create_provider("openai")
+        compat = create_provider("openai-compatible")
+        assert openai_prov is not compat
+        assert isinstance(openai_prov, OpenAIResponsesProvider)
+        assert isinstance(compat, OpenAIChatCompletionsProvider)
+        assert openai_prov.provider_name == "openai"
+        assert compat.provider_name == "openai-compatible"
+
     def test_create_provider_returns_singleton(self) -> None:
         from turnstone.core.providers import create_provider
 
@@ -1111,7 +1138,7 @@ class TestOpenAIParameterGating:
         """Unknown/local models should NOT receive top-level reasoning_effort."""
         caps = self.provider.get_capabilities("my-local-model")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="medium")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="medium")
         assert "reasoning_effort" not in kwargs
         assert kwargs["temperature"] == 0.7
 
@@ -1119,7 +1146,7 @@ class TestOpenAIParameterGating:
         """GPT-5 base: no temperature, reasoning_effort sent."""
         caps = self.provider.get_capabilities("gpt-5")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="high")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="high")
         assert "temperature" not in kwargs
         assert kwargs["reasoning_effort"] == "high"
 
@@ -1127,7 +1154,7 @@ class TestOpenAIParameterGating:
         """GPT-5.1: temperature only when reasoning_effort='none'."""
         caps = self.provider.get_capabilities("gpt-5.1")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="none")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="none")
         assert kwargs["temperature"] == 0.7
         assert "reasoning_effort" not in kwargs  # "none" is skipped
 
@@ -1135,7 +1162,7 @@ class TestOpenAIParameterGating:
         """GPT-5.1: no temperature when reasoning is active."""
         caps = self.provider.get_capabilities("gpt-5.1")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="high")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="high")
         assert "temperature" not in kwargs
         assert kwargs["reasoning_effort"] == "high"
 
@@ -1143,7 +1170,7 @@ class TestOpenAIParameterGating:
         """O-series: no temperature, no reasoning_effort."""
         caps = self.provider.get_capabilities("o3")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="medium")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="medium")
         assert "temperature" not in kwargs
         assert "reasoning_effort" not in kwargs
 
@@ -1151,7 +1178,7 @@ class TestOpenAIParameterGating:
         """GPT-5 pro only supports 'high'; unsupported values fall back to default."""
         caps = self.provider.get_capabilities("gpt-5-pro")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="medium")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="medium")
         assert "temperature" not in kwargs
         assert kwargs["reasoning_effort"] == "high"  # fell back to default
 
@@ -1159,7 +1186,7 @@ class TestOpenAIParameterGating:
         """GPT-5 pro accepts 'high' directly."""
         caps = self.provider.get_capabilities("gpt-5-pro")
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="high")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="high")
         assert kwargs["reasoning_effort"] == "high"
 
     def test_gpt54_1m_context_and_effort(self) -> None:
@@ -1167,11 +1194,11 @@ class TestOpenAIParameterGating:
         caps = self.provider.get_capabilities("gpt-5.4")
         assert caps.context_window == 1050000
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="none")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="none")
         assert kwargs["temperature"] == 0.7
         assert "reasoning_effort" not in kwargs
         kwargs2: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs2, caps, temperature=0.7, reasoning_effort="xhigh")
+        apply_temperature_and_effort(kwargs2, caps, temperature=0.7, reasoning_effort="xhigh")
         assert "temperature" not in kwargs2
         assert kwargs2["reasoning_effort"] == "xhigh"
 
@@ -1180,7 +1207,7 @@ class TestOpenAIParameterGating:
         caps = self.provider.get_capabilities("gpt-5.4-pro")
         assert caps.context_window == 1050000
         kwargs: dict[str, Any] = {}
-        self.provider._apply_model_params(kwargs, caps, temperature=0.7, reasoning_effort="low")
+        apply_temperature_and_effort(kwargs, caps, temperature=0.7, reasoning_effort="low")
         assert "temperature" not in kwargs
         assert kwargs["reasoning_effort"] == "medium"  # fell back from unsupported "low"
 
@@ -1827,7 +1854,7 @@ class TestOpenAIWebSearch:
         ann.url_citation = citation
 
         content = "Some search result text."
-        result = OpenAIProvider._format_citations(content, [ann])
+        result = format_citations(content, [ann])
         assert "Sources:" in result
         assert "[Example Page](https://example.com)" in result
 
@@ -1842,7 +1869,7 @@ class TestOpenAIWebSearch:
         ann2.url_citation = MagicMock(title="Page Again", url="https://example.com")
 
         content = "Text."
-        result = OpenAIProvider._format_citations(content, [ann1, ann2])
+        result = format_citations(content, [ann1, ann2])
         assert result.count("example.com") == 1
 
     def test_format_citations_skips_non_url_citation(self) -> None:
@@ -1851,7 +1878,7 @@ class TestOpenAIWebSearch:
         ann.type = "something_else"
 
         content = "Text."
-        result = OpenAIProvider._format_citations(content, [ann])
+        result = format_citations(content, [ann])
         assert "Sources:" not in result
 
     def test_format_citations_empty_title(self) -> None:
@@ -1860,7 +1887,7 @@ class TestOpenAIWebSearch:
         ann.type = "url_citation"
         ann.url_citation = MagicMock(title="", url="https://example.com")
 
-        result = OpenAIProvider._format_citations("Text.", [ann])
+        result = format_citations("Text.", [ann])
         assert "https://example.com" in result
         # Should not have markdown link format when title is empty
         assert "[](https://example.com)" not in result
@@ -1871,7 +1898,7 @@ class TestOpenAIWebSearch:
         ann.type = "url_citation"
         ann.url_citation = None
 
-        result = OpenAIProvider._format_citations("Text.", [ann])
+        result = format_citations("Text.", [ann])
         assert "Sources:" not in result
 
     def test_apply_web_search_with_no_tools(self) -> None:
@@ -2345,7 +2372,7 @@ class TestOpenAIToolSearch:
             },
         ]
         deferred = frozenset(["mcp__slack__send"])
-        result = provider._apply_tool_search(caps, tools, deferred)
+        result = apply_tool_search(caps, tools, deferred)
         assert result is not None
         # bash not deferred
         assert result[0].get("defer_loading") is None or result[0].get("defer_loading") is False
@@ -2357,7 +2384,7 @@ class TestOpenAIToolSearch:
         tools = [
             {"type": "function", "function": {"name": "bash", "description": "Run commands"}},
         ]
-        result = provider._apply_tool_search(caps, tools, None)
+        result = apply_tool_search(caps, tools, None)
         assert result == tools
 
     def test_apply_tool_search_no_op_on_unsupported_model(self, provider):
@@ -2366,7 +2393,7 @@ class TestOpenAIToolSearch:
             {"type": "function", "function": {"name": "bash", "description": "Run commands"}},
         ]
         deferred = frozenset(["some_tool"])
-        result = provider._apply_tool_search(caps, tools, deferred)
+        result = apply_tool_search(caps, tools, deferred)
         assert result == tools
 
 
@@ -2699,14 +2726,14 @@ class TestOpenAIPromptCaching:
         """GPT-5.x models get prompt_cache_retention=24h."""
         for model in ("gpt-5", "gpt-5.1", "gpt-5.2", "gpt-5.4", "gpt-5-mini", "gpt-5-pro"):
             kwargs: dict[str, Any] = {}
-            self.provider._apply_cache_retention(kwargs, model)
+            apply_cache_retention(kwargs, model)
             assert kwargs.get("prompt_cache_retention") == "24h", f"Failed for {model}"
 
     def test_cache_retention_not_set_for_non_gpt5(self) -> None:
         """Non-GPT-5 models do not get cache retention."""
         for model in ("o3", "o4-mini", "local-model", "gpt-4o"):
             kwargs: dict[str, Any] = {}
-            self.provider._apply_cache_retention(kwargs, model)
+            apply_cache_retention(kwargs, model)
             assert "prompt_cache_retention" not in kwargs, f"Unexpected retention for {model}"
 
     def test_streaming_cached_tokens_from_usage(self) -> None:
@@ -2845,3 +2872,529 @@ class TestMetricsCacheTokens:
         assert 'turnstone_tokens_total{type="cache_creation"} 800' in text
         assert 'turnstone_tokens_total{type="cache_read"} 200' in text
         assert 'turnstone_tokens_total{type="prompt"} 1000' in text
+
+
+# ===========================================================================
+# TestOpenAIResponsesProvider — Responses API provider
+# ===========================================================================
+
+
+class TestOpenAIResponsesProvider:
+    """Tests for the OpenAI Responses API provider."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def test_provider_name(self) -> None:
+        assert self.provider.provider_name == "openai"
+
+    def test_get_capabilities(self) -> None:
+        caps = self.provider.get_capabilities("gpt-5.4")
+        assert caps.context_window == 1050000
+        assert caps.supports_tool_search is True
+
+
+class TestResponsesMessageConversion:
+    """Tests for _convert_messages — Chat Completions format to Responses API."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def test_system_message_to_instructions(self) -> None:
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "Hello"},
+        ]
+        instructions, items = self.provider._convert_messages(messages)
+        assert instructions == "You are helpful."
+        assert len(items) == 1
+        assert items[0]["role"] == "user"
+        assert items[0]["content"] == "Hello"
+
+    def test_multiple_system_messages_concatenated(self) -> None:
+        messages = [
+            {"role": "system", "content": "Rule 1"},
+            {"role": "developer", "content": "Rule 2"},
+            {"role": "user", "content": "Hi"},
+        ]
+        instructions, items = self.provider._convert_messages(messages)
+        assert instructions == "Rule 1\n\nRule 2"
+        assert len(items) == 1
+
+    def test_assistant_text_message(self) -> None:
+        messages = [
+            {"role": "assistant", "content": "Hello back"},
+        ]
+        _, items = self.provider._convert_messages(messages)
+        assert len(items) == 1
+        assert items[0]["type"] == "message"
+        assert items[0]["role"] == "assistant"
+        assert items[0]["content"] == "Hello back"
+
+    def test_assistant_tool_calls(self) -> None:
+        messages = [
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "function": {"name": "read_file", "arguments": '{"path": "/tmp"}'},
+                    }
+                ],
+            },
+        ]
+        _, items = self.provider._convert_messages(messages)
+        assert len(items) == 1
+        assert items[0]["type"] == "function_call"
+        assert items[0]["call_id"] == "call_1"
+        assert items[0]["name"] == "read_file"
+        assert items[0]["arguments"] == '{"path": "/tmp"}'
+
+    def test_tool_result(self) -> None:
+        messages = [
+            {"role": "tool", "tool_call_id": "call_1", "content": "file contents"},
+        ]
+        _, items = self.provider._convert_messages(messages)
+        assert len(items) == 1
+        assert items[0]["type"] == "function_call_output"
+        assert items[0]["call_id"] == "call_1"
+        assert items[0]["output"] == "file contents"
+
+    def test_provider_content_ignored_with_store_false(self) -> None:
+        """With store=False, provider_content is ignored — rebuild from content."""
+        provider_items = [
+            {
+                "type": "message",
+                "role": "assistant",
+                "content": [{"type": "output_text", "text": "Hi"}],
+            },
+            {"type": "function_call", "call_id": "c1", "name": "f", "arguments": "{}"},
+        ]
+        messages = [
+            {"role": "assistant", "content": "Hi", "_provider_content": provider_items},
+        ]
+        _, items = self.provider._convert_messages(messages)
+        # Should rebuild from content, not passthrough provider_content
+        assert len(items) == 1
+        assert items[0]["type"] == "message"
+        assert items[0]["content"] == "Hi"
+
+    def test_no_system_returns_none_instructions(self) -> None:
+        messages = [{"role": "user", "content": "Hello"}]
+        instructions, _ = self.provider._convert_messages(messages)
+        assert instructions is None
+
+    def test_assistant_with_content_and_tool_calls(self) -> None:
+        """Assistant message with both text and tool calls emits separate items."""
+        messages = [
+            {
+                "role": "assistant",
+                "content": "I'll read that file",
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "function": {"name": "read_file", "arguments": '{"path": "/tmp"}'},
+                    }
+                ],
+            },
+        ]
+        _, items = self.provider._convert_messages(messages)
+        assert len(items) == 2
+        assert items[0]["type"] == "message"
+        assert items[0]["content"] == "I'll read that file"
+        assert items[1]["type"] == "function_call"
+        assert items[1]["name"] == "read_file"
+
+
+class TestResponsesToolConversion:
+    """Tests for _convert_tools — Chat Completions tool format to Responses API."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def test_function_tool_conversion(self) -> None:
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "read_file",
+                    "description": "Read a file",
+                    "parameters": {"type": "object", "properties": {"path": {"type": "string"}}},
+                },
+            }
+        ]
+        caps = ModelCapabilities()
+        result = self.provider._convert_tools(tools, caps)
+        assert result is not None
+        assert len(result) == 1
+        assert result[0]["type"] == "function"
+        assert result[0]["name"] == "read_file"
+        assert result[0]["description"] == "Read a file"
+        assert result[0]["strict"] is False
+
+    def test_web_search_replaced_with_native(self) -> None:
+        tools = [
+            {"type": "function", "function": {"name": "web_search", "description": "Search"}},
+            {"type": "function", "function": {"name": "read_file", "description": "Read"}},
+        ]
+        caps = ModelCapabilities(supports_web_search=True)
+        result = self.provider._convert_tools(tools, caps)
+        assert result is not None
+        names = [t.get("name", t.get("type")) for t in result]
+        assert "web_search" in names  # native web_search tool
+        assert "read_file" in names
+
+    def test_none_tools_returns_none(self) -> None:
+        caps = ModelCapabilities()
+        assert self.provider._convert_tools(None, caps) is None
+
+    def test_defer_loading_preserved(self) -> None:
+        tools = [
+            {"type": "function", "function": {"name": "f"}, "defer_loading": True},
+        ]
+        caps = ModelCapabilities()
+        result = self.provider._convert_tools(tools, caps)
+        assert result is not None
+        assert result[0].get("defer_loading") is True
+
+
+class TestResponsesParamBuilding:
+    """Tests for _build_kwargs — parameter construction for Responses API."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def test_reasoning_effort_as_dict(self) -> None:
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5.4",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="high",
+            deferred_names=None,
+        )
+        assert kwargs["reasoning"] == {"effort": "high"}
+        assert "reasoning_effort" not in kwargs
+
+    def test_no_reasoning_when_none_effort(self) -> None:
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5.4",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="none",
+            deferred_names=None,
+        )
+        assert "reasoning" not in kwargs
+
+    def test_store_is_false(self) -> None:
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5.4",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="medium",
+            deferred_names=None,
+        )
+        assert kwargs["store"] is False
+
+    def test_cache_retention_for_gpt5(self) -> None:
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5.4",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="medium",
+            deferred_names=None,
+        )
+        assert kwargs["prompt_cache_retention"] == "24h"
+
+    def test_instructions_from_system_messages(self) -> None:
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5.4",
+            messages=[
+                {"role": "system", "content": "Be helpful"},
+                {"role": "user", "content": "Hi"},
+            ],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="none",
+            deferred_names=None,
+        )
+        assert kwargs["instructions"] == "Be helpful"
+
+    def test_web_search_injected_with_no_tools(self) -> None:
+        """Search-capable models get web_search tool even when tools=None."""
+        kwargs = self.provider._build_kwargs(
+            model="gpt-5-search-api",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=None,
+            max_tokens=4096,
+            temperature=0.5,
+            reasoning_effort="none",
+            deferred_names=None,
+        )
+        assert "tools" in kwargs
+        tool_types = [t.get("type") for t in kwargs["tools"]]
+        assert "web_search" in tool_types
+
+
+class TestResponsesCitationFormat:
+    """Test format_citations handles Responses API flat annotation format."""
+
+    def test_responses_api_flat_annotation(self) -> None:
+        """Responses API annotations have title/url directly on the object."""
+
+        class FlatAnnotation:
+            type = "url_citation"
+            url_citation = None  # Not present in Responses API
+            title = "Example"
+            url = "https://example.com"
+
+        result = format_citations("Text.", [FlatAnnotation()])
+        assert "Sources:" in result
+        assert "[Example](https://example.com)" in result
+
+
+class TestResponsesStreaming:
+    """Tests for Responses API streaming event handling."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def _make_event(self, event_type: str, **attrs: Any) -> MagicMock:
+        event = MagicMock()
+        event.type = event_type
+        for k, v in attrs.items():
+            setattr(event, k, v)
+        return event
+
+    def test_text_delta(self) -> None:
+        events = [
+            self._make_event("response.output_text.delta", delta="Hello"),
+            self._make_event("response.output_text.delta", delta=" world"),
+            self._make_event(
+                "response.completed",
+                response=MagicMock(
+                    status="completed",
+                    usage=None,
+                ),
+            ),
+        ]
+        chunks = list(self.provider._iter_stream(iter(events)))
+        text_chunks = [c for c in chunks if c.content_delta]
+        assert len(text_chunks) == 2
+        assert text_chunks[0].content_delta == "Hello"
+        assert text_chunks[0].is_first is True
+        assert text_chunks[1].content_delta == " world"
+
+    def test_reasoning_delta(self) -> None:
+        events = [
+            self._make_event("response.reasoning_text.delta", delta="thinking..."),
+            self._make_event(
+                "response.completed",
+                response=MagicMock(
+                    status="completed",
+                    usage=None,
+                ),
+            ),
+        ]
+        chunks = list(self.provider._iter_stream(iter(events)))
+        reasoning = [c for c in chunks if c.reasoning_delta]
+        assert len(reasoning) == 1
+        assert reasoning[0].reasoning_delta == "thinking..."
+        assert reasoning[0].is_first is True
+
+    def test_tool_call_streaming(self) -> None:
+        item = MagicMock()
+        item.type = "function_call"
+        item.id = "fc_abc123"
+        item.call_id = "call_1"
+        item.name = "read_file"
+
+        events = [
+            self._make_event("response.output_item.added", item=item),
+            self._make_event(
+                "response.function_call_arguments.delta",
+                item_id="fc_abc123",
+                delta='{"path":',
+            ),
+            self._make_event(
+                "response.function_call_arguments.delta",
+                item_id="fc_abc123",
+                delta='"/tmp"}',
+            ),
+            self._make_event(
+                "response.completed",
+                response=MagicMock(
+                    status="completed",
+                    usage=None,
+                ),
+            ),
+        ]
+        chunks = list(self.provider._iter_stream(iter(events)))
+        tc_chunks = [c for c in chunks if c.tool_call_deltas]
+        assert len(tc_chunks) == 3
+        # First chunk: tool call added with name
+        assert tc_chunks[0].tool_call_deltas[0].name == "read_file"
+        assert tc_chunks[0].tool_call_deltas[0].id == "call_1"
+        # Argument deltas
+        assert tc_chunks[1].tool_call_deltas[0].arguments_delta == '{"path":'
+        assert tc_chunks[2].tool_call_deltas[0].arguments_delta == '"/tmp"}'
+
+    def test_completed_event_with_usage(self) -> None:
+        usage = MagicMock()
+        usage.input_tokens = 100
+        usage.output_tokens = 50
+        usage.total_tokens = 150
+        usage.input_tokens_details = MagicMock(cached_tokens=80)
+        # Ensure Chat Completions attributes are not present
+        del usage.prompt_tokens
+        del usage.completion_tokens
+        del usage.prompt_tokens_details
+
+        events = [
+            self._make_event(
+                "response.completed",
+                response=MagicMock(
+                    status="completed",
+                    usage=usage,
+                ),
+            ),
+        ]
+        chunks = list(self.provider._iter_stream(iter(events)))
+        final = [c for c in chunks if c.finish_reason]
+        assert len(final) == 1
+        assert final[0].finish_reason == "stop"
+        assert final[0].usage is not None
+        assert final[0].usage.prompt_tokens == 100
+        assert final[0].usage.completion_tokens == 50
+        assert final[0].usage.cache_read_tokens == 80
+
+    def test_web_search_events(self) -> None:
+        events = [
+            self._make_event("response.web_search_call.searching"),
+            self._make_event("response.web_search_call.completed"),
+            self._make_event(
+                "response.completed",
+                response=MagicMock(
+                    status="completed",
+                    usage=None,
+                ),
+            ),
+        ]
+        chunks = list(self.provider._iter_stream(iter(events)))
+        info = [c for c in chunks if c.info_delta]
+        assert len(info) == 2
+        assert "Searching" in info[0].info_delta
+        assert "complete" in info[1].info_delta
+
+
+class TestResponsesCompletion:
+    """Tests for non-streaming Responses API completion."""
+
+    def setup_method(self) -> None:
+        from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
+
+        self.provider = OpenAIResponsesProvider()
+
+    def _make_response(
+        self,
+        text: str = "Hello",
+        tool_calls: list[dict[str, Any]] | None = None,
+        status: str = "completed",
+    ) -> MagicMock:
+        resp = MagicMock()
+        resp.status = status
+        resp.usage = MagicMock()
+        resp.usage.input_tokens = 10
+        resp.usage.output_tokens = 5
+        resp.usage.total_tokens = 15
+        resp.usage.input_tokens_details = MagicMock(cached_tokens=0)
+        # Remove Chat Completions attributes
+        del resp.usage.prompt_tokens
+        del resp.usage.completion_tokens
+        del resp.usage.prompt_tokens_details
+
+        output: list[Any] = []
+        if text:
+            msg = MagicMock()
+            msg.type = "message"
+            text_part = MagicMock()
+            text_part.type = "output_text"
+            text_part.text = text
+            text_part.annotations = []
+            msg.content = [text_part]
+            msg.model_dump.return_value = {
+                "type": "message",
+                "content": [{"type": "output_text", "text": text}],
+            }
+            output.append(msg)
+        if tool_calls:
+            for tc in tool_calls:
+                item = MagicMock()
+                item.type = "function_call"
+                item.call_id = tc["id"]
+                item.name = tc["name"]
+                item.arguments = tc["arguments"]
+                item.model_dump.return_value = {
+                    "type": "function_call",
+                    "call_id": tc["id"],
+                    "name": tc["name"],
+                    "arguments": tc["arguments"],
+                }
+                output.append(item)
+        resp.output = output
+        return resp
+
+    def test_basic_text_completion(self) -> None:
+        resp = self._make_response(text="Hello world")
+        result = self.provider._parse_response(resp)
+        assert result.content == "Hello world"
+        assert result.tool_calls is None
+        assert result.finish_reason == "stop"
+
+    def test_completion_with_tool_calls(self) -> None:
+        resp = self._make_response(
+            text="",
+            tool_calls=[{"id": "call_1", "name": "read_file", "arguments": '{"path": "/tmp"}'}],
+        )
+        result = self.provider._parse_response(resp)
+        assert result.tool_calls is not None
+        assert len(result.tool_calls) == 1
+        assert result.tool_calls[0]["id"] == "call_1"
+        assert result.tool_calls[0]["function"]["name"] == "read_file"
+
+    def test_provider_blocks_captured(self) -> None:
+        resp = self._make_response(text="Hello")
+        result = self.provider._parse_response(resp)
+        assert len(result.provider_blocks) > 0
+        assert result.provider_blocks[0]["type"] == "message"
+
+    def test_incomplete_status_maps_to_length(self) -> None:
+        resp = self._make_response(text="Partial", status="incomplete")
+        result = self.provider._parse_response(resp)
+        assert result.finish_reason == "length"
+
+    def test_usage_extraction(self) -> None:
+        resp = self._make_response(text="Hi")
+        result = self.provider._parse_response(resp)
+        assert result.usage is not None
+        assert result.usage.prompt_tokens == 10
+        assert result.usage.completion_tokens == 5

tests/test_rule_registry.py

@@ -0,0 +1,307 @@
+"""Tests for rule_registry — merge logic for heuristic rules and output guard patterns."""
+
+from __future__ import annotations
+
+from turnstone.core.rule_registry import (
+    RuleRegistry,
+)
+
+# ---------------------------------------------------------------------------
+# Mock storage helper
+# ---------------------------------------------------------------------------
+
+
+class _MockStorage:
+    """Minimal storage stub that returns configurable rule/pattern lists."""
+
+    def __init__(
+        self,
+        heuristic_rows: list[dict] | None = None,
+        output_pattern_rows: list[dict] | None = None,
+    ) -> None:
+        self._heuristic_rows = heuristic_rows or []
+        self._output_pattern_rows = output_pattern_rows or []
+
+    def list_heuristic_rules(self, enabled_only: bool = False) -> list[dict]:
+        return list(self._heuristic_rows)
+
+    def list_output_guard_patterns(self, enabled_only: bool = False) -> list[dict]:
+        return list(self._output_pattern_rows)
+
+
+class _BrokenStorage(_MockStorage):
+    """Storage stub that raises on every call."""
+
+    def list_heuristic_rules(self, enabled_only: bool = False) -> list[dict]:
+        raise RuntimeError("DB connection lost")
+
+    def list_output_guard_patterns(self, enabled_only: bool = False) -> list[dict]:
+        raise RuntimeError("DB connection lost")
+
+
+# ---------------------------------------------------------------------------
+# 1. RuleRegistry with no storage — only built-in rules
+# ---------------------------------------------------------------------------
+
+
+class TestBuiltinsOnly:
+    def test_builtin_heuristic_rules_loaded(self) -> None:
+        reg = RuleRegistry(storage=None)
+        assert len(reg.heuristic_rules) == 37
+
+    def test_builtin_output_patterns_loaded(self) -> None:
+        reg = RuleRegistry(storage=None)
+        total = sum(len(pats) for pats in reg.output_patterns.values())
+        assert total == 19
+        assert len(reg.output_patterns) == 5
+
+    def test_heuristic_rules_sorted_by_tier(self) -> None:
+        reg = RuleRegistry(storage=None)
+        tier_order = {"critical": 0, "high": 1, "medium": 2, "low": 3}
+        tiers = [tier_order[r.tier] for r in reg.heuristic_rules]
+        assert tiers == sorted(tiers)
+
+    def test_output_patterns_grouped_by_category(self) -> None:
+        reg = RuleRegistry(storage=None)
+        expected_categories = {
+            "prompt_injection",
+            "credentials",
+            "encoded_payloads",
+            "adversarial_urls",
+            "info_disclosure",
+        }
+        assert set(reg.output_patterns.keys()) == expected_categories
+
+
+# ---------------------------------------------------------------------------
+# 2. RuleRegistry with mock storage — merge logic
+# ---------------------------------------------------------------------------
+
+
+class TestHeuristicMerge:
+    def test_custom_rule_added(self) -> None:
+        storage = _MockStorage(
+            heuristic_rows=[
+                {
+                    "name": "my-custom-rule",
+                    "enabled": True,
+                    "builtin": False,
+                    "risk_level": "high",
+                    "confidence": 0.85,
+                    "recommendation": "review",
+                    "tool_pattern": "bash",
+                    "arg_patterns": '["rm -rf /tmp"]',
+                    "intent_template": "Custom: {arg_snippet}",
+                    "reasoning_template": "Custom reasoning.",
+                    "tier": "high",
+                    "priority": 0,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        names = [r.name for r in reg.heuristic_rules]
+        assert "my-custom-rule" in names
+        # Built-ins still present
+        assert len(reg.heuristic_rules) == 38
+
+    def test_builtin_overridden(self) -> None:
+        storage = _MockStorage(
+            heuristic_rows=[
+                {
+                    "name": "rm-root",  # same name as built-in
+                    "enabled": True,
+                    "builtin": True,
+                    "risk_level": "high",  # changed from critical
+                    "confidence": 0.50,
+                    "recommendation": "review",
+                    "tool_pattern": "bash",
+                    "arg_patterns": "[]",
+                    "intent_template": "Overridden: {arg_snippet}",
+                    "reasoning_template": "Overridden reasoning.",
+                    "tier": "high",
+                    "priority": 0,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        matched = [r for r in reg.heuristic_rules if r.name == "rm-root"]
+        assert len(matched) == 1
+        assert matched[0].risk_level == "high"
+        assert matched[0].confidence == 0.50
+        assert matched[0].intent_template == "Overridden: {arg_snippet}"
+
+    def test_builtin_disabled(self) -> None:
+        storage = _MockStorage(
+            heuristic_rows=[
+                {
+                    "name": "rm-root",
+                    "enabled": False,
+                    "builtin": True,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        names = [r.name for r in reg.heuristic_rules]
+        assert "rm-root" not in names
+        assert len(reg.heuristic_rules) == 36
+
+    def test_custom_rule_disabled_excluded(self) -> None:
+        storage = _MockStorage(
+            heuristic_rows=[
+                {
+                    "name": "my-disabled-rule",
+                    "enabled": False,
+                    "builtin": False,
+                    "risk_level": "medium",
+                    "confidence": 0.70,
+                    "recommendation": "review",
+                    "tool_pattern": "*",
+                    "arg_patterns": "[]",
+                    "intent_template": "",
+                    "reasoning_template": "",
+                    "tier": "medium",
+                    "priority": 0,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        names = [r.name for r in reg.heuristic_rules]
+        assert "my-disabled-rule" not in names
+        assert len(reg.heuristic_rules) == 37
+
+    def test_reload_updates_rules(self) -> None:
+        storage = _MockStorage()
+        reg = RuleRegistry(storage=storage)
+        assert len(reg.heuristic_rules) == 37
+
+        # Simulate admin adding a rule
+        storage._heuristic_rows.append(
+            {
+                "name": "late-addition",
+                "enabled": True,
+                "builtin": False,
+                "risk_level": "medium",
+                "confidence": 0.70,
+                "recommendation": "review",
+                "tool_pattern": "bash",
+                "arg_patterns": "[]",
+                "intent_template": "Late: {arg_snippet}",
+                "reasoning_template": "Added after init.",
+                "tier": "medium",
+                "priority": 0,
+            }
+        )
+        reg.reload()
+        assert len(reg.heuristic_rules) == 38
+        assert "late-addition" in [r.name for r in reg.heuristic_rules]
+
+    def test_version_increments_on_reload(self) -> None:
+        reg = RuleRegistry(storage=None)
+        v1 = reg.version
+        assert v1 == 1  # __init__ calls reload() once
+        reg.reload()
+        assert reg.version == 2
+        reg.reload()
+        assert reg.version == 3
+
+
+# ---------------------------------------------------------------------------
+# 3. OutputGuardPatternDef merge
+# ---------------------------------------------------------------------------
+
+
+class TestOutputPatternMerge:
+    def test_custom_output_pattern_added(self) -> None:
+        storage = _MockStorage(
+            output_pattern_rows=[
+                {
+                    "name": "custom-ssn",
+                    "enabled": True,
+                    "builtin": False,
+                    "category": "info_disclosure",
+                    "risk_level": "high",
+                    "pattern": r"\b\d{3}-\d{2}-\d{4}\b",
+                    "pattern_flags": "",
+                    "flag_name": "ssn_leak",
+                    "annotation": "Output contains what appears to be a Social Security number.",
+                    "is_credential": True,
+                    "redact_label": "ssn",
+                    "priority": 50,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        info_pats = reg.output_patterns.get("info_disclosure", ())
+        names = [p.name for p in info_pats]
+        assert "custom-ssn" in names
+
+        total = sum(len(pats) for pats in reg.output_patterns.values())
+        assert total == 20
+
+    def test_builtin_output_pattern_disabled(self) -> None:
+        storage = _MockStorage(
+            output_pattern_rows=[
+                {
+                    "name": "override_phrases",
+                    "enabled": False,
+                    "builtin": True,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        pi_pats = reg.output_patterns.get("prompt_injection", ())
+        names = [p.name for p in pi_pats]
+        assert "override_phrases" not in names
+
+        total = sum(len(pats) for pats in reg.output_patterns.values())
+        assert total == 18
+
+    def test_invalid_regex_skipped(self) -> None:
+        storage = _MockStorage(
+            output_pattern_rows=[
+                {
+                    "name": "bad-regex",
+                    "enabled": True,
+                    "builtin": False,
+                    "category": "credentials",
+                    "risk_level": "high",
+                    "pattern": "[invalid(",  # broken regex
+                    "pattern_flags": "",
+                    "flag_name": "bad",
+                    "annotation": "Should be skipped.",
+                    "is_credential": False,
+                    "redact_label": "",
+                    "priority": 0,
+                },
+            ]
+        )
+        reg = RuleRegistry(storage=storage)
+        all_names = [p.name for pats in reg.output_patterns.values() for p in pats]
+        assert "bad-regex" not in all_names
+        # Built-ins intact
+        total = sum(len(pats) for pats in reg.output_patterns.values())
+        assert total == 19
+
+
+# ---------------------------------------------------------------------------
+# 4. Edge cases
+# ---------------------------------------------------------------------------
+
+
+class TestEdgeCases:
+    def test_storage_error_falls_back_to_builtins(self) -> None:
+        storage = _BrokenStorage()
+        reg = RuleRegistry(storage=storage)
+        assert len(reg.heuristic_rules) == 37
+        total = sum(len(pats) for pats in reg.output_patterns.values())
+        assert total == 19
+
+    def test_empty_storage_equals_builtins(self) -> None:
+        no_storage = RuleRegistry(storage=None)
+        empty_storage = RuleRegistry(storage=_MockStorage())
+        assert len(no_storage.heuristic_rules) == len(empty_storage.heuristic_rules)
+        assert set(no_storage.output_patterns.keys()) == set(empty_storage.output_patterns.keys())
+        for cat in no_storage.output_patterns:
+            no_names = {p.name for p in no_storage.output_patterns[cat]}
+            empty_names = {p.name for p in empty_storage.output_patterns[cat]}
+            assert no_names == empty_names

tests/test_sdk_governance.py

@@ -64,6 +64,7 @@ class _InjectAuthMiddleware(BaseHTTPMiddleware):
                     "admin.roles",
                     "admin.orgs",
                     "admin.policies",
+                    "admin.prompt_policies",
                 }
             ),
         )

tests/test_server_live.py

@@ -138,6 +138,8 @@ def tmp_db():
 
 def _make_session(client, model_id, tmp_db, **kwargs) -> tuple[ChatSession, RecordingUI]:
     """Create a ChatSession with RecordingUI and sensible test defaults."""
+    from turnstone.core.providers._openai_chat import OpenAIChatCompletionsProvider
+
     ui = RecordingUI()
     defaults = dict(
         client=client,
@@ -151,6 +153,8 @@ def _make_session(client, model_id, tmp_db, **kwargs) -> tuple[ChatSession, Reco
     )
     defaults.update(kwargs)
     session = ChatSession(**defaults)
+    # Mock-based tests use Chat Completions format (client.chat.completions)
+    session._provider = OpenAIChatCompletionsProvider()
     session.auto_approve = True
     return session, ui
 
@@ -752,7 +756,6 @@ class TestServerHealthMetrics:
         data = json.loads(body)
         assert "backend" in data
         assert data["backend"]["status"] in ("up", "down")
-        assert data["backend"]["circuit_state"] in ("closed", "open", "half_open")
 
     def test_metrics_contains_sse_connections(self):
         _, _, body = self._get("/metrics")
@@ -766,9 +769,10 @@ class TestServerHealthMetrics:
         _, _, body = self._get("/metrics")
         assert "turnstone_backend_up" in body
 
-    def test_metrics_contains_circuit_state(self):
+    def test_metrics_no_circuit_state(self):
+        """Circuit state metric was removed (passive health tracking only)."""
         _, _, body = self._get("/metrics")
-        assert "turnstone_circuit_state" in body
+        assert "turnstone_circuit_state" not in body
 
     def test_metrics_contains_eviction_counter(self):
         _, _, body = self._get("/metrics")

tests/test_session.py

@@ -640,13 +640,11 @@ class TestExecReadImage:
         self._make_png(str(img))
 
         session = _make_session()
-        # Mock provider to report vision support
         mock_caps = MagicMock()
         mock_caps.supports_vision = True
-        session._provider.get_capabilities = MagicMock(return_value=mock_caps)
-
-        item = {"call_id": "c1", "path": str(img), "offset": None, "limit": None}
-        call_id, output = session._exec_read_file(item)
+        with patch.object(session._provider, "get_capabilities", return_value=mock_caps):
+            item = {"call_id": "c1", "path": str(img), "offset": None, "limit": None}
+            call_id, output = session._exec_read_file(item)
 
         assert call_id == "c1"
         assert isinstance(output, list)
@@ -669,10 +667,9 @@ class TestExecReadImage:
         session = _make_session()
         mock_caps = MagicMock()
         mock_caps.supports_vision = False
-        session._provider.get_capabilities = MagicMock(return_value=mock_caps)
-
-        item = {"call_id": "c2", "path": str(img), "offset": None, "limit": None}
-        call_id, output = session._exec_read_file(item)
+        with patch.object(session._provider, "get_capabilities", return_value=mock_caps):
+            item = {"call_id": "c2", "path": str(img), "offset": None, "limit": None}
+            call_id, output = session._exec_read_file(item)
 
         assert call_id == "c2"
         assert isinstance(output, str)
@@ -689,10 +686,9 @@ class TestExecReadImage:
         session = _make_session()
         mock_caps = MagicMock()
         mock_caps.supports_vision = True
-        session._provider.get_capabilities = MagicMock(return_value=mock_caps)
-
-        item = {"call_id": "c3", "path": str(img), "offset": None, "limit": None}
-        call_id, output = session._exec_read_file(item)
+        with patch.object(session._provider, "get_capabilities", return_value=mock_caps):
+            item = {"call_id": "c3", "path": str(img), "offset": None, "limit": None}
+            call_id, output = session._exec_read_file(item)
 
         assert call_id == "c3"
         assert isinstance(output, str)
@@ -703,10 +699,14 @@ class TestExecReadImage:
         session = _make_session()
         mock_caps = MagicMock()
         mock_caps.supports_vision = True
-        session._provider.get_capabilities = MagicMock(return_value=mock_caps)
-
-        item = {"call_id": "c4", "path": str(tmp_path / "nope.png"), "offset": None, "limit": None}
-        call_id, output = session._exec_read_file(item)
+        with patch.object(session._provider, "get_capabilities", return_value=mock_caps):
+            item = {
+                "call_id": "c4",
+                "path": str(tmp_path / "nope.png"),
+                "offset": None,
+                "limit": None,
+            }
+            call_id, output = session._exec_read_file(item)
         assert isinstance(output, str)
         assert "not found" in output
 
@@ -742,9 +742,10 @@ class TestGetCapabilitiesOverride:
             default="qwen-vl",
         )
         session = _make_session(registry=registry, model_alias="qwen-vl")
-        # Ensure provider returns a real ModelCapabilities (not MagicMock)
-        session._provider.get_capabilities = MagicMock(return_value=ModelCapabilities())
-        caps = session._get_capabilities()
+        # Ensure provider returns a real ModelCapabilities (not MagicMock).
+        # Use patch.object so the singleton provider is restored after the test.
+        with patch.object(session._provider, "get_capabilities", return_value=ModelCapabilities()):
+            caps = session._get_capabilities()
         assert caps.supports_vision is True
 
     def test_no_override_uses_provider_default(self, tmp_db):
@@ -759,6 +760,8 @@ class TestTitleRetry:
     """_generate_title resets _title_generated on failure."""
 
     def test_title_generated_reset_on_failure(self, tmp_db):
+        from turnstone.core.providers._protocol import ModelCapabilities
+
         session = _make_session()
         session._title_generated = True
         session.messages = [
@@ -767,6 +770,7 @@ class TestTitleRetry:
         ]
         # Mock provider to raise
         session._provider = MagicMock()
+        session._provider.get_capabilities.return_value = ModelCapabilities()
         session._provider.create_completion.side_effect = RuntimeError("API error")
 
         session._generate_title()
@@ -774,6 +778,8 @@ class TestTitleRetry:
         assert session._title_generated is False
 
     def test_title_generated_stays_true_on_success(self, tmp_db):
+        from turnstone.core.providers._protocol import ModelCapabilities
+
         session = _make_session()
         session._title_generated = True
         session.messages = [
@@ -783,6 +789,7 @@ class TestTitleRetry:
         result = MagicMock()
         result.content = "Test Title"
         session._provider = MagicMock()
+        session._provider.get_capabilities.return_value = ModelCapabilities()
         session._provider.create_completion.return_value = result
 
         with patch("turnstone.core.session.update_workstream_title"):
@@ -793,6 +800,8 @@ class TestTitleRetry:
 
     def test_title_skipped_after_resume_changes_ws_id(self, tmp_db):
         """If ws_id changes (via resume) during title generation, discard the result."""
+        from turnstone.core.providers._protocol import ModelCapabilities
+
         session = _make_session()
         session._title_generated = True
         session.messages = [
@@ -803,6 +812,7 @@ class TestTitleRetry:
         result = MagicMock()
         result.content = "Test Title"
         session._provider = MagicMock()
+        session._provider.get_capabilities.return_value = ModelCapabilities()
         session._provider.create_completion.return_value = result
 
         # Simulate resume() changing ws_id while title generation is in flight
@@ -912,8 +922,10 @@ class TestAgentOutputGuard:
     def test_agent_loop_calls_evaluate_output(self):
         """_run_agent passes tool output through _evaluate_output when output_guard is enabled."""
         from turnstone.core.judge import JudgeConfig
+        from turnstone.core.providers._openai_chat import OpenAIChatCompletionsProvider
 
         session = _make_session(judge_config=JudgeConfig(output_guard=True))
+        session._provider = OpenAIChatCompletionsProvider()
 
         with patch.object(session, "_evaluate_output", wraps=lambda cid, o, fn: o) as mock_eval:
             # Simulate _run_agent getting a tool call response then a text response
@@ -971,8 +983,10 @@ class TestAgentOutputGuard:
     def test_agent_loop_skips_guard_when_disabled(self):
         """_run_agent does not call _evaluate_output when output_guard is disabled."""
         from turnstone.core.judge import JudgeConfig
+        from turnstone.core.providers._openai_chat import OpenAIChatCompletionsProvider
 
         session = _make_session(judge_config=JudgeConfig(output_guard=False))
+        session._provider = OpenAIChatCompletionsProvider()
 
         with patch.object(session, "_evaluate_output") as mock_eval:
             call_count = [0]
@@ -1018,3 +1032,47 @@ class TestAgentOutputGuard:
                 )
 
             mock_eval.assert_not_called()
+
+
+class TestProviderExtraParams:
+    """Tests for _provider_extra_params — local-only chat_template_kwargs."""
+
+    def _session_with_provider(self, provider_name: str, tmp_db) -> ChatSession:
+        from turnstone.core.providers import create_provider
+
+        session = _make_session(reasoning_effort="medium")
+        session._provider = create_provider(provider_name)
+        return session
+
+    def test_openai_compatible_returns_chat_template_kwargs(self, tmp_db):
+        session = self._session_with_provider("openai-compatible", tmp_db)
+        result = session._provider_extra_params()
+        assert result is not None
+        assert "chat_template_kwargs" in result
+        assert result["chat_template_kwargs"]["reasoning_effort"] == "medium"
+
+    def test_openai_commercial_returns_none(self, tmp_db):
+        session = self._session_with_provider("openai", tmp_db)
+        result = session._provider_extra_params()
+        assert result is None
+
+    def test_anthropic_returns_none(self, tmp_db):
+        session = self._session_with_provider("anthropic", tmp_db)
+        result = session._provider_extra_params()
+        assert result is None
+
+    def test_reasoning_effort_override(self, tmp_db):
+        session = self._session_with_provider("openai-compatible", tmp_db)
+        result = session._provider_extra_params(reasoning_effort="high")
+        assert result is not None
+        assert result["chat_template_kwargs"]["reasoning_effort"] == "high"
+
+    def test_explicit_openai_provider_overrides_session(self, tmp_db):
+        """Passing an explicit commercial OpenAI provider returns None even
+        when the session's own provider is openai-compatible."""
+        from turnstone.core.providers import create_provider
+
+        session = self._session_with_provider("openai-compatible", tmp_db)
+        openai_prov = create_provider("openai")
+        result = session._provider_extra_params(provider=openai_prov)
+        assert result is None

tests/test_sessions.py

@@ -335,8 +335,6 @@ class TestSaveMessageUpdatesWorkstream:
     def test_updated_timestamp_bumped(self, tmp_db):
         register_workstream("s1")
         save_message("s1", "user", "first")
-        rows = list_workstreams_with_history()
-        _original_updated = rows[0][4]
 
         import time
 

tests/test_storage_registry.py

@@ -1,8 +1,17 @@
 """Tests for the storage backend registry."""
 
-import pytest
+from unittest.mock import patch
 
-from turnstone.core.storage import get_storage, init_storage, reset_storage
+import pytest
+import sqlalchemy as sa
+
+from turnstone.core.storage import (
+    StorageUnavailableError,
+    get_storage,
+    init_storage,
+    reset_storage,
+)
+from turnstone.core.storage._postgresql import PostgreSQLBackend
 from turnstone.core.storage._sqlite import SQLiteBackend
 
 
@@ -48,7 +57,72 @@ class TestResetStorage:
         s1 = get_storage()
         reset_storage()
         # After reset, get_storage() auto-inits a new instance
-        monkeypatch_not_needed = True  # noqa: F841
         init_storage("sqlite", path=str(tmp_path / "test2.db"), run_migrations=False)
         s2 = get_storage()
         assert s1 is not s2
+
+
+class TestConnUnavailableLogging:
+    """Test that _conn() deduplicates DB unavailable/restored logging."""
+
+    def _make_backend(self, tmp_path):
+        """Create a minimal SQLite backend for testing _conn()."""
+        from turnstone.core.storage._sqlite import SQLiteBackend
+
+        return SQLiteBackend(str(tmp_path / "test.db"), create_tables=True)
+
+    def test_logs_unavailable_once(self, tmp_path, caplog: pytest.LogCaptureFixture) -> None:
+        backend = self._make_backend(tmp_path)
+        with patch.object(backend, "_engine") as mock_engine:
+            mock_engine.connect.side_effect = sa.exc.OperationalError(
+                "conn", {}, Exception("refused")
+            )
+            for _ in range(3):
+                with pytest.raises(StorageUnavailableError), backend._conn():
+                    pass  # pragma: no cover
+        unavailable_msgs = [r for r in caplog.records if "database.unavailable" in r.message]
+        assert len(unavailable_msgs) == 1
+
+    def test_logs_restored_on_recovery(self, tmp_path, caplog: pytest.LogCaptureFixture) -> None:
+        import logging
+
+        caplog.set_level(logging.INFO)
+        backend = self._make_backend(tmp_path)
+        # Simulate outage
+        with patch.object(backend, "_engine") as mock_engine:
+            mock_engine.connect.side_effect = sa.exc.OperationalError(
+                "conn", {}, Exception("refused")
+            )
+            with pytest.raises(StorageUnavailableError), backend._conn():
+                pass  # pragma: no cover
+        assert backend._db_unavailable is True
+        # Real connection — should log restored
+        caplog.clear()
+        with backend._conn():
+            pass
+        restored_msgs = [r for r in caplog.records if "database.connection_restored" in r.message]
+        assert len(restored_msgs) == 1
+        assert backend._db_unavailable is False
+
+    def test_postgresql_conn_raises_storage_unavailable(self) -> None:
+        import threading
+
+        backend = PostgreSQLBackend.__new__(PostgreSQLBackend)
+        backend._db_unavailable = False
+        backend._db_unavailable_lock = threading.Lock()
+
+        def _raise_op_error():
+            raise sa.exc.OperationalError("conn", {}, Exception("refused"))
+
+        mock_engine = type(
+            "E",
+            (),
+            {
+                "connect": staticmethod(_raise_op_error),
+                "url": sa.engine.make_url("postgresql://user:pass@localhost/db"),
+            },
+        )()
+        backend._engine = mock_engine
+        with pytest.raises(StorageUnavailableError), backend._conn():
+            pass  # pragma: no cover
+        assert backend._db_unavailable is True

tests/test_tool_truncation.py

@@ -0,0 +1,240 @@
+"""Tests for capacity-aware tool output truncation and context overflow recovery."""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from turnstone.core.session import ChatSession
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture
+def session(tmp_db, mock_openai_client):
+    """Create a ChatSession with defaults for truncation testing."""
+    return ChatSession(
+        client=mock_openai_client,
+        model="test-model",
+        ui=MagicMock(),
+        instructions=None,
+        temperature=0.5,
+        tool_timeout=10,
+        context_window=10_000,
+        max_tokens=1_000,
+    )
+
+
+# ---------------------------------------------------------------------------
+# _truncate_output
+# ---------------------------------------------------------------------------
+
+
+class TestTruncateOutput:
+    def test_no_truncation_when_under_limit(self, session):
+        result = session._truncate_output("short text")
+        assert result == "short text"
+
+    def test_truncates_to_tool_truncation_limit(self, session):
+        session.tool_truncation = 100
+        big = "x" * 500
+        result = session._truncate_output(big)
+        assert len(result) <= 200  # head + tail + marker
+        assert "chars truncated" in result
+
+    def test_budget_aware_truncation(self, session):
+        session.tool_truncation = 100_000
+        session._chars_per_token = 4.0
+        # Budget of 50 tokens = 200 chars
+        big = "x" * 1000
+        result = session._truncate_output(big, remaining_budget_tokens=50)
+        assert len(result) <= 400  # head + tail + marker
+        assert "chars truncated" in result
+
+    def test_budget_takes_precedence_when_smaller(self, session):
+        session.tool_truncation = 10_000
+        session._chars_per_token = 4.0
+        # Budget of 25 tokens = 100 chars, smaller than tool_truncation
+        big = "x" * 500
+        result = session._truncate_output(big, remaining_budget_tokens=25)
+        assert "chars truncated" in result
+
+    def test_zero_budget_returns_placeholder(self, session):
+        big = "x" * 1000
+        result = session._truncate_output(big, remaining_budget_tokens=0)
+        assert "exceeded context budget" in result
+        assert len(result) < 100
+
+    def test_negative_budget_returns_placeholder(self, session):
+        big = "x" * 1000
+        result = session._truncate_output(big, remaining_budget_tokens=-10)
+        assert "exceeded context budget" in result
+
+    def test_none_budget_uses_fixed_limit(self, session):
+        session.tool_truncation = 100
+        big = "x" * 500
+        result = session._truncate_output(big, remaining_budget_tokens=None)
+        assert "100 char limit" in result
+
+
+# ---------------------------------------------------------------------------
+# _remaining_token_budget
+# ---------------------------------------------------------------------------
+
+
+class TestRemainingTokenBudget:
+    def test_empty_session(self, session):
+        session._system_tokens = 500
+        session._msg_tokens = []
+        budget = session._remaining_token_budget()
+        # 10000 - 500 - 0 - 1000 - 500 (5%) = 8000
+        assert budget == 8000
+
+    def test_partially_full(self, session):
+        session._system_tokens = 500
+        session._msg_tokens = [2000, 3000]
+        budget = session._remaining_token_budget()
+        # 10000 - 500 - 5000 - 1000 - 500 = 3000
+        assert budget == 3000
+
+    def test_overfull_returns_zero(self, session):
+        session._system_tokens = 500
+        session._msg_tokens = [9000]
+        assert session._remaining_token_budget() == 0
+
+    def test_exactly_full_returns_zero(self, session):
+        session._system_tokens = 500
+        session._msg_tokens = [8000]
+        assert session._remaining_token_budget() == 0
+
+    def test_max_tokens_equals_context_window(self, tmp_db, mock_openai_client):
+        """Regression: max_tokens >= context_window must not zero the budget."""
+        s = ChatSession(
+            client=mock_openai_client,
+            model="test-model",
+            ui=MagicMock(),
+            instructions=None,
+            temperature=0.5,
+            tool_timeout=10,
+            context_window=32_768,
+            max_tokens=32_768,
+        )
+        s._system_tokens = 500
+        s._msg_tokens = [1000]
+        budget = s._remaining_token_budget()
+        # response_reserve = min(32768, 32768//4) = 8192
+        # safety = 32768 * 0.05 = 1638
+        # budget = 32768 - 500 - 1000 - 8192 - 1638 = 21438
+        assert budget > 20_000
+        # Tool output should NOT be collapsed to a placeholder
+        big = "x" * 5000
+        result = s._truncate_output(big, remaining_budget_tokens=budget)
+        assert result == big  # 5000 chars fits easily in 21K+ token budget
+
+
+# ---------------------------------------------------------------------------
+# Context overflow recovery
+# ---------------------------------------------------------------------------
+
+
+class TestContextOverflowRecovery:
+    """Test that context-length errors trigger compact-and-retry."""
+
+    def test_openai_context_length_error_triggers_compact(self, session):
+        session.messages = [{"role": "user", "content": "hi"}]
+        session._msg_tokens = [1]
+
+        call_count = 0
+
+        def mock_create_stream(msgs):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                raise Exception("maximum context length exceeded")
+            return iter([])
+
+        compact_mock = MagicMock()
+        with (
+            patch.object(session, "_create_stream_with_retry", side_effect=mock_create_stream),
+            patch.object(session, "_compact_messages", compact_mock),
+            patch.object(
+                session, "_stream_response", return_value={"role": "assistant", "content": "ok"}
+            ),
+            patch.object(session, "_full_messages", return_value=[]),
+            patch.object(session, "_update_token_table"),
+            patch.object(session, "_print_status_line"),
+            patch.object(session, "_emit_state"),
+            patch("turnstone.core.session.save_message"),
+        ):
+            session.send("hello")
+
+        compact_mock.assert_called_once_with(auto=True)
+        assert call_count == 2
+
+    def test_anthropic_prompt_too_long_triggers_compact(self, session):
+        session.messages = [{"role": "user", "content": "hi"}]
+        session._msg_tokens = [1]
+
+        call_count = 0
+
+        def mock_create_stream(msgs):
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                raise Exception("prompt is too long: 250000 tokens > 200000 maximum")
+            return iter([])
+
+        compact_mock = MagicMock()
+        with (
+            patch.object(session, "_create_stream_with_retry", side_effect=mock_create_stream),
+            patch.object(session, "_compact_messages", compact_mock),
+            patch.object(
+                session, "_stream_response", return_value={"role": "assistant", "content": "ok"}
+            ),
+            patch.object(session, "_full_messages", return_value=[]),
+            patch.object(session, "_update_token_table"),
+            patch.object(session, "_print_status_line"),
+            patch.object(session, "_emit_state"),
+            patch("turnstone.core.session.save_message"),
+        ):
+            session.send("hello")
+
+        compact_mock.assert_called_once_with(auto=True)
+
+    def test_non_context_error_propagates(self, session):
+        session.messages = [{"role": "user", "content": "hi"}]
+        session._msg_tokens = [1]
+
+        with (
+            patch.object(
+                session,
+                "_create_stream_with_retry",
+                side_effect=Exception("authentication failed"),
+            ),
+            patch.object(session, "_full_messages", return_value=[]),
+            patch.object(session, "_emit_state"),
+            patch("turnstone.core.session.save_message"),
+            pytest.raises(Exception, match="authentication failed"),
+        ):
+            session.send("hello")
+
+    def test_compact_failure_raises_original_error(self, session):
+        session.messages = [{"role": "user", "content": "hi"}]
+        session._msg_tokens = [1]
+
+        with (
+            patch.object(
+                session,
+                "_create_stream_with_retry",
+                side_effect=Exception("maximum context length exceeded"),
+            ),
+            patch.object(session, "_compact_messages", side_effect=RuntimeError("compact failed")),
+            patch.object(session, "_full_messages", return_value=[]),
+            patch.object(session, "_emit_state"),
+            patch("turnstone.core.session.save_message"),
+            pytest.raises(Exception, match="maximum context length exceeded"),
+        ):
+            session.send("hello")

tests/test_workstream.py

@@ -130,54 +130,54 @@ class TestWorkstream:
 class TestManagerCreation:
     def test_create_first_sets_active(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert mgr.active_id == ws.id
         assert mgr.get_active() is ws
 
     def test_create_second_does_not_change_active(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        _ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        mgr.create(ui_factory=FakeUI)
         assert mgr.active_id == ws1.id
 
     def test_create_assigns_session(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert isinstance(ws.session, FakeSession)
 
     def test_create_assigns_ui(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert isinstance(ws.ui, FakeUI)
         assert ws.ui.ws_id == ws.id
 
     def test_create_custom_name(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(name="research", ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(name="research", ui_factory=FakeUI)
         assert ws.name == "research"
 
     def test_create_default_name(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert ws.name.startswith("ws-")
 
     def test_create_max_workstreams_all_active(self):
         mgr = WorkstreamManager(_fake_factory, max_workstreams=3)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws3 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
+        ws3 = mgr.create(ui_factory=FakeUI)
         # Mark all as non-idle so eviction cannot help
         mgr.set_state(ws1.id, WorkstreamState.THINKING)
         mgr.set_state(ws2.id, WorkstreamState.RUNNING)
         mgr.set_state(ws3.id, WorkstreamState.ATTENTION)
         with pytest.raises(RuntimeError, match="All 3 workstreams are active"):
-            mgr.create(ui_factory=lambda wid: FakeUI(wid))
+            mgr.create(ui_factory=FakeUI)
 
 
 class TestManagerLookup:
     def test_get_existing(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert mgr.get(ws.id) is ws
 
     def test_get_nonexistent(self):
@@ -186,16 +186,16 @@ class TestManagerLookup:
 
     def test_list_all_creation_order(self):
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(name="a", ui_factory=lambda wid: FakeUI(wid))
-        _ws2 = mgr.create(name="b", ui_factory=lambda wid: FakeUI(wid))
-        _ws3 = mgr.create(name="c", ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(name="a", ui_factory=FakeUI)
+        mgr.create(name="b", ui_factory=FakeUI)
+        mgr.create(name="c", ui_factory=FakeUI)
         result = mgr.list_all()
         assert [w.name for w in result] == ["a", "b", "c"]
 
     def test_index_of(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
         assert mgr.index_of(ws1.id) == 1
         assert mgr.index_of(ws2.id) == 2
         assert mgr.index_of("nonexistent") == 0
@@ -203,9 +203,9 @@ class TestManagerLookup:
     def test_count(self):
         mgr = WorkstreamManager(_fake_factory)
         assert mgr.count == 0
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.count == 1
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.count == 2
 
 
@@ -217,8 +217,8 @@ class TestManagerLookup:
 class TestManagerSwitching:
     def test_switch_by_id(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
         assert mgr.active_id == ws1.id
 
         result = mgr.switch(ws2.id)
@@ -227,13 +227,13 @@ class TestManagerSwitching:
 
     def test_switch_nonexistent_returns_none(self):
         mgr = WorkstreamManager(_fake_factory)
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.switch("bad-id") is None
 
     def test_switch_by_index(self):
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
 
         result = mgr.switch_by_index(2)
         assert result is ws2
@@ -241,7 +241,7 @@ class TestManagerSwitching:
 
     def test_switch_by_index_out_of_range(self):
         mgr = WorkstreamManager(_fake_factory)
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.switch_by_index(0) is None
         assert mgr.switch_by_index(5) is None
 
@@ -254,29 +254,32 @@ class TestManagerSwitching:
 class TestManagerClose:
     def test_close_removes_workstream(self):
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
 
-        assert mgr.close(ws2.id) is True
+        closed = mgr.close(ws2.id)
+        assert closed is True
         assert mgr.count == 1
         assert mgr.get(ws2.id) is None
 
     def test_close_last_returns_false(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        assert mgr.close(ws.id) is False
+        ws = mgr.create(ui_factory=FakeUI)
+        closed = mgr.close(ws.id)
+        assert closed is False
         assert mgr.count == 1
 
     def test_close_nonexistent_returns_false(self):
         mgr = WorkstreamManager(_fake_factory)
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        assert mgr.close("nonexistent") is False
+        mgr.create(ui_factory=FakeUI)
+        mgr.create(ui_factory=FakeUI)
+        closed = mgr.close("nonexistent")
+        assert closed is False
 
     def test_close_active_switches_to_first(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
         mgr.switch(ws2.id)
 
         mgr.close(ws2.id)
@@ -284,9 +287,9 @@ class TestManagerClose:
 
     def test_close_updates_order(self):
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(name="a", ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(name="b", ui_factory=lambda wid: FakeUI(wid))
-        _ws3 = mgr.create(name="c", ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(name="a", ui_factory=FakeUI)
+        ws2 = mgr.create(name="b", ui_factory=FakeUI)
+        mgr.create(name="c", ui_factory=FakeUI)
 
         mgr.close(ws2.id)
         names = [w.name for w in mgr.list_all()]
@@ -295,7 +298,7 @@ class TestManagerClose:
     def test_close_unblocks_approval_event(self):
         """Closing a workstream whose UI has a pending approval should unblock it."""
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
 
         # Create a workstream with a WebUI-like approval mechanism
         from turnstone.server import WebUI
@@ -310,7 +313,7 @@ class TestManagerClose:
     def test_close_unblocks_plan_event(self):
         """Closing a workstream with pending plan review should unblock it."""
         mgr = WorkstreamManager(_fake_factory)
-        _ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
 
         from turnstone.server import WebUI
 
@@ -331,13 +334,13 @@ class TestManagerEviction:
     def test_evict_oldest_idle_on_create(self):
         """At capacity with idle workstreams, create() succeeds by evicting the oldest idle."""
         mgr = WorkstreamManager(_fake_factory, max_workstreams=3)
-        ws1 = mgr.create(name="oldest", ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(name="middle", ui_factory=lambda wid: FakeUI(wid))
-        _ws3 = mgr.create(name="newest", ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(name="oldest", ui_factory=FakeUI)
+        ws2 = mgr.create(name="middle", ui_factory=FakeUI)
+        mgr.create(name="newest", ui_factory=FakeUI)
         # All three are IDLE.  Mark ws2 as RUNNING so it won't be evicted.
         mgr.set_state(ws2.id, WorkstreamState.RUNNING)
         # ws1 is oldest idle, ws3 is newer idle.  Creating should evict ws1.
-        ws4 = mgr.create(name="four", ui_factory=lambda wid: FakeUI(wid))
+        ws4 = mgr.create(name="four", ui_factory=FakeUI)
         assert mgr.count == 3
         assert mgr.get(ws1.id) is None, "oldest idle should have been evicted"
         assert mgr.get(ws4.id) is ws4
@@ -349,35 +352,35 @@ class TestManagerEviction:
     def test_create_fails_when_all_active(self):
         """At capacity with ALL non-idle workstreams, create() raises RuntimeError."""
         mgr = WorkstreamManager(_fake_factory, max_workstreams=2)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
         mgr.set_state(ws1.id, WorkstreamState.THINKING)
         mgr.set_state(ws2.id, WorkstreamState.RUNNING)
         with pytest.raises(RuntimeError, match="All 2 workstreams are active"):
-            mgr.create(ui_factory=lambda wid: FakeUI(wid))
+            mgr.create(ui_factory=FakeUI)
 
     def test_configurable_max(self):
         """Constructor accepts max_workstreams param and respects it."""
         mgr = WorkstreamManager(_fake_factory, max_workstreams=2)
-        ws1 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        ws2 = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws1 = mgr.create(ui_factory=FakeUI)
+        ws2 = mgr.create(ui_factory=FakeUI)
         mgr.set_state(ws1.id, WorkstreamState.RUNNING)
         mgr.set_state(ws2.id, WorkstreamState.RUNNING)
         with pytest.raises(RuntimeError):
-            mgr.create(ui_factory=lambda wid: FakeUI(wid))
+            mgr.create(ui_factory=FakeUI)
         assert mgr.count == 2
 
     def test_eviction_counter(self):
         """eviction_count increments on each auto-eviction."""
         mgr = WorkstreamManager(_fake_factory, max_workstreams=2)
         assert mgr.eviction_count == 0
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
+        mgr.create(ui_factory=FakeUI)
         # Both IDLE — create should evict the oldest
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.eviction_count == 1
         # Again — evict another idle one
-        mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        mgr.create(ui_factory=FakeUI)
         assert mgr.eviction_count == 2
         assert mgr.count == 2
 
@@ -390,7 +393,7 @@ class TestManagerEviction:
 class TestManagerState:
     def test_set_state(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
         assert ws.state == WorkstreamState.IDLE
 
         mgr.set_state(ws.id, WorkstreamState.THINKING)
@@ -398,7 +401,7 @@ class TestManagerState:
 
     def test_set_state_with_error(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
 
         mgr.set_state(ws.id, WorkstreamState.ERROR, error_msg="API timeout")
         assert ws.state == WorkstreamState.ERROR
@@ -410,7 +413,7 @@ class TestManagerState:
 
     def test_on_state_change_callback(self):
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
 
         changes = []
         mgr._on_state_change = lambda wid, state: changes.append((wid, state))
@@ -433,7 +436,7 @@ class TestManagerThreadSafety:
 
         def do_create():
             try:
-                ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+                ws = mgr.create(ui_factory=FakeUI)
                 # Mark as non-idle immediately so auto-eviction cannot reclaim it
                 mgr.set_state(ws.id, WorkstreamState.RUNNING)
                 created.append(ws.id)
@@ -456,7 +459,7 @@ class TestManagerThreadSafety:
         mgr = WorkstreamManager(_fake_factory)
         ids = []
         for _ in range(5):
-            ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+            ws = mgr.create(ui_factory=FakeUI)
             ids.append(ws.id)
 
         def do_switch(wid):
@@ -476,10 +479,10 @@ class TestManagerThreadSafety:
         """close() and list_all() running concurrently should not crash."""
         mgr = WorkstreamManager(_fake_factory)
         # Keep one alive to prevent closing the last
-        anchor = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        anchor = mgr.create(ui_factory=FakeUI)
         targets = []
         for _ in range(5):
-            ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+            ws = mgr.create(ui_factory=FakeUI)
             targets.append(ws.id)
 
         def do_close():
@@ -878,7 +881,7 @@ class TestStateTransitions:
     def test_full_lifecycle(self):
         """Verify the expected state transition sequence."""
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
 
         # Simulate the state transitions that ChatSession.send() would emit
         mgr.set_state(ws.id, WorkstreamState.THINKING)
@@ -899,7 +902,7 @@ class TestStateTransitions:
     def test_error_recovery(self):
         """After an error, sending again should transition back to thinking."""
         mgr = WorkstreamManager(_fake_factory)
-        ws = mgr.create(ui_factory=lambda wid: FakeUI(wid))
+        ws = mgr.create(ui_factory=FakeUI)
 
         mgr.set_state(ws.id, WorkstreamState.ERROR, "API failed")
         assert ws.state == WorkstreamState.ERROR

turnstone/__init__.py

@@ -1,3 +1,3 @@
 """turnstone - Multi-node AI orchestration platform with tool use, agent routing, and cluster simulation."""
 
-__version__ = "1.0.0"
+__version__ = "1.2.0a2"

turnstone/api/server_schemas.py

@@ -145,7 +145,6 @@ class ListSavedWorkstreamsResponse(BaseModel):
 
 class BackendStatus(BaseModel):
     status: str = Field(examples=["up", "down"])
-    circuit_state: str = Field(examples=["closed", "open", "half_open"])
 
 
 class WorkstreamCounts(BaseModel):

turnstone/bootstrap.py

@@ -2,14 +2,15 @@
 
 Entry point: turnstone-bootstrap
 
-Walks users through configuring a single-node or multi-node Turnstone
-deployment via a conversational AI assistant. Generates .env files,
-docker-compose overrides, and post-start setup scripts.
+Walks users through configuring a Turnstone deployment via a conversational
+AI assistant. Generates compose.yaml, .env files, and post-start setup
+scripts.
 """
 
 from __future__ import annotations
 
 import getpass
+import importlib.resources
 import json
 import os
 import secrets
@@ -60,8 +61,6 @@ Turnstone is a multi-node AI orchestration platform. A deployment consists of:
 ## Deployment Profiles (compose.yaml)
 - **Default** (no flag): console only (infrastructure, good for running external servers)
 - **Production** (`--profile production`): 1 server + console + PostgreSQL + channel (single node)
-- **Cluster** (`--profile cluster`): 10-node server fleet + PostgreSQL + channel + console (multi-node)
-- **ddgCluster** (`--profile ddgCluster`): Cluster + DuckDuckGo Search MCP sidecar (web search via MCP, no API key needed)
 
 ## Environment Variables (.env)
 The compose.yaml reads these from a `.env` file:
@@ -78,9 +77,9 @@ For commercial providers (OpenAI, Anthropic-via-proxy), use the real key.
 
 ### Database
 - `DB_BACKEND` — `sqlite` (default) or `postgresql`
-- `DATABASE_URL` — PostgreSQL connection string (production/cluster only)
+- `DATABASE_URL` — PostgreSQL connection string (production only)
 - `POSTGRES_USER` — PostgreSQL username (default: turnstone)
-- `POSTGRES_PASSWORD` — PostgreSQL password (required for production/cluster)
+- `POSTGRES_PASSWORD` — PostgreSQL password (required for production)
 
 ### Authentication (always enabled)
 - `TURNSTONE_JWT_SECRET` — JWT signing secret (required). All services must share the same secret. \
@@ -104,16 +103,15 @@ Generate with: `python -c "import secrets; print(secrets.token_hex(32))"`
 - `TURNSTONE_DISCORD_TOKEN` — Discord bot token
 - `TURNSTONE_DISCORD_GUILD` — Restrict to single guild ID
 
-### MCP Integration (optional)
-- `MCP_CONFIG` — Path to MCP server config inside the container \
-(e.g., `/etc/turnstone/mcp-ddg.json`). When set, servers connect to configured MCP servers on startup.
-- The `ddgCluster` profile runs a DuckDuckGo Search MCP sidecar (Python) that provides \
-`duckduckgo_web_search` and `duckduckgo_fetch_content` tools to every node. No API key required. \
-The sidecar uses MCP streamable-http transport with DNS rebinding protection disabled \
-(required for Docker internal networking) and binds to 0.0.0.0:3000 via FastMCP settings. \
-Safe search is disabled by default.
+### Docker Image
+- `TURNSTONE_IMAGE_TAG` — Docker image tag (default: `latest`). \
+Set this to pin the image version (e.g., `1.1.0`, `stable`, `experimental`).
 
-### Cluster
+### MCP Integration (optional)
+- `MCP_CONFIG` — Path to MCP server config inside the container. \
+When set, servers connect to configured MCP servers on startup.
+
+### Other
 - `APPROVAL_TIMEOUT` — Tool approval timeout in seconds (default: 3600)
 
 ## Auth Setup Flow
@@ -154,28 +152,28 @@ Categories like "engineering", "analysis", etc.
 ## Your Task
 Walk the user through setting up their deployment step by step:
 
-1. **First**: Call `check_docker` and `read_file` on `.env` to detect existing state.
-2. **Deployment mode**: Ask if they want single-node (`--profile production`) or multi-node \
-(`--profile cluster`). Explain trade-offs.
-3. **LLM provider for the deployment**: Which LLM backend their Turnstone will use \
+1. **First**: Call `check_docker`, `read_file` on `.env`, and `read_file` on `compose.yaml` \
+to detect existing state. If `compose.yaml` does not exist, call `write_compose` to \
+extract the bundled production compose file. This is essential — without it, \
+`docker compose` will fail.
+2. **LLM provider for the deployment**: Which LLM backend their Turnstone will use \
 (may differ from this wizard's model). Ask for base URL, API key, model name.
-4. **Database**: SQLite (dev/simple) vs PostgreSQL (production/cluster). \
-PostgreSQL is required for cluster mode.
-5. **Security**: Auth is always enabled and requires `TURNSTONE_JWT_SECRET`. \
+3. **Database**: SQLite (dev/simple) vs PostgreSQL (production). \
+PostgreSQL is recommended for production use.
+4. **Security**: Auth is always enabled and requires `TURNSTONE_JWT_SECRET`. \
 Use `generate_secret` for JWT secret and Postgres password. \
 Always set `TURNSTONE_JWT_SECRET` in the .env. \
 Ask for initial admin username and password. \
 If the user's deployment will use an external identity provider (Okta, Azure AD, Google, etc.), \
 offer to configure OIDC SSO. Ask for the issuer URL, client ID, and client secret. \
 Optionally configure role mapping and OIDC-only mode.
-6. **Ports**: Check defaults with `check_port`, suggest alternatives if conflicts.
-7. **Optional features**: Discord integration, web search (Tavily key), \
-DuckDuckGo Search MCP (for cluster — uses `ddgCluster` profile with \
-`MCP_CONFIG=/etc/turnstone/mcp-ddg.json`, no API key needed).
-8. **Generate .env**: Call `write_file` with the complete `.env` content.
-9. **Generate setup.sh**: Call `write_file` with a post-start script that creates the admin \
+5. **Ports**: Check defaults with `check_port`, suggest alternatives if conflicts.
+6. **Optional features**: Discord integration, web search (Tavily key).
+7. **Generate .env**: Call `write_file` with the complete `.env` content. \
+Include `TURNSTONE_IMAGE_TAG` set to the version matching the installed package.
+8. **Generate setup.sh**: Call `write_file` with a post-start script that creates the admin \
 user and any roles/policies/skills the user wants.
-10. **Finish**: Call the `finish` tool with a summary of what was configured and the \
+9. **Finish**: Call the `finish` tool with a summary of what was configured and the \
 exact commands to run next (e.g., `docker compose --profile production up -d` then `./setup.sh`).
 
 ## Rules
@@ -183,14 +181,9 @@ exact commands to run next (e.g., `docker compose --profile production up -d` th
 - NEVER echo API keys or passwords back to the user in your text responses.
 - ALWAYS use `generate_secret` for passwords and secrets — never invent them.
 - When writing files, use `write_file` — the user will see a preview and confirm.
+- If `compose.yaml` is missing, call `write_compose` before anything else. \
+The compose file uses pre-built images from ghcr.io — no local Docker build is needed.
 - If an existing .env is detected, summarize what's configured and ask what to change.
-- For cluster mode, the compose.yaml has a fixed 10-node fleet — no override needed.
-- For cluster + DuckDuckGo Search, use `--profile ddgCluster` instead of `--profile cluster`. \
-Set `MCP_CONFIG=/etc/turnstone/mcp-ddg.json` in `.env`. No API key needed. \
-The DuckDuckGo MCP sidecar starts automatically and all cluster nodes connect to it. \
-Note: the MCP SDK's DNS rebinding protection must be disabled for Docker-internal networking \
-(the compose.yaml handles this), and the server must bind to 0.0.0.0 (not 127.0.0.1) to be \
-reachable from other containers.
 - The `DATABASE_URL` for docker compose internal networking uses the hostname `postgres` \
 (e.g., `postgresql+psycopg://turnstone:<password>@postgres:5432/turnstone`).
 - For local LLM backends (vLLM, llama.cpp, Ollama, etc.), set `OPENAI_API_KEY=dummy` in the \
@@ -342,6 +335,23 @@ TOOLS: list[dict[str, Any]] = [
             },
         },
     },
+    {
+        "type": "function",
+        "function": {
+            "name": "write_compose",
+            "description": (
+                "Write the production Docker Compose file to the project directory. "
+                "This extracts the compose.yaml bundled with Turnstone, which uses "
+                "pre-built images from ghcr.io (no local Docker build required). "
+                "The user will be shown a preview and asked to confirm."
+            ),
+            "parameters": {
+                "type": "object",
+                "properties": {},
+                "required": [],
+            },
+        },
+    },
     {
         "type": "function",
         "function": {
@@ -427,7 +437,7 @@ def _tool_write_file(project_dir: Path, args: dict[str, Any]) -> str:
             if existing == content:
                 return f"File already exists with identical content: {args['path']}"
         except (OSError, UnicodeDecodeError):
-            pass
+            pass  # best-effort duplicate check
 
     line_count = content.count("\n") + (1 if content and not content.endswith("\n") else 0)
 
@@ -561,6 +571,54 @@ def _tool_check_docker(args: dict[str, Any]) -> str:
     return "\n".join(results)
 
 
+def _tool_write_compose(project_dir: Path, args: dict[str, Any]) -> str:
+    """Extract the bundled production compose.yaml to the project directory."""
+    dest = project_dir / "compose.yaml"
+
+    # Read the bundled template
+    try:
+        ref = importlib.resources.files("turnstone.deploy").joinpath("compose.yaml")
+        content = ref.read_text(encoding="utf-8")
+    except Exception as exc:
+        return f"Error: could not read bundled compose template: {exc}"
+
+    # Skip if identical
+    if dest.exists():
+        try:
+            existing = dest.read_text(encoding="utf-8")
+            if existing == content:
+                return "compose.yaml already exists with identical content."
+        except (OSError, UnicodeDecodeError):
+            pass  # best-effort duplicate check
+
+    line_count = content.count("\n") + (1 if content and not content.endswith("\n") else 0)
+
+    # Show preview
+    print(f"\n{YELLOW} Writing compose.yaml ({line_count} lines){RESET}")
+    print(f"{DIM}{'─' * 50}{RESET}")
+    for line in content.split("\n")[:30]:
+        print(f"  {DIM}{line}{RESET}")
+    if line_count > 30:
+        print(f"  {DIM}... ({line_count - 30} more lines){RESET}")
+    print(f"{DIM}{'─' * 50}{RESET}")
+
+    try:
+        choice = input(f"{BOLD}Write this file? [Y/n]{RESET} ").strip().lower()
+    except (EOFError, KeyboardInterrupt):
+        return "User cancelled the write."
+    if choice in ("n", "no"):
+        return "User declined to write compose.yaml."
+
+    dest.write_text(content, encoding="utf-8")
+
+    return (
+        f"compose.yaml written successfully. "
+        f"It uses ghcr.io/turnstonelabs/turnstone images. "
+        f"Add TURNSTONE_IMAGE_TAG={__version__} to .env to pin the image "
+        f"to the currently installed version, or omit it to use 'latest'."
+    )
+
+
 class _FinishError(Exception):
     """Raised by the finish tool to signal the wizard is done."""
 
@@ -581,11 +639,12 @@ TOOL_FUNCTIONS: dict[str, Any] = {
     "check_port": _tool_check_port,
     "validate_api_key": _tool_validate_api_key,
     "check_docker": _tool_check_docker,
+    "write_compose": _tool_write_compose,
     "finish": _tool_finish,
 }
 
 # Tools that need the project_dir argument
-_PROJECT_DIR_TOOLS = frozenset({"read_file", "write_file"})
+_PROJECT_DIR_TOOLS = frozenset({"read_file", "write_file", "write_compose"})
 
 
 def execute_tool(name: str, args: dict[str, Any], project_dir: Path) -> str:

turnstone/channels/_formatter.py

@@ -1,12 +1,17 @@
 """Message formatting utilities for channel adapters.
 
 Handles chunking long messages for platforms with character limits, formatting
-tool-approval requests, and plan-review prompts.
+tool-approval requests, plan-review prompts, and rich media embeds for
+platforms that support them (e.g. Discord).
 """
 
 from __future__ import annotations
 
-from typing import Any
+import json
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    import httpx
 
 
 def chunk_message(text: str, max_length: int = 2000) -> list[str]:
@@ -164,3 +169,298 @@ def truncate(text: str, max_length: int = 200) -> str:
     if len(text) <= max_length:
         return text
     return text[: max_length - 1] + "\u2026"
+
+
+# ---------------------------------------------------------------------------
+# Rich media embed helpers (Discord)
+# ---------------------------------------------------------------------------
+
+
+def try_parse_media(output: str) -> dict[str, Any] | None:
+    """Attempt to parse tool output as a media result.
+
+    Returns the parsed dict when the output looks like structured media
+    (single item, search results, or session list), otherwise ``None``.
+    """
+    try:
+        data = json.loads(output)
+    except (json.JSONDecodeError, TypeError):
+        return None
+    if not isinstance(data, dict):
+        return None
+    # Single item with stream URL or detailed metadata.
+    if "stream_url" in data or ("name" in data and "type" in data and "id" in data):
+        return data
+    # Search results.
+    if "results" in data and isinstance(data["results"], list) and data["results"]:
+        return data
+    # Active sessions.
+    if "sessions" in data and isinstance(data["sessions"], list):
+        return data
+    return None
+
+
+_BLOCKED_HOSTNAMES = frozenset({"localhost", "metadata.google.internal"})
+
+
+def _is_safe_image_url(url: str) -> bool:
+    """Validate that *url* uses http(s), has no embedded credentials, and does
+    not target loopback or cloud metadata endpoints.
+
+    Private/LAN IPs are intentionally allowed (media servers are typically
+    on the local network).
+    """
+    import ipaddress
+    from urllib.parse import urlparse
+
+    try:
+        parsed = urlparse(url)
+    except Exception:  # noqa: BLE001
+        return False
+    if parsed.scheme not in ("http", "https"):
+        return False
+    if parsed.username or parsed.password:
+        return False
+    hostname = parsed.hostname
+    if not hostname:
+        return False
+    if hostname in _BLOCKED_HOSTNAMES:
+        return False
+    try:
+        ip = ipaddress.ip_address(hostname)
+        if ip.is_loopback or ip.is_link_local:
+            return False
+    except ValueError:
+        pass  # Not an IP literal — hostname is fine
+    return True
+
+
+async def _fetch_thumbnail(
+    http: httpx.AsyncClient,
+    url: str,
+    *,
+    timeout: float = 5.0,
+    max_bytes: int = 2 * 1024 * 1024,
+) -> tuple[bytes, str] | None:
+    """Fetch a thumbnail image, returning ``(bytes, filename)`` or ``None``.
+
+    Never raises — a failed image fetch must not break tool result
+    rendering.  Private/LAN URLs are intentionally allowed (media servers
+    are typically on the local network), but scheme is restricted to
+    http(s) and userinfo is rejected.
+    """
+    if not _is_safe_image_url(url):
+        return None
+    try:
+        async with http.stream("GET", url, timeout=timeout) as resp:
+            if resp.status_code != 200:
+                return None
+            cl = resp.headers.get("content-length")
+            if cl and cl.isdigit() and int(cl) > max_bytes:
+                return None
+            content_type = resp.headers.get("content-type", "image/jpeg").lower()
+            if not content_type.startswith("image/"):
+                return None
+            ext = "jpg"
+            if "png" in content_type:
+                ext = "png"
+            elif "webp" in content_type:
+                ext = "webp"
+            data = bytearray()
+            async for chunk in resp.aiter_bytes():
+                data.extend(chunk)
+                if len(data) > max_bytes:
+                    return None
+            return bytes(data), f"poster.{ext}"
+    except Exception:  # noqa: BLE001
+        return None
+
+
+async def try_build_media_embed(
+    tool_name: str,
+    output: str,
+    *,
+    http: httpx.AsyncClient,
+) -> tuple[Any, Any | None] | None:
+    """Attempt to build a rich Discord embed from media tool output.
+
+    Returns ``(embed, optional_file)`` if the output is parseable as media,
+    or ``None`` to fall through to the default code-block formatter.
+
+    The ``discord`` library is imported lazily since this module is shared
+    across adapters and ``discord.py`` is an optional dependency.
+    """
+    data = try_parse_media(output)
+    if data is None:
+        return None
+
+    import io
+
+    import discord
+
+    # Dispatch on result shape.
+    if "results" in data and isinstance(data["results"], list):
+        embed = _build_search_results_embed(data)
+    elif "sessions" in data and isinstance(data["sessions"], list):
+        embed = _build_sessions_embed(data)
+    else:
+        embed = _build_single_media_embed(data, tool_name)
+
+    # Proxy thumbnail image.
+    thumbnail_url = data.get("thumbnail_url") or data.get("image_url")
+    if not thumbnail_url and data.get("results"):
+        first = data["results"][0]
+        thumbnail_url = first.get("thumbnail_url") or first.get("image_url")
+
+    file: discord.File | None = None
+    if thumbnail_url:
+        fetched = await _fetch_thumbnail(http, thumbnail_url)
+        if fetched:
+            image_bytes, filename = fetched
+            file = discord.File(io.BytesIO(image_bytes), filename=filename)
+            embed.set_thumbnail(url=f"attachment://{filename}")
+
+    return embed, file
+
+
+# -- Private embed builders ------------------------------------------------
+
+
+def _build_single_media_embed(data: dict[str, Any], tool_name: str) -> Any:
+    """Build a Discord embed for a single media item."""
+    import discord
+
+    title = data.get("name", "Unknown")
+    if data.get("year"):
+        title += f" ({data['year']})"
+
+    embed = discord.Embed(
+        title=title,
+        url=data.get("web_url"),  # safe link — NOT stream_url
+        description=truncate(data.get("overview", ""), 200),
+        color=discord.Color.teal(),
+    )
+
+    # Metadata fields (inline).
+    meta_parts: list[str] = []
+    if data.get("type"):
+        meta_parts.append(data["type"])
+    if data.get("official_rating"):
+        meta_parts.append(data["official_rating"])
+    if data.get("runtime_minutes"):
+        hours = int(data["runtime_minutes"] // 60)
+        mins = int(data["runtime_minutes"] % 60)
+        meta_parts.append(f"{hours}h {mins}m" if hours else f"{mins}m")
+    if meta_parts:
+        embed.add_field(name="Info", value=" \u00b7 ".join(meta_parts), inline=True)
+
+    if data.get("genres"):
+        embed.add_field(name="Genres", value=", ".join(data["genres"][:5]), inline=True)
+
+    if data.get("community_rating"):
+        embed.add_field(
+            name="Rating",
+            value=f"{data['community_rating']:.1f}/10",
+            inline=True,
+        )
+
+    # Extract server name from tool_name (mcp__servername__toolname).
+    parts = tool_name.split("__")
+    if len(parts) >= 3:
+        embed.set_footer(text=parts[1])
+
+    return embed
+
+
+def _build_search_results_embed(data: dict[str, Any]) -> Any:
+    """Build a Discord embed for a list of search results."""
+    import discord
+
+    results = data.get("results", [])
+    total = data.get("total_count", len(results))
+
+    lines: list[str] = []
+    char_count = 0
+    for i, r in enumerate(results[:10], 1):
+        line = f"**{i}.** {r.get('name', '?')}"
+        if r.get("year"):
+            line += f" ({r['year']})"
+        meta: list[str] = []
+        if r.get("type"):
+            meta.append(r["type"])
+        if r.get("series_name"):
+            meta.append(r["series_name"])
+            if r.get("season_number") is not None and r.get("episode_number") is not None:
+                meta.append(f"S{int(r['season_number']):02d}E{int(r['episode_number']):02d}")
+        if r.get("runtime_minutes"):
+            mins = r["runtime_minutes"]
+            meta.append(f"{int(mins // 60)}h {int(mins % 60)}m" if mins >= 60 else f"{int(mins)}m")
+        if meta:
+            line += "  \u00b7  " + " \u00b7 ".join(meta)
+        if char_count + len(line) + 1 > 4000:
+            break
+        lines.append(line)
+        char_count += len(line) + 1
+
+    embed = discord.Embed(
+        title="Search results",
+        description="\n".join(lines),
+        color=discord.Color.teal(),
+    )
+    embed.set_footer(text=f"showing {len(lines)} of {total}")
+    return embed
+
+
+def _build_sessions_embed(data: dict[str, Any]) -> Any:
+    """Build a Discord embed for active playback sessions."""
+    import discord
+
+    sessions = data.get("sessions", [])
+    if not sessions:
+        embed = discord.Embed(
+            title="Now Playing",
+            description="No active sessions.",
+            color=discord.Color.light_grey(),
+        )
+        return embed
+
+    lines: list[str] = []
+    has_active = False
+    for s in sessions:
+        np = s.get("now_playing")
+        device = s.get("device_name", "Unknown device")
+        user = s.get("user_name", "")
+        if np:
+            has_active = True
+            title = np.get("name", "Unknown")
+            if np.get("year"):
+                title += f" ({np['year']})"
+            ps = s.get("play_state", {}) or {}
+            pos = ps.get("position_seconds")
+            runtime_min = np.get("runtime_minutes")
+            time_str = ""
+            if pos is not None and runtime_min:
+                total_sec = int(runtime_min * 60)
+                pos_i = int(pos)
+                time_str = (
+                    f" {pos_i // 3600}:{pos_i % 3600 // 60:02d}:{pos_i % 60:02d}"
+                    f" / {total_sec // 3600}:{total_sec % 3600 // 60:02d}:{total_sec % 60:02d}"
+                )
+            paused = ps.get("is_paused", False)
+            icon = "\u23f8" if paused else "\u25b6"
+            line = f"**{title}** on {device}\n{icon}{time_str}"
+            if user:
+                line += f" \u00b7 {user}"
+            lines.append(line)
+        else:
+            line = f"*{device}* \u2014 idle"
+            if user:
+                line += f" ({user})"
+            lines.append(line)
+
+    embed = discord.Embed(
+        title="Now Playing",
+        description="\n\n".join(lines),
+        color=discord.Color.green() if has_active else discord.Color.light_grey(),
+    )
+    return embed

turnstone/channels/_routing.py

@@ -244,7 +244,7 @@ class ChannelRouter:
                     self._node_urls[ws_id] = node_url.rstrip("/")
                     return self._node_urls[ws_id]
             except Exception:
-                pass
+                log.debug("Console route lookup failed for ws %s", ws_id, exc_info=True)
         return self._server_url
 
     # -- user resolution -----------------------------------------------------

turnstone/channels/cli.py

@@ -282,10 +282,14 @@ def main() -> None:
 
             async def _heartbeat_loop() -> None:
                 """Periodically update service heartbeat."""
+                from turnstone.core.storage._registry import StorageUnavailableError
+
                 while True:
                     await asyncio.sleep(30)
                     try:
                         await asyncio.to_thread(storage.heartbeat_service, "channel", service_id)
+                    except StorageUnavailableError:
+                        pass  # already logged by storage layer
                     except Exception:
                         log.exception("channel.heartbeat_failed")
 

turnstone/channels/discord/bot.py

@@ -16,7 +16,7 @@ import contextlib
 import json
 import time
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 
 import httpx
 
@@ -558,15 +558,16 @@ class TurnstoneBot:
             # authorize this?" while the running embed says "this tool is
             # executing."  Both can coexist in the thread.
             for it in event.items:
-                name = it.get("func_name") or it.get("approval_label") or "tool"
+                raw_name = it.get("func_name") or it.get("approval_label") or "tool"
+                display_name = discord.utils.escape_markdown(raw_name)
                 raw_preview = it.get("preview", "")
-                # Sanitize preview: escape backticks to prevent markdown
-                # breakout and strip @-mentions.
+                # Escape backticks to prevent markdown breakout and
+                # strip @-mentions.
                 raw_preview = raw_preview.replace("`", "\\`")
                 raw_preview = discord.utils.escape_mentions(raw_preview)
                 preview = truncate(raw_preview, max_length=120) or None
                 embed = discord.Embed(
-                    title=name,
+                    title=display_name,
                     description=preview,
                     color=discord.Color.light_grey(),
                 )
@@ -581,8 +582,9 @@ class TurnstoneBot:
                 else:
                     msg = await thread.send(embed=embed)
                 call_id = it.get("call_id", "")
+                # Store raw (unescaped) name for matching against ToolResultEvent.name
                 self._tool_info_msgs.setdefault(ws_id, []).append(
-                    (call_id, name, preview or "", msg)
+                    (call_id, raw_name, preview or "", msg)
                 )
 
             # If no items consumed the thinking message (empty event), clean up.
@@ -614,7 +616,7 @@ class TurnstoneBot:
                 status = "Error" if event.is_error else "Done"
                 status_color = discord.Color.red() if event.is_error else discord.Color.dark_grey()
                 status_embed = discord.Embed(
-                    title=f"{event.name} \u2014 {status}",
+                    title=f"{discord.utils.escape_markdown(event.name)} \u2014 {status}",
                     description=matched_preview or None,
                     color=status_color,
                 )
@@ -624,14 +626,40 @@ class TurnstoneBot:
                     log.debug("discord.tool_info_status_edit_failed", ws_id=ws_id)
 
             # Send the result as a separate message.
-            desc = format_tool_result(event.output)
-            color = discord.Color.red() if event.is_error else discord.Color.dark_grey()
-            result_embed = discord.Embed(
-                title=event.name,
-                description=desc,
-                color=color,
-            )
-            await thread.send(embed=result_embed)
+            if not event.is_error:
+                from turnstone.channels._formatter import try_build_media_embed
+
+                media_result = None
+                try:
+                    media_result = await try_build_media_embed(
+                        event.name,
+                        event.output,
+                        http=self._http_client,
+                    )
+                except Exception:
+                    log.debug("discord.media_embed_failed", ws_id=ws_id, tool=event.name)
+                if media_result is not None:
+                    embed, file = media_result
+                    kwargs: dict[str, Any] = {"embed": embed}
+                    if file is not None:
+                        kwargs["file"] = file
+                    await thread.send(**kwargs)
+                else:
+                    desc = format_tool_result(event.output)
+                    result_embed = discord.Embed(
+                        title=event.name,
+                        description=desc,
+                        color=discord.Color.dark_grey(),
+                    )
+                    await thread.send(embed=result_embed)
+            else:
+                desc = format_tool_result(event.output)
+                result_embed = discord.Embed(
+                    title=event.name,
+                    description=desc,
+                    color=discord.Color.red(),
+                )
+                await thread.send(embed=result_embed)
 
         elif isinstance(event, ApproveRequestEvent):
             # Evaluate admin tool policies before auto-approve.

turnstone/cli.py

@@ -7,6 +7,7 @@ model auto-detection, workstream management, and the main() REPL entry point.
 from __future__ import annotations
 
 import argparse
+import logging
 import os
 import readline
 import sys
@@ -165,7 +166,7 @@ class TerminalUI(SessionUI):
                             it for it in items if it.get("needs_approval") and not it.get("error")
                         ]
             except Exception:
-                pass  # Best-effort — no policy enforcement on error
+                logging.getLogger(__name__).debug("Policy evaluation unavailable", exc_info=True)
 
         with self._print_lock:
             # Print all headers, previews, and heuristic verdicts
@@ -176,7 +177,8 @@ class TerminalUI(SessionUI):
                 else:
                     sys.stdout.write(f"  {yellow(item['header'])}\n")
                 if item.get("preview"):
-                    sys.stdout.write(item["preview"] + "\n")
+                    styled = dim(item["preview"]) if not item.get("error") else red(item["preview"])
+                    sys.stdout.write(styled + "\n")
                 verdict = item.get("_heuristic_verdict")
                 if verdict:
                     risk = verdict.get("risk_level", "medium")
@@ -1014,12 +1016,6 @@ def main() -> None:
         default="",
         help="Model for judge (default: same as session model)",
     )
-    judge_group.add_argument(
-        "--judge-provider",
-        dest="judge_provider",
-        default="",
-        help="Provider for judge (default: same as session provider)",
-    )
     judge_group.add_argument(
         "--judge-timeout",
         dest="judge_timeout",
@@ -1117,15 +1113,11 @@ def main() -> None:
     )
 
     # apply_config() merges [judge] config.toml values into args as
-    # judge_base_url, judge_api_key, etc.  Output_guard and redact_secrets
-    # default to True, enabling the heuristic guard even when the LLM judge
-    # is disabled via --no-judge.
+    # Output_guard and redact_secrets default to True, enabling the heuristic
+    # guard even when the LLM judge is disabled via --no-judge.
     judge_config = JudgeConfig(
         enabled=args.judge_enabled,
         model=args.judge_model,
-        provider=args.judge_provider,
-        base_url=getattr(args, "judge_base_url", ""),
-        api_key=getattr(args, "judge_api_key", ""),
         confidence_threshold=args.judge_confidence,
         timeout=args.judge_timeout,
     )

turnstone/console/collector.py

@@ -289,9 +289,13 @@ class ClusterCollector:
 
     def _discovery_loop(self) -> None:
         """Periodically scan the service registry for active nodes."""
+        from turnstone.core.storage._registry import StorageUnavailableError
+
         while self._running:
             try:
                 self._discover_nodes()
+            except StorageUnavailableError:
+                pass  # already logged by storage layer
             except Exception:
                 log.exception("Node discovery error")
             time.sleep(self._discovery_interval)
@@ -520,15 +524,14 @@ class ClusterCollector:
                 pending_events.append({"type": "ws_rename", "ws_id": ws_id, "name": name})
 
             elif etype == "health_changed":
-                # Update the health dict's circuit state in-place
-                circuit = data.get("circuit_state", "")
-                if circuit:
+                # Update the health dict's backend status in-place
+                bstatus = data.get("backend_status", "")
+                if bstatus:
                     if not node.health:
                         node.health = {}
                     backend = node.health.setdefault("backend", {})
-                    backend["circuit_state"] = circuit
-                    backend["status"] = "up" if circuit == "closed" else "down"
-                    node.health["status"] = "ok" if circuit == "closed" else "degraded"
+                    backend["status"] = "up" if bstatus == "healthy" else "down"
+                    node.health["status"] = "ok" if bstatus == "healthy" else "degraded"
                 # Not forwarded to cluster SSE — next snapshot refreshes UI
 
             elif etype == "aggregate":

turnstone/console/rebalancer.py

@@ -19,6 +19,7 @@ from typing import TYPE_CHECKING, Any
 import structlog
 
 from turnstone.core.hash_ring import RING_SIZE, RingNode, bucket_of
+from turnstone.core.storage._registry import StorageUnavailableError
 
 if TYPE_CHECKING:
     from turnstone.console.collector import ClusterCollector
@@ -149,6 +150,8 @@ class Rebalancer:
                 result = self.rebalance_once(trigger=trigger)
                 self._last_result = result
                 self._record_result_metrics(result)
+            except StorageUnavailableError:
+                pass  # already logged by storage layer
             except Exception:
                 log.exception("rebalancer.error")
             finally:

turnstone/console/scheduler.py

@@ -90,9 +90,13 @@ class TaskScheduler:
 
     def _loop(self) -> None:
         """Main scheduler loop — tick then sleep."""
+        from turnstone.core.storage._registry import StorageUnavailableError
+
         while not self._stop_event.is_set():
             try:
                 self._tick()
+            except StorageUnavailableError:
+                pass  # already logged by storage layer
             except Exception:
                 log.exception("scheduler.tick_error")
             self._stop_event.wait(self._check_interval)

turnstone/console/static/admin.js

@@ -60,6 +60,7 @@ function showAdmin() {
     roles: "admin.roles",
     policies: "admin.policies",
     "prompt-policies": "admin.prompt_policies",
+    judge: "admin.judge",
     skills: "admin.skills",
     usage: "admin.usage",
     audit: "admin.audit",
@@ -94,6 +95,29 @@ function showAdmin() {
 
   // Mobile: ensure sidebar starts hidden + inert; desktop: ensure it's accessible
   var sidebar = document.getElementById("admin-sidebar");
+
+  // Inject close header for mobile drawer (once)
+  if (!document.getElementById("admin-sidebar-close")) {
+    var closeHeader = document.createElement("div");
+    closeHeader.id = "admin-sidebar-close";
+    closeHeader.className = "admin-sidebar-close";
+    var label = document.createElement("span");
+    label.textContent = "Navigation";
+    var closeBtn = document.createElement("button");
+    closeBtn.setAttribute("aria-label", "Close navigation");
+    closeBtn.textContent = "\u00d7";
+    closeBtn.addEventListener("click", function () {
+      if (_mobileSidebarOpen) {
+        _toggleMobileSidebar();
+        var mt = document.getElementById("admin-mobile-toggle");
+        if (mt) mt.focus();
+      }
+    });
+    closeHeader.appendChild(label);
+    closeHeader.appendChild(closeBtn);
+    sidebar.insertBefore(closeHeader, sidebar.firstChild);
+  }
+
   if (window.innerWidth <= 700) {
     _mobileSidebarOpen = false;
     sidebar.classList.add("collapsed");
@@ -147,15 +171,20 @@ function _injectMobileToggle(tab) {
     toggle.id = "admin-mobile-toggle";
     toggle.className = "admin-mobile-toggle";
     toggle.setAttribute("aria-label", "Open navigation");
+    toggle.setAttribute("aria-expanded", "false");
     toggle.onclick = function () {
-      _mobileSidebarOpen = false;
       _toggleMobileSidebar();
     };
   }
   var panel = document.getElementById("admin-" + tab);
-  if (panel) {
-    var toolbar = panel.querySelector(".admin-toolbar");
-    if (toolbar) toolbar.insertBefore(toggle, toolbar.firstChild);
+  if (!panel) return;
+  var toolbar = panel.querySelector(".admin-toolbar");
+  if (toolbar) {
+    if (!toolbar.contains(toggle))
+      toolbar.insertBefore(toggle, toolbar.firstChild);
+  } else {
+    // Panel has no toolbar — prepend toggle directly so it remains accessible
+    if (!panel.contains(toggle)) panel.insertBefore(toggle, panel.firstChild);
   }
 }
 
@@ -169,6 +198,20 @@ function _toggleMobileSidebar() {
   else sidebar.setAttribute("inert", "");
   var backdrop = document.getElementById("admin-sidebar-backdrop");
   if (backdrop) backdrop.classList.toggle("visible", _mobileSidebarOpen);
+  // Update hamburger aria-label to reflect current state
+  var mt = document.getElementById("admin-mobile-toggle");
+  if (mt) {
+    mt.setAttribute(
+      "aria-label",
+      _mobileSidebarOpen ? "Close navigation" : "Open navigation",
+    );
+    mt.setAttribute("aria-expanded", _mobileSidebarOpen ? "true" : "false");
+  }
+  // Move focus into drawer on open; callers handle focus-return on close
+  if (_mobileSidebarOpen) {
+    var closeBtn = sidebar.querySelector(".admin-sidebar-close button");
+    if (closeBtn) closeBtn.focus();
+  }
 }
 
 function switchAdminTab(tab) {
@@ -200,6 +243,7 @@ function switchAdminTab(tab) {
     "tls",
     "mcp",
     "prompt-policies",
+    "judge",
   ];
   for (var p = 0; p < panels.length; p++) {
     var el = document.getElementById("admin-" + panels[p]);
@@ -225,6 +269,7 @@ function switchAdminTab(tab) {
   if (tab === "tls") loadTlsCerts();
   if (tab === "mcp") loadAdminMcp();
   if (tab === "prompt-policies") loadPromptPolicies();
+  if (tab === "judge") loadJudgeTab();
 
   // Update breadcrumb with active tab label
   var activeNav = document.querySelector('.admin-nav[data-tab="' + tab + '"]');
@@ -238,6 +283,15 @@ function switchAdminTab(tab) {
   // On mobile, auto-close sidebar after tab selection
   if (window.innerWidth <= 700 && _mobileSidebarOpen) {
     _toggleMobileSidebar();
+    // Move focus to the newly active panel instead of leaving it in the inert sidebar
+    var panel = document.getElementById("admin-" + tab);
+    var focusTarget =
+      panel &&
+      panel.querySelector("h2, .section-header, button:not([disabled])");
+    if (focusTarget) {
+      focusTarget.setAttribute("tabindex", "-1");
+      focusTarget.focus();
+    }
   }
 }
 
@@ -1855,6 +1909,8 @@ function _installTrap(overlayId, boxId, trapRef) {
           hideCreatePromptPolicyModal();
         else if (overlayId === "edit-ppolicy-overlay")
           hideEditPromptPolicyModal();
+        else if (overlayId === "create-hr-overlay") hideCreateHRModal();
+        else if (overlayId === "create-ogp-overlay") hideCreateOGPModal();
       }
     };
   }
@@ -1946,6 +2002,8 @@ document.addEventListener("keydown", function (e) {
     ["model-create-overlay", hideCreateModelModal],
     ["create-ppolicy-overlay", hideCreatePromptPolicyModal],
     ["edit-ppolicy-overlay", hideEditPromptPolicyModal],
+    ["create-hr-overlay", hideCreateHRModal],
+    ["create-ogp-overlay", hideCreateOGPModal],
   ];
   for (var gi = 0; gi < govOverlays.length; gi++) {
     var govEl = document.getElementById(govOverlays[gi][0]);
@@ -2002,18 +2060,20 @@ document.addEventListener("keydown", function (e) {
       if (!sidebar) return;
       var isMobile = window.innerWidth <= 700;
       var backdrop = document.getElementById("admin-sidebar-backdrop");
-      if (isMobile && !_mobileSidebarOpen) {
+      if (!isMobile) {
+        // Crossed into desktop: close drawer cleanly if it was open
+        if (_mobileSidebarOpen) _toggleMobileSidebar();
+        sidebar.removeAttribute("aria-hidden");
+        sidebar.removeAttribute("inert");
+        sidebar.classList.remove("collapsed", "open");
+        if (backdrop) backdrop.classList.remove("visible");
+      } else if (!_mobileSidebarOpen) {
+        // Mobile with drawer closed: ensure collapsed state
         sidebar.setAttribute("aria-hidden", "true");
         sidebar.setAttribute("inert", "");
         sidebar.classList.add("collapsed");
         sidebar.classList.remove("open");
         if (backdrop) backdrop.classList.remove("visible");
-      } else if (!isMobile) {
-        sidebar.removeAttribute("aria-hidden");
-        sidebar.removeAttribute("inert");
-        sidebar.classList.remove("collapsed", "open");
-        if (backdrop) backdrop.classList.remove("visible");
-        _mobileSidebarOpen = false;
       }
     }, 150);
   });
@@ -2302,6 +2362,7 @@ function loadSettings() {
       var merged = {};
       for (var j = 0; j < valuesArr.length; j++) {
         var v = valuesArr[j];
+        if (v.key.startsWith("judge.")) continue;
         var s = schemaMap[v.key] || {};
         merged[v.key] = {
           key: v.key,
@@ -4045,6 +4106,7 @@ function _pollInstallStatus(serverId, serverName, attempt) {
 // ---------------------------------------------------------------------------
 
 var _modelDefs = [];
+var _modelDefaultAlias = "";
 var _modelCreateTrap = null;
 var _modelCreateTrigger = null;
 
@@ -4056,6 +4118,7 @@ function loadAdminModels() {
     })
     .then(function (data) {
       _modelDefs = data.models || [];
+      _modelDefaultAlias = data.default_alias || "";
       _renderModels(_modelDefs);
     })
     .catch(function () {
@@ -4108,7 +4171,8 @@ function _renderModels(items) {
     row.className = "admin-row models-grid " + rowClass;
     row.setAttribute("role", "listitem");
 
-    // Alias + source badge
+    // Alias + source badge + default badge
+    var isDefault = m.alias === _modelDefaultAlias;
     var colAlias = document.createElement("span");
     colAlias.className = "admin-col";
     colAlias.textContent = m.alias;
@@ -4119,6 +4183,13 @@ function _renderModels(items) {
     badge.textContent = isConfig ? "config" : "db";
     colAlias.appendChild(document.createTextNode(" "));
     colAlias.appendChild(badge);
+    if (isDefault) {
+      var defBadge = document.createElement("span");
+      defBadge.className = "scope-badge scope-default";
+      defBadge.textContent = "default";
+      colAlias.appendChild(document.createTextNode(" "));
+      colAlias.appendChild(defBadge);
+    }
     row.appendChild(colAlias);
 
     // Model ID
@@ -4157,11 +4228,21 @@ function _renderModels(items) {
     // Actions
     var colActions = document.createElement("span");
     colActions.className = "admin-col";
+    if (!isDefault && m.enabled) {
+      var defBtn = document.createElement("button");
+      defBtn.className = "admin-btn-action";
+      defBtn.textContent = "set default";
+      defBtn.setAttribute("data-model-set-default", m.alias);
+      defBtn.setAttribute("aria-label", "Set " + m.alias + " as default model");
+      defBtn.setAttribute("title", "Set " + m.alias + " as default model");
+      colActions.appendChild(defBtn);
+    }
     if (!isConfig) {
       var editBtn = document.createElement("button");
       editBtn.className = "admin-btn-action";
       editBtn.textContent = "edit";
       editBtn.setAttribute("data-model-edit", m.definition_id);
+      editBtn.setAttribute("title", "Edit " + m.alias);
       colActions.appendChild(editBtn);
 
       var delBtn = document.createElement("button");
@@ -4169,6 +4250,7 @@ function _renderModels(items) {
       delBtn.textContent = "del";
       delBtn.setAttribute("data-model-delete", m.definition_id);
       delBtn.setAttribute("data-model-alias", m.alias);
+      delBtn.setAttribute("title", "Delete " + m.alias);
       colActions.appendChild(delBtn);
     }
     row.appendChild(colActions);
@@ -4177,6 +4259,30 @@ function _renderModels(items) {
   }
 
   // Bind event handlers
+  el.querySelectorAll("[data-model-set-default]").forEach(function (btn) {
+    btn.addEventListener("click", function () {
+      var alias = this.getAttribute("data-model-set-default");
+      var self = this;
+      self.disabled = true;
+      self.textContent = "setting\u2026";
+      authFetch("/v1/api/admin/settings/model.default_alias", {
+        method: "PUT",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ value: alias }),
+      })
+        .then(function (r) {
+          if (!r.ok) throw new Error();
+          showToast("Default model set to " + alias);
+          _flagModelSyncPending();
+          loadAdminModels();
+        })
+        .catch(function () {
+          showToast("Failed to set default model");
+          self.disabled = false;
+          self.textContent = "set default";
+        });
+    });
+  });
   el.querySelectorAll("[data-model-edit]").forEach(function (btn) {
     btn.addEventListener("click", function () {
       showEditModelModal(this.getAttribute("data-model-edit"));

turnstone/console/static/app.js

@@ -653,25 +653,21 @@ function buildNodeRow(node) {
         '%"></span>'
       : "";
 
-  var circuitTitle = "";
+  var healthTitle = "";
   if (node.health && node.health.backend) {
-    circuitTitle =
-      "backend: " +
-      node.health.backend.status +
-      ", circuit: " +
-      node.health.backend.circuit_state;
+    healthTitle = "backend: " + node.health.backend.status;
   }
   var degradedBadge = isDegraded
     ? '<span class="node-degraded-badge" title="' +
-      escapeHtml(circuitTitle) +
+      escapeHtml(healthTitle) +
       '" aria-label="' +
-      escapeHtml(circuitTitle) +
+      escapeHtml(healthTitle) +
       '">degraded</span>'
     : "";
 
   row.innerHTML =
     '<span class="node-cell node-cell-name"' +
-    (circuitTitle ? ' title="' + escapeHtml(circuitTitle) + '"' : "") +
+    (healthTitle ? ' title="' + escapeHtml(healthTitle) + '"' : "") +
     '><span class="' +
     dotClass +
     '"></span>' +
@@ -720,7 +716,9 @@ function buildNodeRow(node) {
 function toggleGroup(prefix) {
   expandedGroups[prefix] = !expandedGroups[prefix];
   var body = document.querySelector(
-    '.node-group-body[data-prefix="' + prefix.replace(/"/g, '\\"') + '"]',
+    '.node-group-body[data-prefix="' +
+      prefix.replace(/\\/g, "\\\\").replace(/"/g, '\\"') +
+      '"]',
   );
   if (!body) return;
   var isExpanded = expandedGroups[prefix];

turnstone/console/static/governance.js

@@ -2185,8 +2185,7 @@ function searchSkillDiscover() {
   var searchBtn = document.getElementById("skill-discover-search-btn");
   if (searchBtn) searchBtn.disabled = true;
 
-  var url = "/v1/api/admin/skills/discover?limit=20";
-  if (q) url += "&q=" + encodeURIComponent(q);
+  var url = "/v1/api/admin/skills/discover?limit=20&q=" + encodeURIComponent(q);
 
   authFetch(url)
     .then(function (r) {
@@ -2729,3 +2728,811 @@ function submitEditPromptPolicy() {
       submitBtn.disabled = false;
     });
 }
+
+// ---------------------------------------------------------------------------
+// Judge tab — settings, heuristic rules, output guard patterns
+// ---------------------------------------------------------------------------
+
+var _judgeSettings = [];
+var _judgeHeuristicRules = [];
+var _judgeOGPatterns = [];
+var _judgeModelDefs = [];
+var _chrTrapHandler = null; // create heuristic rule
+var _cogpTrapHandler = null; // create output guard pattern
+var _chrTriggerEl = null;
+var _cogpTriggerEl = null;
+
+// -- Sub-section switcher ---------------------------------------------------
+
+function switchJudgeSection(section) {
+  var sections = document.querySelectorAll(".judge-section");
+  for (var i = 0; i < sections.length; i++) sections[i].style.display = "none";
+  var btns = document.querySelectorAll(".judge-section-btn");
+  for (var i = 0; i < btns.length; i++) {
+    var isActive = btns[i].getAttribute("data-section") === section;
+    btns[i].classList.toggle("active", isActive);
+    btns[i].setAttribute("aria-selected", isActive ? "true" : "false");
+    btns[i].setAttribute("tabindex", isActive ? "0" : "-1");
+  }
+  var target = document.getElementById(section + "-section");
+  if (target) target.style.display = "";
+}
+
+// Arrow key navigation for judge sub-section tabs
+(function () {
+  var switcher = document.querySelector(".judge-section-switcher");
+  if (!switcher) return;
+  switcher.addEventListener("keydown", function (e) {
+    if (e.key !== "ArrowLeft" && e.key !== "ArrowRight") return;
+    var btns = switcher.querySelectorAll(".judge-section-btn");
+    var secs = [];
+    for (var i = 0; i < btns.length; i++)
+      secs.push(btns[i].getAttribute("data-section"));
+    var current = switcher.querySelector(".judge-section-btn.active");
+    var idx = secs.indexOf(current ? current.getAttribute("data-section") : "");
+    if (e.key === "ArrowRight") idx = (idx + 1) % secs.length;
+    else idx = (idx - 1 + secs.length) % secs.length;
+    e.preventDefault();
+    switchJudgeSection(secs[idx]);
+    btns[idx].focus();
+  });
+})();
+
+// -- Load all judge data ----------------------------------------------------
+
+function loadJudgeTab() {
+  loadJudgeHeuristicRules();
+  loadJudgeOGPatterns();
+  // Load model definitions before settings (settings render needs the model list)
+  authFetch("/v1/api/admin/model-definitions")
+    .then(function (r) {
+      if (!r.ok) throw new Error("Failed");
+      return r.json();
+    })
+    .then(function (d) {
+      _judgeModelDefs = d.models || [];
+    })
+    .catch(function () {
+      _judgeModelDefs = [];
+    })
+    .finally(function () {
+      loadJudgeSettings();
+    });
+}
+
+// -- Settings section -------------------------------------------------------
+// NOTE: innerHTML usage below is safe — all dynamic values are escaped via
+// escapeHtml before interpolation into the HTML string, and the
+// data originates from our own admin API (authenticated, same-origin).
+
+function loadJudgeSettings() {
+  authFetch("/v1/api/admin/judge/settings")
+    .then(function (r) {
+      if (!r.ok) throw new Error("Failed");
+      return r.json();
+    })
+    .then(function (d) {
+      _judgeSettings = d.settings || [];
+      renderJudgeSettings();
+    })
+    .catch(function () {
+      document.getElementById("judge-settings-container").innerHTML =
+        '<div class="dashboard-empty">Failed to load settings</div>';
+    });
+}
+
+function renderJudgeSettings() {
+  var c = document.getElementById("judge-settings-container");
+  if (!_judgeSettings.length) {
+    c.innerHTML = '<div class="dashboard-empty">No judge settings found</div>';
+    return;
+  }
+  var html = "";
+  for (var i = 0; i < _judgeSettings.length; i++) {
+    var s = _judgeSettings[i];
+    var shortKey = s.key.replace("judge.", "");
+    var inputHtml = "";
+    var currentVal = s.value;
+    var isDefault = s.source === "default";
+
+    if (s.type === "bool") {
+      inputHtml =
+        '<label class="toggle-label" style="display:flex;align-items:center;gap:8px;cursor:pointer">' +
+        '<input type="checkbox" data-key="' +
+        s.key +
+        '" ' +
+        (currentVal ? "checked" : "") +
+        " onchange=\"saveJudgeSetting('" +
+        s.key +
+        '\',this.checked)" style="width:16px;height:16px">' +
+        '<span style="font-size:12px">' +
+        (currentVal ? "Enabled" : "Disabled") +
+        "</span></label>";
+    } else if (s.type === "float") {
+      inputHtml =
+        '<div style="display:flex;gap:8px;align-items:center">' +
+        '<input type="number" step="0.01" data-key="' +
+        s.key +
+        '" value="' +
+        currentVal +
+        '"' +
+        (s.min_value != null ? ' min="' + s.min_value + '"' : "") +
+        (s.max_value != null ? ' max="' + s.max_value + '"' : "") +
+        ' style="width:100px;padding:4px 8px;background:var(--bg);border:1px solid var(--border-strong);color:var(--fg);border-radius:3px">' +
+        '<button class="admin-action-btn" onclick="saveJudgeSettingFromInput(\'' +
+        s.key +
+        "')\">Save</button></div>";
+    } else if (s.is_secret) {
+      inputHtml =
+        '<div style="display:flex;gap:8px;align-items:center">' +
+        '<input type="password" data-key="' +
+        s.key +
+        '" value="' +
+        escapeHtml(currentVal || "") +
+        '" placeholder="(not set)"' +
+        ' style="width:240px;padding:4px 8px;background:var(--bg);border:1px solid var(--border-strong);color:var(--fg);border-radius:3px">' +
+        '<button class="admin-action-btn" onclick="saveJudgeSettingFromInput(\'' +
+        s.key +
+        "')\">Save</button></div>";
+    } else if (shortKey === "model") {
+      // Model picker: select from model definitions
+      inputHtml =
+        '<div style="display:flex;gap:8px;align-items:center">' +
+        '<select data-key="' +
+        s.key +
+        '" onchange="saveJudgeSetting(\'' +
+        s.key +
+        "',this.value)\"" +
+        ' style="width:240px;padding:4px 8px;background:var(--bg);border:1px solid var(--border-strong);color:var(--fg);border-radius:3px">' +
+        '<option value="">(same as session)</option>';
+      for (var m = 0; m < _judgeModelDefs.length; m++) {
+        var md = _judgeModelDefs[m];
+        if (!md.enabled) continue;
+        inputHtml +=
+          '<option value="' +
+          escapeHtml(md.alias) +
+          '"' +
+          (currentVal === md.alias ? " selected" : "") +
+          ">" +
+          escapeHtml(md.alias) +
+          " (" +
+          escapeHtml(md.model) +
+          ")</option>";
+      }
+      // Also allow the current value if it's not in model defs (manual entry)
+      if (
+        currentVal &&
+        !_judgeModelDefs.some(function (md) {
+          return md.alias === currentVal;
+        })
+      ) {
+        inputHtml +=
+          '<option value="' +
+          escapeHtml(currentVal) +
+          '" selected>' +
+          escapeHtml(currentVal) +
+          " (manual)</option>";
+      }
+      inputHtml += "</select></div>";
+    } else {
+      inputHtml =
+        '<div style="display:flex;gap:8px;align-items:center">' +
+        '<input type="text" data-key="' +
+        s.key +
+        '" value="' +
+        escapeHtml(currentVal || "") +
+        '"' +
+        ' style="width:240px;padding:4px 8px;background:var(--bg);border:1px solid var(--border-strong);color:var(--fg);border-radius:3px">' +
+        '<button class="admin-action-btn" onclick="saveJudgeSettingFromInput(\'' +
+        s.key +
+        "')\">Save</button></div>";
+    }
+
+    var resetBtn = !isDefault
+      ? ' <button class="admin-action-btn" style="font-size:11px;padding:2px 6px" onclick="resetJudgeSetting(\'' +
+        s.key +
+        "')\">Reset</button>"
+      : "";
+
+    html +=
+      '<div style="margin-bottom:12px;padding-bottom:10px;border-bottom:1px solid var(--border-strong)">' +
+      '<div style="display:flex;align-items:center;gap:8px;margin-bottom:4px">' +
+      '<code style="font-family:var(--font-display);font-size:12px;font-weight:600;color:var(--fg)">' +
+      shortKey +
+      "</code>" +
+      (isDefault
+        ? '<span style="font-size:11px;color:var(--fg-dim)">default</span>'
+        : '<span style="font-size:11px;color:var(--green)">customized</span>') +
+      resetBtn +
+      "</div>" +
+      '<div style="font-size:11px;color:var(--fg-dim);margin-bottom:5px">' +
+      escapeHtml(s.help || s.description || "") +
+      "</div>" +
+      inputHtml +
+      "</div>";
+  }
+  c.innerHTML = html;
+}
+
+function saveJudgeSetting(key, value) {
+  authFetch("/v1/api/admin/judge/settings/" + encodeURIComponent(key), {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ value: value }),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast("Setting saved");
+      loadJudgeSettings();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+function saveJudgeSettingFromInput(key) {
+  var input = document.querySelector('[data-key="' + key + '"]');
+  if (!input) return;
+  saveJudgeSetting(key, input.value);
+}
+
+function resetJudgeSetting(key) {
+  authFetch("/v1/api/admin/judge/settings/" + encodeURIComponent(key), {
+    method: "DELETE",
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast("Reset to default");
+      loadJudgeSettings();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+// -- Heuristic Rules section ------------------------------------------------
+
+function loadJudgeHeuristicRules() {
+  authFetch("/v1/api/admin/judge/heuristic-rules")
+    .then(function (r) {
+      if (!r.ok) throw new Error("Failed");
+      return r.json();
+    })
+    .then(function (d) {
+      _judgeHeuristicRules = d.rules || [];
+      renderHeuristicRules();
+    })
+    .catch(function () {
+      document.getElementById("judge-heuristic-table-container").innerHTML =
+        '<div class="dashboard-empty">Failed to load rules</div>';
+    });
+}
+
+function renderHeuristicRules() {
+  var c = document.getElementById("judge-heuristic-table-container");
+  if (!_judgeHeuristicRules.length) {
+    c.innerHTML = '<div class="dashboard-empty">No rules found</div>';
+    return;
+  }
+  var html = "";
+  for (var i = 0; i < _judgeHeuristicRules.length; i++) {
+    var r = _judgeHeuristicRules[i];
+    var sourceBadge =
+      r.source === "builtin"
+        ? '<span class="scope-badge">built-in</span>'
+        : r.source === "builtin-overridden"
+          ? '<span class="scope-badge scope-scan-safe">overridden</span>'
+          : r.source === "builtin-disabled"
+            ? '<span class="scope-badge scope-deny">disabled</span>'
+            : '<span class="scope-badge scope-write">custom</span>';
+    var statusBadge = r.enabled
+      ? '<span class="scope-badge scope-scan-safe">active</span>'
+      : '<span class="scope-badge scope-deny">disabled</span>';
+    var actions = "";
+    if (r.rule_id) {
+      actions =
+        '<button class="admin-btn-action" onclick="toggleHeuristicRule(\'' +
+        r.rule_id +
+        "\'," +
+        !r.enabled +
+        ')">' +
+        (r.enabled ? "Disable" : "Enable") +
+        "</button> " +
+        '<button class="admin-btn-danger" onclick="deleteHeuristicRule(\'' +
+        r.rule_id +
+        "')\">Delete</button>";
+    } else {
+      actions =
+        '<button class="admin-btn-action" onclick="overrideBuiltinHeuristicRule(\'' +
+        escapeHtml(r.name) +
+        "')\">Customize</button>";
+    }
+    html +=
+      '<div class="admin-row">' +
+      '<span class="admin-col"><code>' +
+      escapeHtml(r.name) +
+      "</code></span>" +
+      '<span class="admin-col admin-col-htier">' +
+      escapeHtml(r.tier || r.risk_level) +
+      "</span>" +
+      '<span class="admin-col admin-col-hrisk">' +
+      escapeHtml(r.risk_level) +
+      "</span>" +
+      '<span class="admin-col"><code>' +
+      escapeHtml(r.tool_pattern) +
+      "</code></span>" +
+      '<span class="admin-col admin-col-hrec">' +
+      escapeHtml(r.recommendation) +
+      "</span>" +
+      '<span class="admin-col">' +
+      sourceBadge +
+      "</span>" +
+      '<span class="admin-col">' +
+      statusBadge +
+      "</span>" +
+      '<span class="admin-col">' +
+      actions +
+      "</span></div>";
+  }
+  c.innerHTML = html;
+}
+
+function toggleHeuristicRule(ruleId, enabled) {
+  authFetch("/v1/api/admin/judge/heuristic-rules/" + ruleId, {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ enabled: enabled }),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast(enabled ? "Rule enabled" : "Rule disabled");
+      loadJudgeHeuristicRules();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+function deleteHeuristicRule(ruleId) {
+  showConfirmModal(
+    "Delete Rule",
+    "Delete this heuristic rule? This action cannot be undone.",
+    "Delete",
+    function () {
+      authFetch("/v1/api/admin/judge/heuristic-rules/" + ruleId, {
+        method: "DELETE",
+      })
+        .then(function (r) {
+          if (!r.ok)
+            return r.json().then(function (d) {
+              throw new Error(d.error || "Failed");
+            });
+          return r.json();
+        })
+        .then(function () {
+          showToast("Rule deleted");
+          loadJudgeHeuristicRules();
+        })
+        .catch(function (e) {
+          showToast("Error: " + e.message);
+        });
+    },
+  );
+}
+
+function overrideBuiltinHeuristicRule(name) {
+  // Find the built-in rule data
+  var rule = null;
+  for (var i = 0; i < _judgeHeuristicRules.length; i++) {
+    if (_judgeHeuristicRules[i].name === name) {
+      rule = _judgeHeuristicRules[i];
+      break;
+    }
+  }
+  if (!rule) return;
+  // Create a DB copy marked as builtin override, initially disabled
+  var payload = {
+    name: rule.name,
+    risk_level: rule.risk_level,
+    confidence: rule.confidence,
+    recommendation: rule.recommendation,
+    tool_pattern: rule.tool_pattern,
+    arg_patterns: rule.arg_patterns,
+    intent_template: rule.intent_template || "",
+    reasoning_template: rule.reasoning_template || "",
+    tier: rule.tier || rule.risk_level,
+    priority: rule.priority || 0,
+    builtin: true,
+    enabled: false,
+  };
+  authFetch("/v1/api/admin/judge/heuristic-rules", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast("Built-in rule overridden (disabled)");
+      loadJudgeHeuristicRules();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+function showCreateHeuristicRuleModal() {
+  _chrTriggerEl = document.activeElement;
+  var ov = document.getElementById("create-hr-overlay");
+  ov.style.display = "flex";
+  document.getElementById("hr-name").value = "";
+  document.getElementById("hr-tier").value = "medium";
+  document.getElementById("hr-risk").value = "medium";
+  document.getElementById("hr-rec").value = "review";
+  document.getElementById("hr-tool").value = "bash";
+  document.getElementById("hr-args").value = "";
+  document.getElementById("hr-conf").value = "0.8";
+  document.getElementById("hr-intent").value = "";
+  document.getElementById("hr-reason").value = "";
+  document.getElementById("create-hr-error").style.display = "none";
+  document.getElementById("hr-submit").disabled = false;
+  document.getElementById("hr-name").focus();
+  _chrTrapHandler = _installTrap("create-hr-overlay", "create-hr-box");
+}
+
+function hideCreateHRModal() {
+  document.getElementById("create-hr-overlay").style.display = "none";
+  _chrTrapHandler = _removeTrap(_chrTrapHandler);
+  if (_chrTriggerEl && _chrTriggerEl.focus) _chrTriggerEl.focus();
+  _chrTriggerEl = null;
+}
+
+function submitCreateHeuristicRule() {
+  var errEl = document.getElementById("create-hr-error");
+  errEl.style.display = "none";
+  var argsText = document.getElementById("hr-args").value.trim();
+  var argPatterns = argsText
+    ? argsText.split("\n").filter(function (l) {
+        return l.trim();
+      })
+    : [];
+  var payload = {
+    name: document.getElementById("hr-name").value.trim(),
+    tier: document.getElementById("hr-tier").value,
+    risk_level: document.getElementById("hr-risk").value,
+    recommendation: document.getElementById("hr-rec").value,
+    tool_pattern: document.getElementById("hr-tool").value.trim(),
+    arg_patterns: argPatterns,
+    confidence: parseFloat(document.getElementById("hr-conf").value) || 0.8,
+    intent_template: document.getElementById("hr-intent").value.trim(),
+    reasoning_template: document.getElementById("hr-reason").value.trim(),
+    enabled: true,
+  };
+  var btn = document.getElementById("hr-submit");
+  btn.disabled = true;
+  authFetch("/v1/api/admin/judge/heuristic-rules", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      hideCreateHRModal();
+      showToast("Rule created");
+      loadJudgeHeuristicRules();
+    })
+    .catch(function (e) {
+      errEl.textContent = e.message;
+      errEl.style.display = "";
+    })
+    .finally(function () {
+      btn.disabled = false;
+    });
+}
+
+// -- Output Guard Patterns section ------------------------------------------
+
+function loadJudgeOGPatterns() {
+  authFetch("/v1/api/admin/judge/output-guard-patterns")
+    .then(function (r) {
+      if (!r.ok) throw new Error("Failed");
+      return r.json();
+    })
+    .then(function (d) {
+      _judgeOGPatterns = d.patterns || [];
+      renderOGPatterns();
+    })
+    .catch(function () {
+      document.getElementById("judge-og-table-container").innerHTML =
+        '<div class="dashboard-empty">Failed to load patterns</div>';
+    });
+}
+
+function renderOGPatterns() {
+  var c = document.getElementById("judge-og-table-container");
+  if (!_judgeOGPatterns.length) {
+    c.innerHTML = '<div class="dashboard-empty">No patterns found</div>';
+    return;
+  }
+  var html = "";
+  for (var i = 0; i < _judgeOGPatterns.length; i++) {
+    var p = _judgeOGPatterns[i];
+    var sourceBadge =
+      p.source === "builtin"
+        ? '<span class="scope-badge">built-in</span>'
+        : p.source === "builtin-overridden"
+          ? '<span class="scope-badge scope-scan-safe">overridden</span>'
+          : p.source === "builtin-disabled"
+            ? '<span class="scope-badge scope-deny">disabled</span>'
+            : '<span class="scope-badge scope-write">custom</span>';
+    var statusBadge = p.enabled
+      ? '<span class="scope-badge scope-scan-safe">active</span>'
+      : '<span class="scope-badge scope-deny">disabled</span>';
+    var actions = "";
+    if (p.pattern_id) {
+      actions =
+        '<button class="admin-btn-action" onclick="toggleOGPattern(\'' +
+        p.pattern_id +
+        "\'," +
+        !p.enabled +
+        ')">' +
+        (p.enabled ? "Disable" : "Enable") +
+        "</button> " +
+        '<button class="admin-btn-danger" onclick="deleteOGPattern(\'' +
+        p.pattern_id +
+        "')\">Delete</button>";
+    } else {
+      actions =
+        '<button class="admin-btn-action" onclick="overrideBuiltinOGPattern(\'' +
+        escapeHtml(p.name) +
+        "')\">Customize</button>";
+    }
+    html +=
+      '<div class="admin-row">' +
+      '<span class="admin-col"><code>' +
+      escapeHtml(p.name) +
+      "</code></span>" +
+      '<span class="admin-col">' +
+      escapeHtml(p.category) +
+      "</span>" +
+      '<span class="admin-col admin-col-ogrisk">' +
+      escapeHtml(p.risk_level) +
+      "</span>" +
+      '<span class="admin-col admin-col-ogflag"><code>' +
+      escapeHtml(p.flag_name) +
+      "</code></span>" +
+      '<span class="admin-col">' +
+      sourceBadge +
+      "</span>" +
+      '<span class="admin-col">' +
+      statusBadge +
+      "</span>" +
+      '<span class="admin-col">' +
+      actions +
+      "</span></div>";
+  }
+  c.innerHTML = html;
+}
+
+function toggleOGPattern(patternId, enabled) {
+  authFetch("/v1/api/admin/judge/output-guard-patterns/" + patternId, {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ enabled: enabled }),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast(enabled ? "Pattern enabled" : "Pattern disabled");
+      loadJudgeOGPatterns();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+function deleteOGPattern(patternId) {
+  showConfirmModal(
+    "Delete Pattern",
+    "Delete this output guard pattern? This action cannot be undone.",
+    "Delete",
+    function () {
+      authFetch("/v1/api/admin/judge/output-guard-patterns/" + patternId, {
+        method: "DELETE",
+      })
+        .then(function (r) {
+          if (!r.ok)
+            return r.json().then(function (d) {
+              throw new Error(d.error || "Failed");
+            });
+          return r.json();
+        })
+        .then(function () {
+          showToast("Pattern deleted");
+          loadJudgeOGPatterns();
+        })
+        .catch(function (e) {
+          showToast("Error: " + e.message);
+        });
+    },
+  );
+}
+
+function overrideBuiltinOGPattern(name) {
+  var pat = null;
+  for (var i = 0; i < _judgeOGPatterns.length; i++) {
+    if (_judgeOGPatterns[i].name === name) {
+      pat = _judgeOGPatterns[i];
+      break;
+    }
+  }
+  if (!pat) return;
+  var payload = {
+    name: pat.name,
+    category: pat.category,
+    risk_level: pat.risk_level,
+    pattern: pat.pattern || "",
+    flag_name: pat.flag_name,
+    annotation: pat.annotation || "",
+    pattern_flags: pat.pattern_flags || "",
+    is_credential: pat.is_credential || false,
+    redact_label: pat.redact_label || "",
+    priority: pat.priority || 0,
+    builtin: true,
+    enabled: false,
+  };
+  authFetch("/v1/api/admin/judge/output-guard-patterns", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      showToast("Built-in pattern overridden (disabled)");
+      loadJudgeOGPatterns();
+    })
+    .catch(function (e) {
+      showToast("Error: " + e.message);
+    });
+}
+
+function showCreateOutputGuardPatternModal() {
+  _cogpTriggerEl = document.activeElement;
+  var ov = document.getElementById("create-ogp-overlay");
+  ov.style.display = "flex";
+  document.getElementById("ogp-name").value = "";
+  document.getElementById("ogp-cat").value = "prompt_injection";
+  document.getElementById("ogp-risk").value = "medium";
+  document.getElementById("ogp-pattern").value = "";
+  document.getElementById("ogp-flag").value = "";
+  document.getElementById("ogp-ann").value = "";
+  document.getElementById("ogp-flags").value = "";
+  document.getElementById("ogp-cred").checked = false;
+  document.getElementById("ogp-redact").value = "";
+  document.getElementById("ogp-regex-result").textContent = "";
+  document.getElementById("create-ogp-error").style.display = "none";
+  document.getElementById("ogp-submit").disabled = false;
+  document.getElementById("ogp-name").focus();
+  _cogpTrapHandler = _installTrap("create-ogp-overlay", "create-ogp-box");
+}
+
+function hideCreateOGPModal() {
+  document.getElementById("create-ogp-overlay").style.display = "none";
+  _cogpTrapHandler = _removeTrap(_cogpTrapHandler);
+  if (_cogpTriggerEl && _cogpTriggerEl.focus) _cogpTriggerEl.focus();
+  _cogpTriggerEl = null;
+}
+
+function validateOGRegex() {
+  var pattern = document.getElementById("ogp-pattern").value;
+  var resultEl = document.getElementById("ogp-regex-result");
+  if (!pattern) {
+    resultEl.textContent = "";
+    return;
+  }
+  authFetch("/v1/api/admin/judge/validate-regex", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ pattern: pattern }),
+  })
+    .then(function (r) {
+      if (!r.ok) throw new Error("Validation failed");
+      return r.json();
+    })
+    .then(function (d) {
+      if (d.valid) {
+        resultEl.textContent = "Valid";
+        resultEl.style.color = "var(--green)";
+      } else {
+        resultEl.textContent = d.error || "Invalid";
+        resultEl.style.color = "var(--red)";
+      }
+    })
+    .catch(function () {
+      resultEl.textContent = "Validation failed";
+      resultEl.style.color = "var(--red)";
+    });
+}
+
+function submitCreateOGPattern() {
+  var errEl = document.getElementById("create-ogp-error");
+  errEl.style.display = "none";
+  var payload = {
+    name: document.getElementById("ogp-name").value.trim(),
+    category: document.getElementById("ogp-cat").value,
+    risk_level: document.getElementById("ogp-risk").value,
+    pattern: document.getElementById("ogp-pattern").value,
+    flag_name: document.getElementById("ogp-flag").value.trim(),
+    annotation: document.getElementById("ogp-ann").value.trim(),
+    pattern_flags: document.getElementById("ogp-flags").value.trim(),
+    is_credential: document.getElementById("ogp-cred").checked,
+    redact_label: document.getElementById("ogp-redact").value.trim(),
+    enabled: true,
+  };
+  var btn = document.getElementById("ogp-submit");
+  btn.disabled = true;
+  authFetch("/v1/api/admin/judge/output-guard-patterns", {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify(payload),
+  })
+    .then(function (r) {
+      if (!r.ok)
+        return r.json().then(function (d) {
+          throw new Error(d.error || "Failed");
+        });
+      return r.json();
+    })
+    .then(function () {
+      hideCreateOGPModal();
+      showToast("Pattern created");
+      loadJudgeOGPatterns();
+    })
+    .catch(function (e) {
+      errEl.textContent = e.message;
+      errEl.style.display = "";
+    })
+    .finally(function () {
+      btn.disabled = false;
+    });
+}

turnstone/console/static/index.html

@@ -96,6 +96,7 @@
           <button id="tab-roles" class="admin-nav" data-tab="roles" role="tab" aria-selected="false" aria-controls="admin-roles" tabindex="-1" onclick="switchAdminTab('roles')">Roles</button>
           <button id="tab-policies" class="admin-nav" data-tab="policies" role="tab" aria-selected="false" aria-controls="admin-policies" tabindex="-1" onclick="switchAdminTab('policies')">Policies</button>
           <button id="tab-prompt-policies" class="admin-nav" data-tab="prompt-policies" role="tab" aria-selected="false" aria-controls="admin-prompt-policies" tabindex="-1" onclick="switchAdminTab('prompt-policies')">Prompts</button>
+          <button id="tab-judge" class="admin-nav" data-tab="judge" role="tab" aria-selected="false" aria-controls="admin-judge" tabindex="-1" onclick="switchAdminTab('judge')">Judge</button>
         </div>
         <div class="admin-sidebar-group" data-group="extensions" role="group" aria-label="Extensions">
           <div class="admin-sidebar-group-label" aria-hidden="true">Extensions</div>
@@ -278,6 +279,144 @@
       </div>
     </div>
 
+    <!-- Judge Tab -->
+    <div id="admin-judge" class="admin-panel" role="tabpanel" aria-labelledby="tab-judge" style="display:none">
+      <div class="admin-toolbar">
+        <span class="section-header" style="margin:0">JUDGE</span>
+      </div>
+
+      <!-- Sub-panel switcher -->
+      <div class="judge-section-switcher" role="tablist" aria-label="Judge sections">
+        <button id="judge-tab-settings" class="judge-section-btn active" role="tab" aria-selected="true" aria-controls="judge-settings-section" tabindex="0" data-section="judge-settings" onclick="switchJudgeSection('judge-settings')">Settings</button>
+        <button id="judge-tab-heuristic" class="judge-section-btn" role="tab" aria-selected="false" aria-controls="judge-heuristic-section" tabindex="-1" data-section="judge-heuristic" onclick="switchJudgeSection('judge-heuristic')">Heuristic Rules</button>
+        <button id="judge-tab-output-guard" class="judge-section-btn" role="tab" aria-selected="false" aria-controls="judge-output-guard-section" tabindex="-1" data-section="judge-output-guard" onclick="switchJudgeSection('judge-output-guard')">Output Guard</button>
+      </div>
+
+      <!-- Settings section -->
+      <div id="judge-settings-section" class="judge-section" role="tabpanel" aria-labelledby="judge-tab-settings">
+        <div id="judge-settings-container" style="max-width:600px">
+          <div class="dashboard-empty">Loading settings...</div>
+        </div>
+      </div>
+
+      <!-- Heuristic Rules section -->
+      <div id="judge-heuristic-section" class="judge-section" role="tabpanel" aria-labelledby="judge-tab-heuristic" style="display:none">
+        <div class="admin-toolbar" style="margin-bottom:12px">
+          <span style="font-size:13px;color:var(--fg-dim)">Pattern rules for pre-execution intent validation</span>
+          <button class="admin-action-btn" onclick="showCreateHeuristicRuleModal()">+ Add rule</button>
+        </div>
+        <div class="admin-colheaders" aria-hidden="true">
+          <span class="admin-col">NAME</span>
+          <span class="admin-col admin-col-htier">TIER</span>
+          <span class="admin-col admin-col-hrisk">RISK</span>
+          <span class="admin-col">TOOL</span>
+          <span class="admin-col admin-col-hrec">REC.</span>
+          <span class="admin-col">SOURCE</span>
+          <span class="admin-col">STATUS</span>
+          <span class="admin-col">ACTIONS</span>
+        </div>
+        <div id="judge-heuristic-table-container" role="list" aria-label="Heuristic rules" aria-live="polite">
+          <div class="dashboard-empty">Loading rules...</div>
+        </div>
+      </div>
+
+      <!-- Output Guard Patterns section -->
+      <div id="judge-output-guard-section" class="judge-section" role="tabpanel" aria-labelledby="judge-tab-output-guard" style="display:none">
+        <div class="admin-toolbar" style="margin-bottom:12px">
+          <span style="font-size:13px;color:var(--fg-dim)">Regex patterns for post-execution output scanning</span>
+          <button class="admin-action-btn" onclick="showCreateOutputGuardPatternModal()">+ Add pattern</button>
+        </div>
+        <div class="admin-colheaders" aria-hidden="true">
+          <span class="admin-col">NAME</span>
+          <span class="admin-col">CATEGORY</span>
+          <span class="admin-col admin-col-ogrisk">RISK</span>
+          <span class="admin-col admin-col-ogflag">FLAG</span>
+          <span class="admin-col">SOURCE</span>
+          <span class="admin-col">STATUS</span>
+          <span class="admin-col">ACTIONS</span>
+        </div>
+        <div id="judge-og-table-container" role="list" aria-label="Output guard patterns" aria-live="polite">
+          <div class="dashboard-empty">Loading patterns...</div>
+        </div>
+      </div>
+    </div>
+
+    <!-- Judge: Create Heuristic Rule Modal -->
+    <div id="create-hr-overlay" style="display:none" role="dialog" aria-modal="true" aria-labelledby="create-hr-title">
+      <div id="create-hr-box" class="admin-modal admin-modal-wide">
+        <h2 id="create-hr-title">Create Heuristic Rule</h2>
+        <div id="create-hr-error" role="alert" aria-live="assertive"></div>
+        <label for="hr-name">Name</label>
+        <input id="hr-name" type="text" placeholder="my-custom-rule" autocomplete="off" spellcheck="false">
+        <div style="display:flex;gap:12px">
+          <div style="flex:1">
+            <label for="hr-tier">Tier</label>
+            <select id="hr-tier"><option>critical</option><option>high</option><option selected>medium</option><option>low</option></select>
+          </div>
+          <div style="flex:1">
+            <label for="hr-risk">Risk Level</label>
+            <select id="hr-risk"><option>critical</option><option>high</option><option selected>medium</option><option>low</option></select>
+          </div>
+          <div style="flex:1">
+            <label for="hr-rec">Recommendation</label>
+            <select id="hr-rec"><option>approve</option><option selected>review</option><option>deny</option></select>
+          </div>
+        </div>
+        <label for="hr-tool">Tool Pattern <span class="label-hint">fnmatch syntax: bash, write_file, mcp__*</span></label>
+        <input id="hr-tool" type="text" value="bash" autocomplete="off" spellcheck="false">
+        <label for="hr-args">Arg Patterns <span class="label-hint">one regex per line</span></label>
+        <textarea id="hr-args" rows="3" style="font-family:var(--font-mono);font-size:12px"></textarea>
+        <label for="hr-conf">Confidence <span class="label-hint">0.0 – 1.0</span></label>
+        <input id="hr-conf" type="number" step="0.05" value="0.8" min="0" max="1" style="width:100px">
+        <label for="hr-intent">Intent Description</label>
+        <input id="hr-intent" type="text" placeholder="Detected dangerous operation: {arg_snippet}" autocomplete="off">
+        <label for="hr-reason">Reasoning</label>
+        <input id="hr-reason" type="text" placeholder="Explain why this is risky" autocomplete="off">
+        <div class="modal-buttons">
+          <button class="modal-cancel" onclick="hideCreateHRModal()">Cancel</button>
+          <button id="hr-submit" class="modal-submit" onclick="submitCreateHeuristicRule()">Create</button>
+        </div>
+      </div>
+    </div>
+
+    <!-- Judge: Create Output Guard Pattern Modal -->
+    <div id="create-ogp-overlay" style="display:none" role="dialog" aria-modal="true" aria-labelledby="create-ogp-title">
+      <div id="create-ogp-box" class="admin-modal admin-modal-wide">
+        <h2 id="create-ogp-title">Create Output Guard Pattern</h2>
+        <div id="create-ogp-error" role="alert" aria-live="assertive"></div>
+        <label for="ogp-name">Name</label>
+        <input id="ogp-name" type="text" placeholder="my-pattern" autocomplete="off" spellcheck="false">
+        <div style="display:flex;gap:12px">
+          <div style="flex:1">
+            <label for="ogp-cat">Category</label>
+            <select id="ogp-cat"><option>prompt_injection</option><option>credentials</option><option>encoded_payloads</option><option>adversarial_urls</option><option>info_disclosure</option></select>
+          </div>
+          <div style="flex:1">
+            <label for="ogp-risk">Risk Level</label>
+            <select id="ogp-risk"><option>high</option><option selected>medium</option><option>low</option></select>
+          </div>
+        </div>
+        <label for="ogp-pattern">Regex Pattern</label>
+        <input id="ogp-pattern" type="text" autocomplete="off" spellcheck="false" style="font-family:var(--font-mono);font-size:12px">
+        <button class="admin-btn-action" style="margin:4px 0 8px" onclick="validateOGRegex()">Validate regex</button>
+        <span id="ogp-regex-result" role="status" aria-live="polite" style="font-size:11px;margin-left:8px"></span>
+        <label for="ogp-flag">Flag Name</label>
+        <input id="ogp-flag" type="text" placeholder="my_flag" autocomplete="off" spellcheck="false">
+        <label for="ogp-ann">Annotation</label>
+        <input id="ogp-ann" type="text" placeholder="Human-readable description" autocomplete="off">
+        <label for="ogp-flags">Pattern Flags <span class="label-hint">comma-separated: IGNORECASE, MULTILINE, DOTALL</span></label>
+        <input id="ogp-flags" type="text" autocomplete="off">
+        <div style="display:flex;gap:16px;margin:8px 0">
+          <label style="display:flex;align-items:center;gap:6px;font-size:12px"><input id="ogp-cred" type="checkbox"> Is Credential</label>
+          <label style="font-size:12px">Redact Label <input id="ogp-redact" type="text" placeholder="api_key" style="width:100px;margin-left:4px"></label>
+        </div>
+        <div class="modal-buttons">
+          <button class="modal-cancel" onclick="hideCreateOGPModal()">Cancel</button>
+          <button id="ogp-submit" class="modal-submit" onclick="submitCreateOGPattern()">Create</button>
+        </div>
+      </div>
+    </div>
+
     <!-- Skills Tab -->
     <div id="admin-skills" class="admin-panel" role="tabpanel" aria-labelledby="tab-skills" style="display:none">
       <div class="admin-toolbar">

turnstone/console/static/style.css

@@ -768,7 +768,8 @@
   color: var(--fg-dim);
   padding: 12px 16px 4px;
 }
-.admin-sidebar-group:first-child .admin-sidebar-group-label {
+.admin-sidebar-group:first-child .admin-sidebar-group-label,
+.admin-sidebar-close + .admin-sidebar-group .admin-sidebar-group-label {
   padding-top: 4px;
 }
 
@@ -818,13 +819,16 @@
   z-index: 499;
   opacity: 0;
   pointer-events: none;
-  transition: opacity 0.25s ease;
+  transition: opacity 0.25s cubic-bezier(0.4, 0, 0.2, 1);
 }
 .admin-sidebar-backdrop.visible {
   opacity: 1;
   pointer-events: auto;
 }
 
+/* Close header — hidden on desktop, shown via mobile media query */
+.admin-sidebar-close { display: none; }
+
 /* Mobile menu toggle — visible only on mobile, lives in toolbars */
 .admin-mobile-toggle {
   display: none;
@@ -832,8 +836,8 @@
   border: 1px solid var(--border);
   border-radius: var(--radius-sm);
   color: var(--fg-dim);
-  width: 28px;
-  height: 28px;
+  min-width: 44px;
+  min-height: 44px;
   cursor: pointer;
   align-items: center;
   justify-content: center;
@@ -850,6 +854,10 @@
   box-shadow: 0 4px 0 currentColor, 0 8px 0 currentColor;
 }
 .admin-mobile-toggle:hover { color: var(--fg); }
+.admin-mobile-toggle:focus-visible {
+  outline: 2px solid var(--accent);
+  outline-offset: 2px;
+}
 @media (max-width: 700px) {
   .admin-mobile-toggle { display: flex; }
 }
@@ -1400,7 +1408,8 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
 #memory-detail-overlay,
 #mcp-create-overlay, #mcp-import-overlay, #mcp-detail-overlay, #mcp-install-overlay,
 #github-import-overlay,
-#model-create-overlay {
+#model-create-overlay,
+#create-hr-overlay, #create-ogp-overlay {
   position: fixed;
   inset: 0;
   background: rgba(0, 0, 0, 0.7);
@@ -1452,6 +1461,20 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
     grid-template-columns: 1.2fr 80px 70px 70px 70px;
   }
   .admin-col-wcmd, .admin-col-wcond, .admin-col-winterval { display: none; }
+
+  /* Judge: Heuristic Rules - hide Tier, Risk, Rec on mobile */
+  #judge-heuristic-section .admin-colheaders,
+  #judge-heuristic-section .admin-row {
+    grid-template-columns: 1fr 100px 90px 60px 120px;
+  }
+  .admin-col-htier, .admin-col-hrisk, .admin-col-hrec { display: none; }
+
+  /* Judge: Output Guard - hide Risk, Flag on mobile */
+  #judge-output-guard-section .admin-colheaders,
+  #judge-output-guard-section .admin-row {
+    grid-template-columns: 1fr 120px 90px 60px 120px;
+  }
+  .admin-col-ogrisk, .admin-col-ogflag { display: none; }
 }
 
 /* ==========================================================================
@@ -1464,18 +1487,62 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
     right: 0;
     bottom: 0;
     left: auto;
-    width: 220px;
+    width: 260px;
+    max-width: 80vw;
     z-index: 500;
     background: var(--bg-surface);
     border-left: 1px solid var(--border-strong);
     border-right: none;
+    box-shadow: -4px 0 24px rgba(0, 0, 0, 0.35);
     transform: translateX(100%);
-    transition: transform 0.25s ease;
-    padding-top: 48px;
+    transition: transform 0.25s cubic-bezier(0.4, 0, 0.2, 1);
+    padding-top: 0;
+    overflow-y: auto;
+    -webkit-overflow-scrolling: touch;
   }
   .admin-sidebar.open { transform: translateX(0); }
-  .admin-sidebar.collapsed { transform: translateX(100%); width: 220px; }
+  .admin-sidebar.collapsed { transform: translateX(100%); }
   .admin-content { padding-right: 0; }
+
+  /* Close button at top of mobile drawer */
+  .admin-sidebar-close {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 12px 16px;
+    border-bottom: 1px solid var(--border);
+    font-family: var(--font-display);
+    font-size: 11px;
+    font-weight: 600;
+    text-transform: uppercase;
+    letter-spacing: 0.08em;
+    color: var(--fg-dim);
+  }
+  .admin-sidebar-close button {
+    background: none;
+    border: none;
+    color: var(--fg-dim);
+    font-size: 20px;
+    line-height: 1;
+    cursor: pointer;
+    padding: 10px;
+    min-width: 44px;
+    min-height: 44px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: var(--radius-sm);
+  }
+  .admin-sidebar-close button:hover { color: var(--fg); }
+  .admin-sidebar-close button:focus-visible {
+    outline: 2px solid var(--accent);
+    outline-offset: 2px;
+  }
+
+  /* Flip active indicator to left border on mobile (drawer is on right edge) */
+  .admin-nav { border-right: none; border-left: 2px solid transparent; }
+  .admin-nav:hover { border-right-color: transparent; border-left-color: var(--border-strong); }
+  .admin-nav.active { border-right-color: transparent; border-left-color: var(--accent); }
 }
 
 /* ==========================================================================
@@ -1542,6 +1609,49 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
   grid-template-columns: 80px 80px 1fr 120px 1.5fr;
 }
 
+/* ==========================================================================
+   Judge sub-section tabs
+   ========================================================================== */
+.judge-section-switcher {
+  display: flex;
+  gap: 8px;
+  margin: 12px 0 16px;
+  border-bottom: 1px solid var(--border-strong);
+}
+.judge-section-btn {
+  padding: 6px 14px;
+  background: none;
+  border: none;
+  border-bottom: 2px solid transparent;
+  color: var(--fg-dim);
+  cursor: pointer;
+  font-family: var(--font-display);
+  font-size: 13px;
+  transition: color 0.15s, border-color 0.15s;
+}
+.judge-section-btn:hover { color: var(--fg); }
+.judge-section-btn.active {
+  border-bottom-color: var(--accent);
+  color: var(--fg);
+}
+.judge-section-btn:focus-visible {
+  outline: 2px solid var(--accent);
+  outline-offset: -2px;
+}
+
+/* ==========================================================================
+   Judge: Heuristic Rules grid
+   ========================================================================== */
+#judge-heuristic-section .admin-colheaders,
+#judge-heuristic-section .admin-row {
+  grid-template-columns: 1.2fr 70px 70px 100px 70px 90px 60px 120px;
+}
+/* Judge: Output Guard Patterns grid */
+#judge-output-guard-section .admin-colheaders,
+#judge-output-guard-section .admin-row {
+  grid-template-columns: 1.2fr 120px 60px 100px 90px 60px 120px;
+}
+
 /* Audit action badges */
 .audit-badge {
   display: inline-block;
@@ -2144,6 +2254,7 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
 
 /* -- MCP source badges ---------------------------------------------------- */
 .scope-config{color:var(--magenta);border-color:rgba(192,132,252,.25)}
+.scope-default{color:var(--yellow);border-color:rgba(251,191,36,.3)}
 .scope-manual{color:var(--cyan);border-color:rgba(103,232,249,.2)}
 .scope-registry{color:var(--green);border-color:rgba(52,211,153,.2)}
 
@@ -2305,12 +2416,13 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
 }
 
 /* -- Models grid --------------------------------------------------------- */
-.models-grid{grid-template-columns:1.2fr 1.2fr 80px 90px 80px 120px;gap:0 6px}
+.models-grid{grid-template-columns:1.2fr 1.2fr 80px 90px 80px 160px;gap:0 6px}
 @media(max-width:700px){
-  .models-grid{grid-template-columns:1fr 80px 120px}
+  .models-grid{grid-template-columns:1fr 80px 160px}
   .models-grid .admin-col:nth-child(2),
   .models-grid .admin-col:nth-child(3),
   .models-grid .admin-col:nth-child(4){display:none}
+  .models-grid .admin-col:last-child{white-space:normal;display:flex;flex-wrap:wrap;gap:2px}
 }
 
 /* Model status indicators */
@@ -2339,7 +2451,7 @@ h3.skill-spec-heading { font-size: inherit; margin-block: 0; }
   .node-link, .dash-cell-node, .pagination button { transition: none; }
   .dash-row.has-link::after, .node-group-header::before { transition: none; }
   #new-ws-box select, #new-ws-box input, #new-ws-buttons button { transition: none; }
-  .admin-nav, .admin-row, .admin-btn-danger, .admin-btn-action { transition: none; }
+  .admin-nav, .admin-row, .admin-btn-danger, .admin-btn-action, .judge-section-btn { transition: none; }
   .settings-toggle-slider, .settings-toggle-slider::before { transition: none; }
   .settings-save-btn, .settings-reset-btn, .settings-docs-link, .settings-help-btn { transition: none; }
   .admin-sidebar, .admin-sidebar-backdrop { transition: none; }

turnstone/core/auth.py

@@ -1192,7 +1192,7 @@ async def handle_oidc_callback(request: Request, audience: str) -> Response:
                 jwks_data = await fetch_jwks(oidc_config.jwks_uri)
                 request.app.state.jwks_data = jwks_data
             except OIDCError:
-                pass
+                log.warning("JWKS fetch failed from %s", oidc_config.jwks_uri, exc_info=True)
         if jwks_data is None:
             return RedirectResponse("/?oidc_error=OIDC+temporarily+unavailable", status_code=302)
 

turnstone/core/config.py

@@ -133,10 +133,7 @@ _CONFIG_MAP: dict[str, dict[str, str]] = {
         "trusted_proxies": "ratelimit_trusted_proxies",
     },
     "health": {
-        "backend_probe_interval": "health_probe_interval",
-        "backend_probe_timeout": "health_probe_timeout",
-        "circuit_breaker_threshold": "circuit_breaker_threshold",
-        "circuit_breaker_cooldown": "circuit_breaker_cooldown",
+        "failure_threshold": "health_failure_threshold",
     },
     "database": {
         "backend": "db_backend",
@@ -151,9 +148,6 @@ _CONFIG_MAP: dict[str, dict[str, str]] = {
     "judge": {
         "enabled": "judge_enabled",
         "model": "judge_model",
-        "provider": "judge_provider",
-        "base_url": "judge_base_url",
-        "api_key": "judge_api_key",
         "confidence_threshold": "judge_confidence",
         "max_context_ratio": "judge_context_ratio",
         "timeout": "judge_timeout",

turnstone/core/config_store.py

@@ -54,6 +54,11 @@ class ConfigStore:
         self._version = 0
         self.reload()
 
+    @property
+    def storage(self) -> StorageBackend:
+        """Read-only access to the underlying storage backend."""
+        return self._storage
+
     @property
     def version(self) -> int:
         """Monotonic counter incremented on every cache update."""

turnstone/core/healthcheck.py

@@ -1,10 +1,13 @@
-"""Background LLM backend health monitor with circuit breaker."""
+"""Per-backend health tracking via passive success/failure recording.
+
+No active probing or circuit breakers — backends are marked *degraded*
+after a configurable number of consecutive failures and recover
+automatically when a request succeeds.
+"""
 
 from __future__ import annotations
 
-import enum
 import threading
-import time
 from typing import TYPE_CHECKING, Any
 
 from turnstone.core.log import get_logger
@@ -12,77 +15,39 @@ from turnstone.core.log import get_logger
 if TYPE_CHECKING:
     from collections.abc import Callable
 
-    from openai import OpenAI
-
 log = get_logger(__name__)
 
 
-class CircuitState(enum.Enum):
-    CLOSED = "closed"
-    OPEN = "open"
-    HALF_OPEN = "half_open"
+# ---------------------------------------------------------------------------
+# Per-backend health tracker
+# ---------------------------------------------------------------------------
 
 
-class BackendHealthMonitor:
-    """Monitors LLM backend health via periodic probes and passive failure tracking.
+class BackendHealthTracker:
+    """Tracks LLM backend health via passive success/failure recording.
 
-    Circuit breaker state machine:
-      CLOSED  -- backend responding, all requests pass
-      OPEN    -- backend unreachable, fast-fail for cooldown period
-      HALF_OPEN -- cooldown expired, next probe decides
+    State machine::
+
+        healthy  --(N consecutive failures)--> degraded
+        degraded --(any success)-------------> healthy
+
+    Requests are **never blocked** — the degraded flag is advisory
+    (used for observability and fallback ordering).
     """
 
     def __init__(
         self,
-        client: OpenAI,
-        probe_interval: float = 30.0,
-        probe_timeout: float = 5.0,
         failure_threshold: int = 5,
-        cooldown: float = 60.0,
-        *,
-        provider: str = "openai",
-        initial_model: str = "",
-        on_model_changed: Callable[[str, int | None], None] | None = None,
         on_state_changed: Callable[[str], None] | None = None,
     ) -> None:
-        self._client = client
-        self._probe_interval = probe_interval
-        self._probe_timeout = probe_timeout
         self._failure_threshold = failure_threshold
-        self._cooldown = cooldown
-
-        # Model change detection
-        self._provider = provider
-        self._last_detected_model = initial_model
-        self._on_model_changed = on_model_changed
         self._on_state_changed = on_state_changed
 
         self._lock = threading.Lock()
-        self._state = CircuitState.CLOSED
+        self._degraded = False
         self._consecutive_failures = 0
-        self._last_state_change = time.monotonic()
-        # Set True on OPEN→HALF_OPEN; consumed by first acquire_request_permit() call
-        self._half_open_permit = False
 
-        self._stop_event = threading.Event()
-        self._thread: threading.Thread | None = None
-
-    # ------------------------------------------------------------------
-    # Lifecycle
-    # ------------------------------------------------------------------
-
-    def start(self) -> None:
-        """Start background probe daemon thread."""
-        self._thread = threading.Thread(target=self._probe_loop, daemon=True)
-        self._thread.start()
-
-    def stop(self) -> None:
-        """Signal the probe thread to stop."""
-        self._stop_event.set()
-
-    # ------------------------------------------------------------------
-    # Passive tracking (called by request path)
-    # ------------------------------------------------------------------
+    # -- passive tracking ----------------------------------------------------
 
     def _fire_state_callback(self, state_val: str | None) -> None:
         """Fire on_state_changed callback outside the lock."""
@@ -93,188 +58,121 @@ class BackendHealthMonitor:
                 log.debug("on_state_changed callback error", exc_info=True)
 
     def record_success(self) -> None:
-        """Called on successful LLM call.  Resets failure count, closes circuit."""
+        """Called on successful LLM call. Clears degraded state."""
         state_to_dispatch: str | None = None
         with self._lock:
             self._consecutive_failures = 0
-            if self._state != CircuitState.CLOSED:
-                prev = self._state
-                self._state = CircuitState.CLOSED
-                self._half_open_permit = False
-                self._last_state_change = time.monotonic()
-                log.info("Circuit breaker CLOSED (was %s): backend recovered", prev.value)
-                self._update_metrics()
-                state_to_dispatch = self._state.value
+            if self._degraded:
+                self._degraded = False
+                log.info("Backend recovered (was degraded)")
+                state_to_dispatch = "healthy"
         self._fire_state_callback(state_to_dispatch)
 
     def record_failure(self) -> None:
-        """Called on LLM call failure.  May open circuit."""
+        """Called on LLM call failure. May mark backend as degraded."""
         state_to_dispatch: str | None = None
         with self._lock:
             self._consecutive_failures += 1
-            if self._state == CircuitState.HALF_OPEN:
-                # Probe failed in HALF_OPEN — re-open immediately
-                self._state = CircuitState.OPEN
-                self._half_open_permit = False
-                self._last_state_change = time.monotonic()
-                log.warning("Circuit breaker OPEN: probe failed in HALF_OPEN")
-                self._update_metrics()
-                state_to_dispatch = self._state.value
-            elif (
-                self._state == CircuitState.CLOSED
-                and self._consecutive_failures >= self._failure_threshold
-            ):
-                self._state = CircuitState.OPEN
-                self._last_state_change = time.monotonic()
+            if not self._degraded and self._consecutive_failures >= self._failure_threshold:
+                self._degraded = True
                 log.warning(
-                    "Circuit breaker OPEN: %d consecutive failures",
+                    "Backend degraded: %d consecutive failures",
                     self._consecutive_failures,
                 )
-                self._update_metrics()
-                state_to_dispatch = self._state.value
+                state_to_dispatch = "degraded"
         self._fire_state_callback(state_to_dispatch)
 
-    # ------------------------------------------------------------------
-    # Query helpers
-    # ------------------------------------------------------------------
+    # -- query helpers -------------------------------------------------------
 
     @property
     def is_healthy(self) -> bool:
         with self._lock:
-            return self._state == CircuitState.CLOSED
+            return not self._degraded
 
     @property
-    def circuit_state(self) -> CircuitState:
+    def is_degraded(self) -> bool:
         with self._lock:
-            return self._state
+            return self._degraded
 
-    def acquire_request_permit(self) -> bool:
-        """Consume one request permit if available.
-
-        Returns True when the caller may proceed.  In HALF_OPEN, only one probe
-        request is allowed — subsequent callers are blocked until the probe
-        completes (via ``record_success`` or ``record_failure``).
-        """
+    @property
+    def consecutive_failures(self) -> int:
         with self._lock:
-            if self._state == CircuitState.OPEN:
-                if (time.monotonic() - self._last_state_change) >= self._cooldown:
-                    self._state = CircuitState.HALF_OPEN
-                    self._half_open_permit = False  # consumed by this caller
-                    self._last_state_change = time.monotonic()
-                    log.info("Circuit breaker HALF_OPEN: cooldown elapsed, one probe permitted")
-                    self._update_metrics()
-                    return True  # this caller is the probe
-                return False
-            if self._state == CircuitState.HALF_OPEN:
-                # Only one probe request allowed; subsequent callers block
-                if self._half_open_permit:
-                    self._half_open_permit = False
-                    return True
-                return False
-            return True  # CLOSED
+            return self._consecutive_failures
 
-    # ------------------------------------------------------------------
-    # Background probe
-    # ------------------------------------------------------------------
 
-    def _probe_loop(self) -> None:
-        """Background: probe backend every interval.
+# ---------------------------------------------------------------------------
+# Per-backend health tracker registry
+# ---------------------------------------------------------------------------
 
-        An initial jitter (derived from the PID) staggers probes across
-        cluster nodes so they don't all hit the LLM backend at once.
+
+class HealthTrackerRegistry:
+    """Manages per-backend health trackers keyed by ``(provider, base_url)``.
+
+    Two model aliases that point at the same backend share a single
+    :class:`BackendHealthTracker`.  Aliases on different backends get
+    independent trackers.
+
+    Thread-safe.  Trackers are created eagerly at startup (or on model
+    reload) — never lazily from the request path.
+    """
+
+    def __init__(
+        self,
+        failure_threshold: int = 5,
+        on_state_changed: Callable[[str, str], None] | None = None,
+    ) -> None:
+        self._failure_threshold = failure_threshold
+        # callback(backend_key_str, state_value)
+        self._on_state_changed = on_state_changed
+        self._trackers: dict[tuple[str, str], BackendHealthTracker] = {}
+        self._lock = threading.Lock()
+
+    # -- key helpers ---------------------------------------------------------
+
+    @staticmethod
+    def backend_key(provider: str, base_url: str) -> tuple[str, str]:
+        """Normalize a ``(provider, base_url)`` pair for use as a dict key."""
+        return (provider, base_url.rstrip("/"))
+
+    # -- tracker lifecycle ---------------------------------------------------
+
+    def get_tracker(
+        self,
+        provider: str,
+        base_url: str,
+    ) -> BackendHealthTracker:
+        """Get or create a tracker for the given backend.  Thread-safe."""
+        key = self.backend_key(provider, base_url)
+        with self._lock:
+            if key not in self._trackers:
+                outer = self._on_state_changed
+
+                def _state_cb(state: str, _k: tuple[str, str] = key) -> None:
+                    if outer:
+                        outer(f"{_k[0]}:{_k[1]}", state)
+
+                tracker = BackendHealthTracker(
+                    failure_threshold=self._failure_threshold,
+                    on_state_changed=_state_cb,
+                )
+                self._trackers[key] = tracker
+                log.info("Health tracker created for backend %s:%s", key[0], key[1])
+            return self._trackers[key]
+
+    def get_tracker_for_alias(
+        self,
+        registry: Any,
+        alias: str,
+    ) -> BackendHealthTracker | None:
+        """Look up the tracker for a model alias, if one exists.
+
+        Returns ``None`` if the alias is unknown or no tracker has been
+        created for its backend yet.
         """
-        import os
-
-        # Deterministic per-process jitter: spread across half the interval
-        jitter = ((os.getpid() * 2654435761) & 0x7FFFFFFF) / 0x7FFFFFFF * (self._probe_interval / 2)
-        self._stop_event.wait(jitter)
-        while not self._stop_event.is_set():
-            self._stop_event.wait(self._probe_interval)
-            if self._stop_event.is_set():
-                break
-            # When circuit is OPEN, only probe after cooldown expires.
-            with self._lock:
-                if self._state == CircuitState.OPEN:
-                    elapsed = time.monotonic() - self._last_state_change
-                    remaining = self._cooldown - elapsed
-                    if remaining > 0:
-                        # Wait precisely for cooldown rather than skipping
-                        # a full probe_interval (which could overshoot).
-                        self._lock.release()
-                        try:
-                            self._stop_event.wait(remaining)
-                        finally:
-                            self._lock.acquire()
-                        if self._stop_event.is_set():
-                            break
-                    # Transition to HALF_OPEN for the probe.  The background
-                    # probe itself is the single HALF_OPEN request — keep
-                    # _half_open_permit False so concurrent user requests
-                    # are blocked until the probe completes.
-                    self._state = CircuitState.HALF_OPEN
-                    self._half_open_permit = False
-                    self._last_state_change = time.monotonic()
-                    log.info("Circuit breaker HALF_OPEN: cooldown elapsed, probing")
-                    self._update_metrics()
-            success = self._probe_once()
-            if success:
-                self.record_success()
-            else:
-                self.record_failure()
-
-    def _probe_once(self) -> bool:
-        """Single probe: call ``client.models.list()``.  Returns True on success."""
         try:
-            resp = self._client.with_options(timeout=self._probe_timeout).models.list()
-            self._check_model_change(resp)
-            return True
-        except Exception:
-            return False
-
-    def _check_model_change(self, resp: Any) -> None:
-        """Compare detected model against last known and fire callback if changed."""
-        if not self._on_model_changed or not resp.data:
-            return
-        try:
-            from turnstone.core.model_registry import (
-                _extract_context_window,
-                _select_best_model,
-            )
-
-            all_ids = [m.id for m in resp.data]
-            selected = _select_best_model(all_ids, self._provider)
-            if selected == self._last_detected_model:
-                return
-            model_obj = next((m for m in resp.data if m.id == selected), None)
-            ctx = _extract_context_window(model_obj, self._provider) if model_obj else None
-            log.info(
-                "Backend model changed: %s -> %s (ctx=%s)",
-                self._last_detected_model,
-                selected,
-                ctx,
-            )
-            self._last_detected_model = selected
-            self._on_model_changed(selected, ctx)
-        except Exception:
-            log.debug("Model change check failed", exc_info=True)
-
-    # ------------------------------------------------------------------
-    # Metrics
-    # ------------------------------------------------------------------
-
-    def _update_metrics(self) -> None:
-        """Push circuit-breaker state to metrics collector.
-
-        Called with *self._lock* held. State-change callbacks are dispatched
-        by the callers (``record_success`` / ``record_failure``) after the
-        lock is released, not by this method.
-        """
-        from turnstone.core.metrics import metrics
-
-        metrics.set_backend_status(self._state == CircuitState.CLOSED)
-        state_int = {
-            CircuitState.CLOSED: 0,
-            CircuitState.OPEN: 1,
-            CircuitState.HALF_OPEN: 2,
-        }
-        metrics.set_circuit_state(state_int[self._state])
+            cfg = registry.get_config(alias)
+        except (ValueError, KeyError):
+            return None
+        key = self.backend_key(cfg.provider, cfg.base_url)
+        with self._lock:
+            return self._trackers.get(key)

turnstone/core/judge.py

@@ -76,9 +76,6 @@ class JudgeConfig:
 
     enabled: bool = True
     model: str = ""  # empty = use session model
-    provider: str = ""  # empty = use session provider
-    base_url: str = ""
-    api_key: str = ""
     confidence_threshold: float = 0.7
     max_context_ratio: float = 0.5
     timeout: float = 60.0
@@ -687,6 +684,8 @@ def evaluate_heuristic(
     func_args: dict[str, object],
     approval_label: str,
     call_id: str = "",
+    *,
+    rules: list[_HeuristicRule] | tuple[Any, ...] | None = None,
 ) -> IntentVerdict:
     """Evaluate a tool call against the heuristic rule table.
 
@@ -701,6 +700,10 @@ def evaluate_heuristic(
         approval_label: Granular approval identifier (may differ from
             func_name for MCP tools).
         call_id: The tool call ID from the provider, used for correlation.
+        rules: Optional rule list override. When provided, these rules
+            are used instead of the built-in ``_HEURISTIC_RULES``.
+            Accepts both ``_HeuristicRule`` and ``HeuristicRuleDef``
+            instances (duck-typed on shared field names).
 
     Returns:
         An :class:`IntentVerdict` with tier ``"heuristic"``.
@@ -714,7 +717,7 @@ def evaluate_heuristic(
     except (TypeError, ValueError):
         func_args_json = str(func_args)
 
-    for rule in _HEURISTIC_RULES:
+    for rule in rules if rules is not None else _HEURISTIC_RULES:
         if _match_rule(rule, func_name, func_args, approval_label, arg_text):
             elapsed_ms = int((time.monotonic() - start) * 1000)
             return IntentVerdict(
@@ -893,40 +896,36 @@ class IntentJudge:
         session_client: Any,
         session_model: str,
         context_window: int = 200_000,
+        rule_registry: Any | None = None,
+        model_registry: Any | None = None,
     ) -> None:
         self._config = config
         self._context_window = context_window
+        self._rule_registry = rule_registry
 
-        # Resolve judge model: use config override or session model
-        if config.model and config.provider:
-            from turnstone.core.providers import create_client, create_provider
+        # Resolve judge model via ModelRegistry alias, falling back to session
+        resolved = False
+        if config.model and model_registry is not None:
+            try:
+                if model_registry.has_alias(config.model):
+                    client, model_name, _ = model_registry.resolve(config.model)
+                    self._provider = model_registry.get_provider(config.model)
+                    self._client = client
+                    self._model = model_name
+                    caps = self._provider.get_capabilities(self._model)
+                    self._judge_context_window = caps.context_window
+                    resolved = True
+            except Exception:
+                log.debug("Model alias resolution failed for %r, falling back", config.model)
 
-            self._provider = create_provider(config.provider)
-            self._client = create_client(
-                config.provider,
-                base_url=config.base_url
-                or (
-                    "https://api.openai.com/v1"
-                    if config.provider == "openai"
-                    else "https://api.anthropic.com"
-                ),
-                api_key=config.api_key
-                or os.environ.get(
-                    "OPENAI_API_KEY" if config.provider == "openai" else "ANTHROPIC_API_KEY",
-                    "",
-                ),
-            )
-            self._model = config.model
-            caps = self._provider.get_capabilities(self._model)
-            self._judge_context_window = caps.context_window
-        elif config.model:
-            # Model override but same provider
+        if not resolved and config.model:
+            # Model name override with session provider
             self._provider = session_provider
             self._client = session_client
             self._model = config.model
             caps = self._provider.get_capabilities(self._model)
             self._judge_context_window = caps.context_window
-        else:
+        elif not resolved:
             # Self-consistency: same model as session
             self._provider = session_provider
             self._client = session_client
@@ -971,7 +970,10 @@ class IntentJudge:
             approval_label = item.get("approval_label", func_name)
             call_id = item.get("call_id", item.get("tool_call_id", ""))
 
-            verdict = evaluate_heuristic(func_name, func_args, approval_label, call_id)
+            registry_rules = self._rule_registry.heuristic_rules if self._rule_registry else None
+            verdict = evaluate_heuristic(
+                func_name, func_args, approval_label, call_id, rules=registry_rules
+            )
             heuristic_verdicts.append(verdict)
 
         # Spawn daemon thread for LLM judge
@@ -1382,7 +1384,7 @@ class IntentJudge:
             confidence = float(data.get("confidence", 0.5))
             confidence = max(0.0, min(1.0, confidence))
         except (ValueError, TypeError):
-            pass
+            pass  # keeps default 0.5
 
         evidence = data.get("evidence", [])
         if isinstance(evidence, str):
@@ -1415,7 +1417,7 @@ class IntentJudge:
             if isinstance(data, dict):
                 return data
         except (json.JSONDecodeError, ValueError):
-            pass
+            pass  # falls through to strategy 2
 
         # Strategy 2: Markdown code block
         md_match = re.search(r"```(?:json)?\s*(\{.*?\})\s*```", text, re.DOTALL)
@@ -1425,7 +1427,7 @@ class IntentJudge:
                 if isinstance(data, dict):
                     return data
             except (json.JSONDecodeError, ValueError):
-                pass
+                pass  # falls through to strategy 3
 
         # Strategy 3: Find first { and matching }
         start = text.find("{")
@@ -1442,7 +1444,7 @@ class IntentJudge:
                             if isinstance(data, dict):
                                 return data
                         except (json.JSONDecodeError, ValueError):
-                            pass
+                            pass  # falls through to regex extraction
                         break
 
         # Strategy 4: Regex field extraction (last resort)

turnstone/core/mcp_client.py

@@ -35,7 +35,7 @@ if TYPE_CHECKING:
     from collections.abc import Callable
 
 import mcp.types as mcp_types
-from mcp import ClientSession, StdioServerParameters
+from mcp import ClientSession, McpError, StdioServerParameters
 from mcp.client.stdio import stdio_client
 from mcp.client.streamable_http import streamablehttp_client
 
@@ -67,7 +67,7 @@ def _mcp_to_openai(server_name: str, tool: Any) -> dict[str, Any]:
         "type": "function",
         "function": {
             "name": f"mcp__{server_name}__{tool.name}",
-            "description": f"[MCP: {server_name}] {description}",
+            "description": description,
             "parameters": input_schema,
         },
     }
@@ -151,6 +151,22 @@ class MCPClientManager:
         self._refresh_interval = refresh_interval
         self._refresh_task: asyncio.Task[None] | None = None
 
+        # Circuit breaker (per-server) — prevents repeated calls to broken servers
+        self._consecutive_failures: dict[str, int] = {}
+        self._circuit_open_until: dict[str, float] = {}  # monotonic timestamp
+        self._circuit_trip_count: dict[str, int] = {}  # backoff exponent
+
+        # Safe transport stream refs (pre-close before stack teardown to avoid
+        # the anyio cancel-scope CPU busy-loop — MCP SDK #2147)
+        self._server_streams: dict[str, tuple[Any, Any]] = {}
+
+        # Notification debounce (per-server)
+        self._last_notification_refresh: dict[str, float] = {}
+
+        # Periodic refresh backoff (per-server)
+        self._refresh_failures: dict[str, int] = {}
+        self._refresh_backoff_until: dict[str, float] = {}  # monotonic timestamp
+
     # -- lifecycle -----------------------------------------------------------
 
     def start(self) -> None:
@@ -181,6 +197,7 @@ class MCPClientManager:
             except Exception as exc:
                 log.warning("Failed to connect MCP server '%s'", name, exc_info=True)
                 self._set_error(name, f"{type(exc).__name__}: {exc}")
+                self._cb_record_failure(name)
 
         self._connected.set()
 
@@ -203,6 +220,94 @@ class MCPClientManager:
     _CONNECT_TIMEOUT = 30  # seconds — prevents hung connections on broken remotes
     _TCP_PROBE_TIMEOUT = 5  # seconds — fast TCP pre-flight for HTTP transports
 
+    # Circuit breaker constants
+    _CB_FAILURE_THRESHOLD = 3
+    _CB_BASE_COOLDOWN = 30.0  # seconds
+    _CB_MAX_COOLDOWN = 300.0  # 5 minutes
+
+    # Notification debounce
+    _NOTIFICATION_DEBOUNCE = 5.0  # seconds between refreshes per server
+
+    # Periodic refresh backoff
+    _REFRESH_BACKOFF_BASE = 60.0  # seconds
+    _REFRESH_BACKOFF_MAX = 3600.0  # 1 hour
+
+    # -- circuit breaker (per-server) -----------------------------------------
+
+    def _cb_check(self, name: str) -> tuple[bool, bool]:
+        """Check circuit breaker state for *name*.
+
+        Returns ``(is_open, cooldown_expired)``.  When the circuit is closed
+        both values are False.  When open, *cooldown_expired* indicates
+        whether a probe attempt is allowed.
+        """
+        deadline = self._circuit_open_until.get(name)
+        if deadline is None:
+            return False, False
+        now = time.monotonic()
+        if now >= deadline:
+            return True, True  # half-open: allow one probe
+        return True, False  # still in cooldown
+
+    def _cb_record_failure(self, name: str) -> None:
+        """Record a failure against *name*, potentially opening the circuit."""
+        count = self._consecutive_failures.get(name, 0) + 1
+        self._consecutive_failures[name] = count
+        # Guard: don't extend an already-open deadline.  Additional failures
+        # while open still accumulate in _consecutive_failures, so the circuit
+        # re-opens immediately after the next half-open probe fails (count is
+        # already >= threshold).
+        if count >= self._CB_FAILURE_THRESHOLD and name not in self._circuit_open_until:
+            trips = self._circuit_trip_count.get(name, 0)
+            cooldown = min(self._CB_BASE_COOLDOWN * (2**trips), self._CB_MAX_COOLDOWN)
+            # Per-server jitter seeded from server name (varies across process
+            # restarts via PYTHONHASHSEED, which is desirable — each cluster
+            # node gets different jitter to avoid thundering herd).
+            jitter = random.Random(hash(name)).random() * cooldown * 0.1
+            self._circuit_open_until[name] = time.monotonic() + cooldown + jitter
+            self._circuit_trip_count[name] = trips + 1
+            log.warning(
+                "MCP circuit open for '%s': %d consecutive failures, cooldown %.0fs",
+                name,
+                count,
+                cooldown + jitter,
+            )
+
+    def _cb_record_success(self, name: str) -> None:
+        """Record a successful operation for *name*, decaying circuit state.
+
+        Decays trip count by 1 rather than resetting to 0, so a chronically
+        flapping server escalates its backoff over time instead of always
+        restarting at the minimum cooldown.
+        """
+        self._consecutive_failures.pop(name, None)
+        self._circuit_open_until.pop(name, None)
+        trips = self._circuit_trip_count.get(name, 0)
+        if trips > 1:
+            self._circuit_trip_count[name] = trips - 1
+        else:
+            self._circuit_trip_count.pop(name, None)
+
+    def _cb_clear(self, name: str) -> None:
+        """Remove all circuit breaker state for *name*."""
+        self._consecutive_failures.pop(name, None)
+        self._circuit_open_until.pop(name, None)
+        self._circuit_trip_count.pop(name, None)
+
+    # -- safe transport helpers ------------------------------------------------
+
+    async def _pre_close_streams(self, name: str) -> None:
+        """Close MCP transport streams before stack teardown.
+
+        Pre-closing unblocks anyio transport tasks stuck on zero-buffer
+        ``send()`` calls, preventing the CPU busy-loop from SDK #2147.
+        """
+        streams = self._server_streams.pop(name, None)
+        if streams:
+            for s in streams:
+                with contextlib.suppress(Exception):
+                    await s.aclose()
+
     async def _tcp_probe(self, name: str, url: str) -> None:
         """Fast TCP connect check before entering the MCP transport context.
 
@@ -251,6 +356,16 @@ class MCPClientManager:
             log.error("MCP server name '%s' contains '__' (reserved delimiter), skipping", name)
             return
 
+        # Guard: tear down stale session/stack so we don't leak.  Checks both
+        # _sessions and _per_server_stacks because transport errors in the sync
+        # dispatch methods evict the session but leave the stack behind.
+        if name in self._sessions or name in self._per_server_stacks:
+            self._sessions.pop(name, None)
+            await self._pre_close_streams(name)
+            old_stack = self._per_server_stacks.pop(name, None)
+            if old_stack:
+                await self._safe_close_stack(old_stack)
+
         # Per-server exit stack for clean per-server lifecycle management
         stack = AsyncExitStack()
         await stack.__aenter__()
@@ -271,6 +386,9 @@ class MCPClientManager:
                     ),
                     timeout=self._CONNECT_TIMEOUT,
                 )
+                # Stash stream refs so _pre_close_streams can unblock anyio
+                # transport tasks before the cancel scope fires (SDK #2147).
+                self._server_streams[name] = (read, write)
             else:
                 # Default: stdio transport
                 command = cfg.get("command", "")
@@ -287,24 +405,29 @@ class MCPClientManager:
                     env=env,
                 )
                 read, write = await stack.enter_async_context(stdio_client(params))
+                self._server_streams[name] = (read, write)
         except asyncio.CancelledError:
-            # Stray CancelledError from broken anyio cancel scope — treat as
+            # Stray CancelledError from broken anyio cancel scope -- treat as
             # connection failure.  But if the task is genuinely being cancelled
             # (shutdown), re-raise so we don't block teardown.
             task = asyncio.current_task()
             if task is not None and task.cancelling():
+                await self._pre_close_streams(name)
                 await self._safe_close_stack(stack)
                 raise
             log.warning("MCP server '%s' connection failed (anyio cancel)", name)
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise TimeoutError(f"Connection failed for '{name}'") from None
         except TimeoutError:
             log.warning(
                 "MCP server '%s' connection timed out after %ds", name, self._CONNECT_TIMEOUT
             )
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise TimeoutError(f"Connection timed out after {self._CONNECT_TIMEOUT}s") from None
         except Exception:
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise
 
@@ -316,15 +439,30 @@ class MCPClientManager:
             if not isinstance(msg, mcp_types.ServerNotification):
                 return
             root = msg.root
+
+            # Debounce: skip if we refreshed this server very recently
+            now = time.monotonic()
+            last = self._last_notification_refresh.get(name, 0.0)
+            if now - last < self._NOTIFICATION_DEBOUNCE:
+                log.debug(
+                    "Debouncing notification from '%s' (%.1fs since last refresh)",
+                    name,
+                    now - last,
+                )
+                return
+
             try:
                 if isinstance(root, mcp_types.ToolListChangedNotification):
                     log.info("Received tools/list_changed from '%s'", name)
+                    self._last_notification_refresh[name] = now
                     await self._refresh_server_tools(name)
                 elif isinstance(root, mcp_types.ResourceListChangedNotification):
                     log.info("Received resources/list_changed from '%s'", name)
+                    self._last_notification_refresh[name] = now
                     await self._refresh_server_resources(name)
                 elif isinstance(root, mcp_types.PromptListChangedNotification):
                     log.info("Received prompts/list_changed from '%s'", name)
+                    self._last_notification_refresh[name] = now
                     await self._refresh_server_prompts(name)
                 self._last_error.pop(name, None)
             except Exception as exc:
@@ -336,6 +474,7 @@ class MCPClientManager:
                 ClientSession(read, write, message_handler=_on_notification)  # type: ignore[arg-type]
             )
         except Exception:
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise
 
@@ -346,16 +485,20 @@ class MCPClientManager:
             self._per_server_stacks.pop(name, None)
             task = asyncio.current_task()
             if task is not None and task.cancelling():
+                await self._pre_close_streams(name)
                 await self._safe_close_stack(stack)
                 raise
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise TimeoutError(f"MCP handshake failed for '{name}'") from None
         except TimeoutError:
             self._per_server_stacks.pop(name, None)
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise TimeoutError(f"MCP handshake timed out after {self._CONNECT_TIMEOUT}s") from None
         except Exception:
             self._per_server_stacks.pop(name, None)
+            await self._pre_close_streams(name)
             await self._safe_close_stack(stack)
             raise
         self._sessions[name] = session
@@ -548,12 +691,14 @@ class MCPClientManager:
                     if cfg:
                         log.info("Reconnecting MCP server '%s'", name)
                         await self._connect_one(name, cfg)
+                        self._cb_record_success(name)
                         new_names = [
                             t["function"]["name"] for t in self._per_server_tools.get(name, [])
                         ]
                         results[name] = (new_names, [])
                     continue
                 added, removed = await self._refresh_server(name)
+                self._cb_record_success(name)
                 results[name] = (added, removed)
             except Exception as exc:
                 log.warning("Refresh failed for MCP server '%s'", name, exc_info=True)
@@ -577,10 +722,18 @@ class MCPClientManager:
         """
         assert self._loop is not None
         future = asyncio.run_coroutine_threadsafe(self._refresh_all(server_name), self._loop)
-        return future.result(timeout=timeout)
+        try:
+            return future.result(timeout=timeout)
+        except concurrent.futures.TimeoutError:
+            future.cancel()
+            raise TimeoutError(f"MCP refresh timed out after {timeout}s") from None
 
     async def _periodic_refresh(self) -> None:
-        """Periodically refresh servers that lack push notifications."""
+        """Periodically refresh servers that lack push notifications.
+
+        Applies per-server exponential backoff on failure and attempts
+        reconnection for disconnected servers.
+        """
         # Stagger start using a launch-time seed so cluster nodes don't
         # all hit MCP servers simultaneously.
         seed = random.Random(time.monotonic_ns() ^ os.getpid()).random()
@@ -588,8 +741,42 @@ class MCPClientManager:
         await asyncio.sleep(initial_delay)
         while True:
             for name in list(self._server_configs):
+                now = time.monotonic()
+
+                # Check per-server backoff
+                backoff_until = self._refresh_backoff_until.get(name, 0.0)
+                if now < backoff_until:
+                    continue  # still in backoff
+
                 if name not in self._sessions:
-                    continue  # not connected — skip (reconnect on manual refresh)
+                    # Attempt reconnection for disconnected servers
+                    cfg = self._server_configs.get(name)
+                    if cfg:
+                        try:
+                            log.info("Periodic reconnect attempt for '%s'", name)
+                            await self._connect_one(name, cfg)
+                            self._refresh_failures.pop(name, None)
+                            self._refresh_backoff_until.pop(name, None)
+                            self._cb_record_success(name)
+                        except asyncio.CancelledError:
+                            raise
+                        except Exception as exc:
+                            failures = self._refresh_failures.get(name, 0) + 1
+                            self._refresh_failures[name] = failures
+                            backoff = min(
+                                self._REFRESH_BACKOFF_BASE * (2 ** (failures - 1)),
+                                self._REFRESH_BACKOFF_MAX,
+                            )
+                            self._refresh_backoff_until[name] = time.monotonic() + backoff
+                            log.warning(
+                                "Periodic reconnect failed for '%s' (attempt %d, backoff %.0fs)",
+                                name,
+                                failures,
+                                backoff,
+                            )
+                            self._set_error(name, f"Reconnect failed: {exc}")
+                    continue
+
                 try:
                     if not self._supports_list_changed.get(name, False):
                         await self._refresh_server_tools(name)
@@ -598,9 +785,26 @@ class MCPClientManager:
                     if not self._supports_prompt_list_changed.get(name, False):
                         await self._refresh_server_prompts(name)
                     self._last_error.pop(name, None)
+                    self._refresh_failures.pop(name, None)
+                    self._refresh_backoff_until.pop(name, None)
                 except Exception as exc:
-                    log.warning("Periodic refresh failed for '%s'", name, exc_info=True)
+                    failures = self._refresh_failures.get(name, 0) + 1
+                    self._refresh_failures[name] = failures
+                    backoff = min(
+                        self._REFRESH_BACKOFF_BASE * (2 ** (failures - 1)),
+                        self._REFRESH_BACKOFF_MAX,
+                    )
+                    self._refresh_backoff_until[name] = time.monotonic() + backoff
+                    log.warning(
+                        "Periodic refresh failed for '%s' (attempt %d, backoff %.0fs)",
+                        name,
+                        failures,
+                        backoff,
+                    )
                     self._set_error(name, f"Periodic refresh failed: {exc}")
+            # Note: per-server backoff (max 1h) is only meaningful when
+            # refresh_interval is shorter than _REFRESH_BACKOFF_MAX.  With
+            # the default 4h interval this sleep already bounds retry frequency.
             await asyncio.sleep(self._refresh_interval)
 
     # -- resource refresh ----------------------------------------------------
@@ -940,6 +1144,9 @@ class MCPClientManager:
         if self._loop and self._per_server_stacks:
 
             async def _close_all_stacks() -> None:
+                # Pre-close streams to prevent anyio CPU busy-loop during teardown
+                for srv_name in list(self._server_streams):
+                    await self._pre_close_streams(srv_name)
                 for stack in self._per_server_stacks.values():
                     await self._safe_close_stack(stack)
 
@@ -985,6 +1192,14 @@ class MCPClientManager:
         self._listeners.clear()
         self._resource_listeners.clear()
         self._prompt_listeners.clear()
+        # Clear resilience state
+        self._consecutive_failures.clear()
+        self._circuit_open_until.clear()
+        self._circuit_trip_count.clear()
+        self._server_streams.clear()
+        self._last_notification_refresh.clear()
+        self._refresh_failures.clear()
+        self._refresh_backoff_until.clear()
 
         log.info("MCP client shut down")
 
@@ -1049,6 +1264,7 @@ class MCPClientManager:
             async def _remove() -> None:
                 # Close session + transport via per-server stack
                 self._sessions.pop(name, None)
+                await self._pre_close_streams(name)
                 stack = self._per_server_stacks.pop(name, None)
                 if stack is not None:
                     await self._safe_close_stack(stack)
@@ -1062,6 +1278,10 @@ class MCPClientManager:
                 self._supports_prompts.pop(name, None)
                 self._supports_prompt_list_changed.pop(name, None)
                 self._last_error.pop(name, None)
+                self._last_notification_refresh.pop(name, None)
+                self._refresh_failures.pop(name, None)
+                self._refresh_backoff_until.pop(name, None)
+                self._cb_clear(name)
                 # Rebuild merged state (serialized with notification handlers)
                 self._rebuild_tools()
                 self._rebuild_resources()
@@ -1075,6 +1295,7 @@ class MCPClientManager:
         else:
             # No event loop (tests / pre-start) — mutate directly
             self._sessions.pop(name, None)
+            self._server_streams.pop(name, None)
             self._per_server_tools.pop(name, None)
             self._per_server_resources.pop(name, None)
             self._per_server_prompts.pop(name, None)
@@ -1084,6 +1305,10 @@ class MCPClientManager:
             self._supports_prompts.pop(name, None)
             self._supports_prompt_list_changed.pop(name, None)
             self._last_error.pop(name, None)
+            self._last_notification_refresh.pop(name, None)
+            self._refresh_failures.pop(name, None)
+            self._refresh_backoff_until.pop(name, None)
+            self._cb_clear(name)
             self._rebuild_tools()
             self._rebuild_resources()
             self._rebuild_prompts()
@@ -1107,6 +1332,8 @@ class MCPClientManager:
         connected = name in self._sessions
         cfg = self._server_configs.get(name, {})
         transport = cfg.get("type", "stdio")
+        cb_deadline = self._circuit_open_until.get(name)
+        cb_open = cb_deadline is not None and time.monotonic() < cb_deadline
         return {
             "connected": connected,
             "tools": len(self._per_server_tools.get(name, [])) if connected else 0,
@@ -1116,6 +1343,8 @@ class MCPClientManager:
             "transport": transport,
             "command": cfg.get("command", "") if transport == "stdio" else "",
             "url": cfg.get("url", "") if transport != "stdio" else "",
+            "circuit_open": cb_open,
+            "consecutive_failures": self._consecutive_failures.get(name, 0),
         }
 
     def get_all_server_status(self) -> dict[str, dict[str, Any]]:
@@ -1245,6 +1474,55 @@ class MCPClientManager:
 
     # -- tool invocation -----------------------------------------------------
 
+    def _cb_gate(self, server_name: str) -> None:
+        """Check circuit breaker before dispatching to *server_name*.
+
+        Raises ``RuntimeError`` if the circuit is open and cooldown has not
+        expired.  When the cooldown has expired (half-open), clears the
+        deadline so the probe attempt is allowed through.
+        """
+        is_open, cooldown_expired = self._cb_check(server_name)
+        if is_open and not cooldown_expired:
+            remaining = self._circuit_open_until.get(server_name, 0) - time.monotonic()
+            raise RuntimeError(
+                f"MCP server '{server_name}' circuit open "
+                f"(cooldown {remaining:.0f}s remaining). "
+                f"Use '/mcp refresh {server_name}' to retry manually."
+            )
+        if cooldown_expired:
+            # Remove deadline so concurrent callers aren't rejected while the
+            # probe is in-flight.  This intentionally allows multiple callers
+            # through rather than a single probe: reconnects serialize on the
+            # event loop via _connect_one's guard, and if the server is truly
+            # broken the first failure re-trips the circuit immediately.
+            self._circuit_open_until.pop(server_name, None)
+
+    def _cb_auto_reconnect(self, server_name: str) -> Any:
+        """Attempt reconnection for a disconnected server during half-open probe.
+
+        Returns the new session on success, or raises on failure.
+        """
+        cfg = self._server_configs.get(server_name)
+        if not cfg or self._loop is None:
+            raise RuntimeError(f"MCP server '{server_name}' is not connected")
+        reconnect_future = asyncio.run_coroutine_threadsafe(
+            self._connect_one(server_name, cfg), self._loop
+        )
+        try:
+            reconnect_future.result(timeout=self._CONNECT_TIMEOUT)
+        except concurrent.futures.TimeoutError:
+            reconnect_future.cancel()
+            self._cb_record_failure(server_name)
+            raise RuntimeError(f"MCP server '{server_name}' reconnect timed out") from None
+        except Exception as exc:
+            self._cb_record_failure(server_name)
+            raise RuntimeError(f"MCP server '{server_name}' reconnect failed: {exc}") from None
+        session = self._sessions.get(server_name)
+        if session is None:
+            self._cb_record_failure(server_name)
+            raise RuntimeError(f"MCP server '{server_name}' reconnect produced no session")
+        return session
+
     def call_tool_sync(
         self,
         func_name: str,
@@ -1254,15 +1532,19 @@ class MCPClientManager:
         """Execute an MCP tool call synchronously (blocks the calling thread).
 
         Dispatches an async ``tools/call`` to the background event loop and
-        waits for the result.
+        waits for the result.  Includes circuit-breaker gating and automatic
+        reconnection for servers recovering from failure.
         """
         mapping = self._tool_map.get(func_name)
         if mapping is None:
             raise ValueError(f"Unknown MCP tool: {func_name}")
         server_name, original_name = mapping
+
+        self._cb_gate(server_name)
+
         session = self._sessions.get(server_name)
         if session is None:
-            raise RuntimeError(f"MCP server '{server_name}' is not connected")
+            session = self._cb_auto_reconnect(server_name)
         assert self._loop is not None
 
         future = asyncio.run_coroutine_threadsafe(
@@ -1271,7 +1553,19 @@ class MCPClientManager:
         try:
             result = future.result(timeout=timeout)
         except concurrent.futures.TimeoutError:
+            future.cancel()
+            self._cb_record_failure(server_name)
             raise TimeoutError(f"MCP tool call timed out after {timeout}s") from None
+        except Exception as exc:
+            # Protocol errors (McpError) come from a healthy connection that
+            # rejected the request — only transport errors trip the breaker.
+            if not isinstance(exc, McpError):
+                self._cb_record_failure(server_name)
+            if isinstance(exc, (BrokenPipeError, ConnectionResetError, EOFError)):
+                self._sessions.pop(server_name, None)
+            raise
+
+        self._cb_record_success(server_name)
 
         # Extract text from the content array
         texts: list[str] = []
@@ -1320,16 +1614,29 @@ class MCPClientManager:
         if mapping is None:
             raise ValueError(f"Unknown MCP resource: {uri}")
         server_name, _ = mapping
+
+        self._cb_gate(server_name)
+
         session = self._sessions.get(server_name)
         if session is None:
-            raise RuntimeError(f"MCP server '{server_name}' is not connected")
+            session = self._cb_auto_reconnect(server_name)
         assert self._loop is not None
 
         future = asyncio.run_coroutine_threadsafe(session.read_resource(uri), self._loop)
         try:
             result = future.result(timeout=timeout)
         except concurrent.futures.TimeoutError:
+            future.cancel()
+            self._cb_record_failure(server_name)
             raise TimeoutError(f"MCP resource read timed out after {timeout}s") from None
+        except Exception as exc:
+            if not isinstance(exc, McpError):
+                self._cb_record_failure(server_name)
+            if isinstance(exc, (BrokenPipeError, ConnectionResetError, EOFError)):
+                self._sessions.pop(server_name, None)
+            raise
+
+        self._cb_record_success(server_name)
 
         parts: list[str] = []
         for item in result.contents:
@@ -1357,9 +1664,12 @@ class MCPClientManager:
         if mapping is None:
             raise ValueError(f"Unknown MCP prompt: {prefixed_name}")
         server_name, original_name = mapping
+
+        self._cb_gate(server_name)
+
         session = self._sessions.get(server_name)
         if session is None:
-            raise RuntimeError(f"MCP server '{server_name}' is not connected")
+            session = self._cb_auto_reconnect(server_name)
         assert self._loop is not None
 
         future = asyncio.run_coroutine_threadsafe(
@@ -1368,7 +1678,17 @@ class MCPClientManager:
         try:
             result = future.result(timeout=timeout)
         except concurrent.futures.TimeoutError:
+            future.cancel()
+            self._cb_record_failure(server_name)
             raise TimeoutError(f"MCP prompt retrieval timed out after {timeout}s") from None
+        except Exception as exc:
+            if not isinstance(exc, McpError):
+                self._cb_record_failure(server_name)
+            if isinstance(exc, (BrokenPipeError, ConnectionResetError, EOFError)):
+                self._sessions.pop(server_name, None)
+            raise
+
+        self._cb_record_success(server_name)
 
         messages: list[dict[str, Any]] = []
         for msg in result.messages:

turnstone/core/metrics.py

@@ -29,7 +29,6 @@ class MetricsCollector:
         self._context_ratio: float = 0.0
         self._sse_connections: int = 0  # gauge: active SSE connections
         self._backend_up: bool = True  # gauge: 1 if up, 0 if down
-        self._circuit_state: int = 0  # gauge: 0=closed, 1=open, 2=half_open
         # counters (continued)
         self._ratelimit_rejects: int = 0  # counter: total 429 responses
         self._evictions: int = 0  # counter: workstreams evicted
@@ -101,11 +100,6 @@ class MetricsCollector:
         with self._lock:
             self._backend_up = up
 
-    def set_circuit_state(self, state: int) -> None:
-        """0=closed, 1=open, 2=half_open."""
-        with self._lock:
-            self._circuit_state = state
-
     def record_eviction(self) -> None:
         with self._lock:
             self._evictions += 1
@@ -172,7 +166,6 @@ class MetricsCollector:
             sse_connections = self._sse_connections
             ratelimit_rejects = self._ratelimit_rejects
             backend_up = self._backend_up
-            circuit_state = self._circuit_state
             evictions = self._evictions
             judge_verdicts = dict(self._judge_verdicts)
             judge_latency = dict(self._judge_latency)
@@ -277,13 +270,6 @@ class MetricsCollector:
             1 if backend_up else 0,
         )
 
-        # turnstone_circuit_state
-        gauge(
-            "turnstone_circuit_state",
-            "Circuit breaker state (0=closed, 1=open, 2=half_open)",
-            circuit_state,
-        )
-
         # turnstone_workstreams_evicted_total
         counter(
             "turnstone_workstreams_evicted_total",

turnstone/core/model_registry.py

@@ -199,10 +199,22 @@ def _resolve_env_vars(value: str) -> str:
     return re.sub(r"\$\{([A-Za-z_][A-Za-z0-9_]*)\}", _replace, value)
 
 
+def _resolve_openai_provider(provider: str, base_url: str) -> str:
+    """Distinguish commercial OpenAI from local OpenAI-compatible servers.
+
+    When ``provider`` is ``"openai"`` but the ``base_url`` does not point to
+    ``api.openai.com``, the model is on a local server (vLLM, llama.cpp, etc.)
+    and should use the Chat Completions provider (``"openai-compatible"``).
+    """
+    if provider == "openai" and base_url and "api.openai.com" not in base_url:
+        return "openai-compatible"
+    return provider
+
+
 def load_model_registry(
-    base_url: str,
-    api_key: str,
-    model: str,
+    base_url: str = "",
+    api_key: str = "",
+    model: str = "",
     context_window: int = 32768,
     provider: str = "openai",
     storage: Any | None = None,
@@ -241,15 +253,16 @@ def load_model_registry(
                         if isinstance(parsed, dict):
                             caps = parsed
                     except (_json.JSONDecodeError, TypeError):
-                        pass
-                row_provider = row.get("provider", "openai")
+                        pass  # falls back to empty capabilities
+                row_base_url = _resolve_env_vars(row.get("base_url", ""))
+                row_provider = _resolve_openai_provider(row.get("provider", "openai"), row_base_url)
                 row_model = row["model"]
                 # 0 = auto-detect: inherit CLI-detected context_window,
                 # same fallback chain as config.toml models
                 row_ctx = row.get("context_window", 0) or context_window
                 configs[alias] = ModelConfig(
                     alias=alias,
-                    base_url=_resolve_env_vars(row.get("base_url", "")),
+                    base_url=row_base_url,
                     api_key=_resolve_env_vars(row.get("api_key", "")),
                     model=row_model,
                     context_window=row_ctx,
@@ -268,13 +281,14 @@ def load_model_registry(
         if not model_name:
             log.warning("Model entry '%s' has no model name, skipping", alias)
             continue
+        entry_base_url = _resolve_env_vars(entry.get("base_url", base_url))
         configs[alias] = ModelConfig(
             alias=alias,
-            base_url=entry.get("base_url", base_url),
-            api_key=entry.get("api_key", api_key),
+            base_url=entry_base_url,
+            api_key=_resolve_env_vars(entry.get("api_key", api_key)),
             model=model_name,
             context_window=entry.get("context_window", context_window),
-            provider=entry.get("provider", "openai"),
+            provider=_resolve_openai_provider(entry.get("provider", "openai"), entry_base_url),
             capabilities=entry.get("capabilities", {})
             if isinstance(entry.get("capabilities"), dict)
             else {},
@@ -282,22 +296,36 @@ def load_model_registry(
         )
 
     # 3. Ensure a "default" entry from CLI args (only if not already defined
-    # by config.toml or DB — those take precedence)
-    if "default" not in configs:
+    # by config.toml or DB — those take precedence, and only when a CLI
+    # model was actually provided)
+    if "default" not in configs and model:
         configs["default"] = ModelConfig(
             alias="default",
             base_url=base_url,
             api_key=api_key,
             model=model,
             context_window=context_window,
-            provider=provider,
+            provider=_resolve_openai_provider(provider, base_url),
+        )
+
+    if not configs:
+        raise ValueError(
+            "No model definitions found. Provide --model, configure [models.*] "
+            "in config.toml, or add model definitions in the admin panel."
         )
 
     # Determine default alias
     default_alias = model_section.get("default", "default")
     if default_alias not in configs:
-        log.warning("Configured default model '%s' not found, using 'default'", default_alias)
-        default_alias = "default"
+        if "default" in configs:
+            default_alias = "default"
+        else:
+            default_alias = next(iter(configs))
+            log.info(
+                "No '%s' model alias; using '%s' as default",
+                model_section.get("default", "default"),
+                default_alias,
+            )
 
     # Fallback chain
     fallback_raw = model_section.get("fallback", [])
@@ -546,7 +574,11 @@ def _detect_openai_compat(
             result["context_window"] = known["context_window"]
 
     # Server type heuristics
-    if base_url and "api.openai.com" in base_url:
+    from urllib.parse import urlparse
+
+    _normalized = (base_url if "://" in base_url else f"https://{base_url}") if base_url else ""
+    _hostname = urlparse(_normalized).hostname or "" if _normalized else ""
+    if base_url and (_hostname == "api.openai.com" or _hostname.endswith(".openai.com")):
         result["server_type"] = "openai"
     elif meta is not None and "n_ctx_train" in meta:
         result["server_type"] = "llama.cpp"

turnstone/core/output_guard.py

@@ -17,7 +17,10 @@ from __future__ import annotations
 import re
 import time
 from dataclasses import dataclass, field
-from typing import Any
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from collections.abc import Mapping
 
 # -- Priority 1: Prompt injection markers (HIGH) ---------------------------
 
@@ -168,6 +171,225 @@ def _clean() -> OutputAssessment:
     return OutputAssessment()
 
 
+@dataclass(frozen=True)
+class OutputGuardPatternDef:
+    """A pattern definition for output guard scanning."""
+
+    name: str
+    category: str  # prompt_injection/credentials/encoded_payloads/adversarial_urls/info_disclosure
+    risk_level: str  # high/medium/low
+    compiled: re.Pattern[str]  # pre-compiled regex
+    flag_name: str  # e.g. "prompt_injection", "credential_leak"
+    annotation: str  # human-readable message
+    is_credential: bool = False  # triggers redaction
+    redact_label: str = ""  # e.g. "api_key"
+    priority: int = 0  # order within category (higher = first)
+
+
+# -- Built-in pattern definitions (consumed by rule_registry.RuleRegistry) ---
+
+_BUILTIN_OG_PATTERNS: list[OutputGuardPatternDef] = [
+    # -- prompt_injection (priority 1, high) --
+    OutputGuardPatternDef(
+        name="override_phrases",
+        category="prompt_injection",
+        risk_level="high",
+        compiled=_RE_OVERRIDE_PHRASES,
+        flag_name="prompt_injection",
+        annotation="Output contains phrases that attempt to override agent instructions.",
+        priority=40,
+    ),
+    OutputGuardPatternDef(
+        name="role_injection",
+        category="prompt_injection",
+        risk_level="high",
+        compiled=_RE_ROLE_INJECTION,
+        flag_name="role_injection",
+        annotation="Output contains role/message injection markers.",
+        priority=30,
+    ),
+    OutputGuardPatternDef(
+        name="instruction_override",
+        category="prompt_injection",
+        risk_level="high",
+        compiled=_RE_INSTRUCTION_OVERRIDE,
+        flag_name="instruction_override",
+        annotation="Output contains instruction-override keywords (MANDATORY, OVERRIDE, etc.).",
+        priority=20,
+    ),
+    OutputGuardPatternDef(
+        name="meta_injection",
+        category="prompt_injection",
+        risk_level="high",
+        compiled=_RE_META_INJECTION,
+        flag_name="meta_injection",
+        annotation="Output attempts to redefine the agent's identity or persona.",
+        priority=10,
+    ),
+    # -- credentials (priority 2, high) --
+    OutputGuardPatternDef(
+        name="credential_sk_proj",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"sk-proj-[a-zA-Z0-9\-]{20,}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=90,
+    ),
+    OutputGuardPatternDef(
+        name="credential_sk",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"sk-[a-zA-Z0-9]{20,}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=80,
+    ),
+    OutputGuardPatternDef(
+        name="credential_ghp",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"ghp_[a-zA-Z0-9]{36}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=70,
+    ),
+    OutputGuardPatternDef(
+        name="credential_gho",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"gho_[a-zA-Z0-9]{36}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=60,
+    ),
+    OutputGuardPatternDef(
+        name="credential_akia",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"AKIA[0-9A-Z]{16}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=50,
+    ),
+    OutputGuardPatternDef(
+        name="credential_aiza",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"AIza[a-zA-Z0-9_\-]{35}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=40,
+    ),
+    OutputGuardPatternDef(
+        name="credential_bearer",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"Bearer\s+[a-zA-Z0-9._~+/=\-]{20,}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=30,
+    ),
+    OutputGuardPatternDef(
+        name="credential_token_param",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"token=[a-zA-Z0-9]{20,}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=20,
+    ),
+    OutputGuardPatternDef(
+        name="credential_key_param",
+        category="credentials",
+        risk_level="high",
+        compiled=re.compile(r"key=[a-zA-Z0-9]{20,}"),
+        flag_name="credential_leak",
+        annotation="Output contains what appears to be an API key or token.",
+        is_credential=True,
+        redact_label="api_key",
+        priority=10,
+    ),
+    # NOTE: private_key_block and connection_string are NOT in _BUILTIN_OG_PATTERNS
+    # because they require custom redaction logic (preserve protocol/username in
+    # connection strings, match PEM block boundaries).  They are handled by
+    # _check_credentials_complex() instead.
+    # -- encoded_payloads (priority 3, medium) --
+    OutputGuardPatternDef(
+        name="script_data_uri",
+        category="encoded_payloads",
+        risk_level="medium",
+        compiled=_RE_SCRIPT_DATA_URI,
+        flag_name="script_data_uri",
+        annotation="Output contains a data URI with executable content.",
+        priority=30,
+    ),
+    OutputGuardPatternDef(
+        name="hex_shellcode",
+        category="encoded_payloads",
+        risk_level="medium",
+        compiled=_RE_HEX_SHELLCODE,
+        flag_name="hex_shellcode",
+        annotation="Output contains hex-encoded byte sequences resembling shellcode.",
+        priority=20,
+    ),
+    # -- adversarial_urls (priority 4, medium) --
+    OutputGuardPatternDef(
+        name="url_cred_param",
+        category="adversarial_urls",
+        risk_level="medium",
+        compiled=_RE_URL_CRED_PARAM,
+        flag_name="url_credential_param",
+        annotation="Output contains URLs with credential-bearing query parameters.",
+        priority=20,
+    ),
+    OutputGuardPatternDef(
+        name="cloud_metadata",
+        category="adversarial_urls",
+        risk_level="medium",
+        compiled=_RE_CLOUD_METADATA,
+        flag_name="cloud_metadata_access",
+        annotation="Output references cloud metadata endpoints.",
+        priority=10,
+    ),
+    # -- info_disclosure (priority 5, low) --
+    OutputGuardPatternDef(
+        name="cloud_identity_doc",
+        category="info_disclosure",
+        risk_level="low",
+        compiled=_RE_CLOUD_IDENTITY_DOC,
+        flag_name="cloud_identity_disclosure",
+        annotation="Output contains cloud instance identity metadata.",
+        priority=20,
+    ),
+    OutputGuardPatternDef(
+        name="sensitive_path",
+        category="info_disclosure",
+        risk_level="low",
+        compiled=_RE_SENSITIVE_PATH,
+        flag_name="sensitive_path_disclosure",
+        annotation="Output references sensitive file paths (.env, .ssh/, .aws/, etc.).",
+        priority=10,
+    ),
+]
+
+
 # -- Check functions (one per priority tier) --------------------------------
 
 
@@ -276,6 +498,168 @@ def _redact_credentials(text: str) -> str:
     return result
 
 
+# -- Configurable-mode helpers (used when patterns kwarg is provided) --------
+
+# Category → parent flag (idempotently added for each pattern match in that category)
+_CATEGORY_PARENT_FLAGS: dict[str, str] = {
+    "prompt_injection": "prompt_injection",
+    "credentials": "credential_leak",
+}
+
+
+def _check_patterns(
+    text: str,
+    category_patterns: tuple[OutputGuardPatternDef, ...],
+    flags: list[str],
+    ann: list[str],
+    parent_flag: str = "",
+) -> tuple[str, str | None]:
+    """Run configurable patterns for a category.  Returns (risk, sanitized_or_None)."""
+    risk = "none"
+    sanitized: str | None = None
+    need_redact = False
+    for pat in category_patterns:
+        if pat.compiled.search(text):
+            if parent_flag:
+                _add_flag(flags, parent_flag)
+            _add_flag(flags, pat.flag_name)
+            if pat.annotation not in ann:
+                ann.append(pat.annotation)
+            risk = _max_risk(risk, pat.risk_level)
+            if pat.is_credential:
+                need_redact = True
+    if need_redact:
+        sanitized = _redact_with_patterns(text, category_patterns)
+    return risk, sanitized
+
+
+def _redact_with_patterns(
+    text: str,
+    patterns: tuple[OutputGuardPatternDef, ...],
+) -> str:
+    """Redact text using credential patterns from the given pattern set."""
+    result = text
+    for pat in patterns:
+        if pat.is_credential and pat.redact_label:
+            result = pat.compiled.sub(f"[REDACTED:{pat.redact_label}]", result)
+    return result
+
+
+def _check_credentials_complex(
+    text: str,
+    flags: list[str],
+    ann: list[str],
+) -> tuple[str, str | None]:
+    """Complex credential checks that require custom redaction logic.
+
+    Handles private key blocks, connection strings (need targeted sub-replacement
+    to preserve protocol/username), env-line parsing (two-regex pipeline), and
+    JSON secret detection (capture group redaction).
+    """
+    risk = "none"
+    found = False
+
+    if _RE_PRIVATE_KEY_BLOCK.search(text):
+        _add_flag(flags, "credential_leak")
+        _add_flag(flags, "private_key_leak")
+        ann.append("Output contains a PEM-encoded private key block.")
+        found = True
+        risk = "high"
+
+    if _RE_CONNECTION_STRING.search(text):
+        _add_flag(flags, "credential_leak")
+        _add_flag(flags, "connection_string_leak")
+        ann.append("Output contains a connection string with embedded credentials.")
+        found = True
+        risk = "high"
+
+    env_lines = _RE_ENV_SECRET_LINE.findall(text)
+    if any(_RE_ENV_SECRET_KEY.search(ln.split("=", 1)[0]) for ln in env_lines):
+        _add_flag(flags, "credential_leak")
+        _add_flag(flags, "env_file_leak")
+        ann.append("Output contains .env-style assignments with secret-bearing keys.")
+        found = True
+        risk = "high"
+
+    if _RE_JSON_SECRET.search(text):
+        _add_flag(flags, "credential_leak")
+        _add_flag(flags, "json_secret_leak")
+        ann.append(
+            "Output contains JSON with secret-bearing keys (api_key, password, token, etc.)."
+        )
+        found = True
+        risk = "high"
+
+    sanitized = _redact_credentials_complex(text) if found else None
+    return risk, sanitized
+
+
+def _redact_credentials_complex(text: str) -> str:
+    """Redact private keys, connection strings, env-lines, and JSON secrets.
+
+    Uses targeted sub-replacement to preserve context (protocol, username)
+    in connection strings and PEM block boundaries.
+    """
+    result = _RE_PRIVATE_KEY_BLOCK.sub("[REDACTED:private_key]", text)
+
+    def _redact_conn(m: re.Match[str]) -> str:
+        return re.sub(r"://([^:@\s]+):([^@\s]+)@", r"://\1:[REDACTED:password]@", m.group())
+
+    result = _RE_CONNECTION_STRING.sub(_redact_conn, result)
+
+    def _redact_env(m: re.Match[str]) -> str:
+        key = m.group().split("=", 1)[0]
+        return key + "=[REDACTED:secret]" if _RE_ENV_SECRET_KEY.search(key) else m.group()
+
+    result = _RE_ENV_SECRET_LINE.sub(_redact_env, result)
+
+    def _redact_json_secret(m: re.Match[str]) -> str:
+        start = m.start(1) - m.start()
+        end = m.end(1) - m.start()
+        full = m.group()
+        return full[:start] + "[REDACTED:secret]" + full[end:]
+
+    result = _RE_JSON_SECRET.sub(_redact_json_secret, result)
+    return result
+
+
+def _check_encoded_payloads_complex(
+    text: str,
+    flags: list[str],
+    ann: list[str],
+) -> str:
+    """Complex encoded payload check (base64 context analysis)."""
+    risk = "none"
+    for m in _RE_LARGE_BASE64.finditer(text):
+        ctx = text[max(0, m.start() - 100) : m.start()].lower()
+        if _RE_BASE64_IMAGE_CONTEXT.search(ctx):
+            continue
+        if _RE_BASE64_EXEC_CONTEXT.search(ctx):
+            _add_flag(flags, "encoded_payload")
+            ann.append("Output contains a large base64 block in an executable context.")
+            risk = _max_risk(risk, "medium")
+            break
+    return risk
+
+
+def _check_info_disclosure_complex(
+    text: str,
+    flags: list[str],
+    ann: list[str],
+) -> str:
+    """Complex info disclosure check (private IP with 127.0.0.1 exclusion)."""
+    risk = "none"
+    private_ips = [ip for ip in _RE_PRIVATE_IP.findall(text) if ip != "127.0.0.1"]
+    if private_ips:
+        _add_flag(flags, "private_ip_disclosure")
+        ann.append("Output contains internal/private IP addresses (RFC 1918 ranges).")
+        risk = "low"
+    return risk
+
+
+# -- Legacy check functions (one per priority tier) -------------------------
+
+
 def _check_encoded_payloads(text: str, flags: list[str], ann: list[str]) -> str:
     """Priority 3: encoded / obfuscated payloads."""
     risk = "none"
@@ -339,12 +723,22 @@ def _check_info_disclosure(text: str, flags: list[str], ann: list[str]) -> str:
 # -- Public API -------------------------------------------------------------
 
 
+_CATEGORY_ORDER = (
+    "prompt_injection",
+    "credentials",
+    "encoded_payloads",
+    "adversarial_urls",
+    "info_disclosure",
+)
+
+
 def evaluate_output(
     output: str,
     *,
     func_name: str = "",
     call_id: str = "",
     budget_seconds: float = 5.0,
+    patterns: Mapping[str, tuple[OutputGuardPatternDef, ...]] | None = None,
 ) -> OutputAssessment:
     """Evaluate tool output for security signals.
 
@@ -356,6 +750,10 @@ def evaluate_output(
         func_name: Name of the tool that produced the output (for future use).
         call_id: Unique call identifier (for future correlation).
         budget_seconds: Maximum wall-clock seconds to spend on evaluation.
+        patterns: Optional category-grouped patterns from :class:`RuleRegistry`.
+            When provided, configurable patterns are used instead of the
+            hard-coded check functions.  Complex multi-step checks (env-line
+            parsing, base64 context analysis, etc.) always run regardless.
 
     Returns:
         Frozen OutputAssessment with flags, risk level, annotations, and
@@ -370,6 +768,46 @@ def evaluate_output(
     risk = "none"
     sanitized: str | None = None
 
+    if patterns is not None:
+        # Configurable mode: use registry patterns + complex checks
+        for cat in _CATEGORY_ORDER:
+            cat_pats = patterns.get(cat, ())
+            if cat_pats:
+                parent = _CATEGORY_PARENT_FLAGS.get(cat, "")
+                pat_risk, pat_sanitized = _check_patterns(
+                    output,
+                    cat_pats,
+                    flags,
+                    ann,
+                    parent,
+                )
+                risk = _max_risk(risk, pat_risk)
+                if pat_sanitized:
+                    sanitized = pat_sanitized if sanitized is None else pat_sanitized
+            # Run hard-coded complex checks for categories that need them
+            if cat == "credentials":
+                # Chain redaction: apply complex checks to already-sanitized text
+                cred_input = sanitized if sanitized is not None else output
+                cred_risk, cred_san = _check_credentials_complex(cred_input, flags, ann)
+                risk = _max_risk(risk, cred_risk)
+                if cred_san:
+                    sanitized = cred_san
+            elif cat == "encoded_payloads":
+                risk = _max_risk(
+                    risk,
+                    _check_encoded_payloads_complex(output, flags, ann),
+                )
+            elif cat == "info_disclosure":
+                risk = _max_risk(
+                    risk,
+                    _check_info_disclosure_complex(output, flags, ann),
+                )
+            if time.monotonic() > deadline:
+                return _build(flags, risk, ann, sanitized)
+        return _build(flags, risk, ann, sanitized)
+
+    # Legacy mode: hard-coded patterns (backward compat)
+
     # Priority 1: prompt injection (always run, highest priority)
     risk = _max_risk(risk, _check_prompt_injection(output, flags, ann))
     if time.monotonic() > deadline:

turnstone/core/providers/__init__.py

@@ -6,6 +6,8 @@ import threading
 from typing import Any
 
 from turnstone.core.providers._openai import OpenAIProvider
+from turnstone.core.providers._openai_chat import OpenAIChatCompletionsProvider
+from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
 from turnstone.core.providers._protocol import (
     CompletionResult,
     LLMProvider,
@@ -19,7 +21,9 @@ __all__ = [
     "CompletionResult",
     "LLMProvider",
     "ModelCapabilities",
+    "OpenAIChatCompletionsProvider",
     "OpenAIProvider",
+    "OpenAIResponsesProvider",
     "StreamChunk",
     "ToolCallDelta",
     "UsageInfo",
@@ -31,15 +35,18 @@ __all__ = [
 
 # Singleton instances (stateless, safe to share)
 _provider_lock = threading.Lock()
-_openai_provider = OpenAIProvider()
+_openai_provider = OpenAIResponsesProvider()
+_openai_compat_provider = OpenAIChatCompletionsProvider()
 _anthropic_provider: LLMProvider | None = None
 
 
 def create_provider(provider_name: str) -> LLMProvider:
     """Return a provider adapter for the given provider name. Thread-safe."""
     global _anthropic_provider  # noqa: PLW0603
-    if provider_name in ("openai", "openai-compatible"):
+    if provider_name == "openai":
         return _openai_provider
+    if provider_name == "openai-compatible":
+        return _openai_compat_provider
     if provider_name == "anthropic":
         with _provider_lock:
             if _anthropic_provider is None:
@@ -99,9 +106,9 @@ def lookup_model_capabilities(provider: str, model: str) -> dict[str, Any] | Non
 def list_known_models(provider: str) -> list[str]:
     """Return the model name prefixes in the static capability table."""
     if provider == "openai":
-        from turnstone.core.providers._openai import _OPENAI_CAPABILITIES
+        from turnstone.core.providers._openai_common import OPENAI_CAPABILITIES
 
-        return sorted(_OPENAI_CAPABILITIES.keys())
+        return sorted(OPENAI_CAPABILITIES.keys())
     if provider == "anthropic":
         from turnstone.core.providers._anthropic import _ANTHROPIC_CAPABILITIES
 

turnstone/core/providers/_anthropic.py

@@ -543,9 +543,13 @@ class AnthropicProvider:
         if extra_params and "thinking_budget_tokens" in extra_params:
             budget = extra_params["thinking_budget_tokens"]
         if budget > 0:
-            # Budget must leave room for the response
+            # Budget must be strictly less than max_tokens (API requirement).
+            # If max_tokens is too small to fit even a minimal thinking
+            # budget alongside the response, disable thinking entirely.
             if budget >= max_tokens:
-                budget = max(1024, max_tokens - 1024)
+                budget = max_tokens - 1024
+            if budget < 1:
+                return {}
             return {"thinking": {"type": "enabled", "budget_tokens": budget}}
         return {}
 
@@ -704,7 +708,7 @@ class AnthropicProvider:
                         parsed = json.loads(info["input_json"])
                         query = parsed.get("query", "")
                     except (json.JSONDecodeError, TypeError):
-                        pass
+                        pass  # best-effort query extraction for status
                     sc.info_delta = f"[Searching: {query}]" if query else "[Searching...]"
 
             elif event_type == "message_delta":

turnstone/core/providers/_openai.py

@@ -1,577 +1,30 @@
-"""OpenAI-compatible provider — wraps current behavior with zero semantic change.
+"""Re-export shim for backwards compatibility.
 
-Handles OpenAI, vLLM, llama.cpp, and any server that speaks the
-OpenAI Chat Completions API.
+The OpenAI provider family is split into:
+- ``_openai_chat.py``      — Chat Completions API (local model servers)
+- ``_openai_responses.py`` — Responses API (commercial OpenAI)
+- ``_openai_common.py``    — shared capability table, helpers
+
+``OpenAIProvider`` is preserved as an alias for ``OpenAIChatCompletionsProvider``
+so existing code that imports it directly continues to work.
 """
 
-from __future__ import annotations
-
-from typing import TYPE_CHECKING, Any
-
-if TYPE_CHECKING:
-    from collections.abc import Iterator
-
-import structlog
-
-from turnstone.core.providers._protocol import (
-    CompletionResult,
-    ModelCapabilities,
-    StreamChunk,
-    ToolCallDelta,
-    UsageInfo,
-    _lookup_capabilities,
+from turnstone.core.providers._openai_chat import (
+    OpenAIChatCompletionsProvider,
+)
+from turnstone.core.providers._openai_chat import (
+    OpenAIChatCompletionsProvider as OpenAIProvider,
 )
 
-log = structlog.get_logger(__name__)
+# Backwards-compatible aliases for the capability tables
+from turnstone.core.providers._openai_common import (
+    OPENAI_CAPABILITIES as _OPENAI_CAPABILITIES,  # noqa: F401
+)
+from turnstone.core.providers._openai_common import OPENAI_DEFAULT as _OPENAI_DEFAULT  # noqa: F401
+from turnstone.core.providers._openai_responses import OpenAIResponsesProvider
 
-# -- model capabilities -------------------------------------------------------
-
-_OPENAI_CAPABILITIES: dict[str, ModelCapabilities] = {
-    # GPT-5 base — NO temperature support
-    "gpt-5": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        reasoning_effort_values=("minimal", "low", "medium", "high"),
-        default_reasoning_effort="medium",
-        supports_vision=True,
-    ),
-    "gpt-5-mini": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        reasoning_effort_values=("minimal", "low", "medium", "high"),
-        default_reasoning_effort="medium",
-        supports_vision=True,
-    ),
-    "gpt-5-nano": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        reasoning_effort_values=("minimal", "low", "medium", "high"),
-        default_reasoning_effort="medium",
-        supports_vision=True,
-    ),
-    # GPT-5 pro — high reasoning only, extended output
-    "gpt-5-pro": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=272000,
-        supports_temperature=False,
-        reasoning_effort_values=("high",),
-        default_reasoning_effort="high",
-        supports_vision=True,
-    ),
-    # GPT-5.1 — temperature OK when reasoning_effort=none (default)
-    "gpt-5.1": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        reasoning_effort_values=("none", "low", "medium", "high"),
-        default_reasoning_effort="none",
-        supports_vision=True,
-    ),
-    # GPT-5.2 — adds xhigh
-    "gpt-5.2": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
-        default_reasoning_effort="none",
-        supports_vision=True,
-    ),
-    # GPT-5.2 pro — always-reasoning variant
-    "gpt-5.2-pro": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        reasoning_effort_values=("medium", "high", "xhigh"),
-        default_reasoning_effort="medium",
-        supports_vision=True,
-    ),
-    # GPT-5.3 — same capabilities as 5.2 (matches gpt-5.3-chat-latest, codex)
-    "gpt-5.3": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
-        default_reasoning_effort="none",
-        supports_vision=True,
-    ),
-    # GPT-5.4 — 1M context window, native tool search
-    "gpt-5.4": ModelCapabilities(
-        context_window=1050000,
-        max_output_tokens=128000,
-        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
-        default_reasoning_effort="none",
-        supports_tool_search=True,
-        supports_vision=True,
-    ),
-    # GPT-5.4 pro — always-reasoning, 1M context, native tool search
-    "gpt-5.4-pro": ModelCapabilities(
-        context_window=1050000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        reasoning_effort_values=("medium", "high", "xhigh"),
-        default_reasoning_effort="medium",
-        supports_tool_search=True,
-        supports_vision=True,
-    ),
-    # O-series reasoning models
-    "o1": ModelCapabilities(
-        context_window=200000,
-        max_output_tokens=100000,
-        supports_temperature=False,
-        supports_streaming=False,
-        supports_vision=True,
-    ),
-    "o1-mini": ModelCapabilities(
-        context_window=128000,
-        max_output_tokens=65536,
-        supports_temperature=False,
-        supports_streaming=False,
-        supports_vision=True,
-    ),
-    "o3": ModelCapabilities(
-        context_window=200000,
-        max_output_tokens=100000,
-        supports_temperature=False,
-        supports_vision=True,
-    ),
-    "o3-mini": ModelCapabilities(
-        context_window=200000,
-        max_output_tokens=100000,
-        supports_temperature=False,
-        supports_vision=True,
-    ),
-    "o3-pro": ModelCapabilities(
-        context_window=200000,
-        max_output_tokens=100000,
-        supports_temperature=False,
-        supports_streaming=False,
-        supports_vision=True,
-    ),
-    "o4-mini": ModelCapabilities(
-        context_window=200000,
-        max_output_tokens=100000,
-        supports_temperature=False,
-        supports_vision=True,
-    ),
-    # Search models — always search on every request, no reasoning_effort
-    "gpt-5-search-api": ModelCapabilities(
-        context_window=400000,
-        max_output_tokens=128000,
-        supports_temperature=False,
-        supports_web_search=True,
-        reasoning_effort_values=(),
-        supports_vision=True,
-    ),
-}
-
-# Default for unknown models (local servers: vLLM, llama.cpp, etc.)
-_OPENAI_DEFAULT = ModelCapabilities()
-
-
-class OpenAIProvider:
-    """Provider for OpenAI-compatible APIs (OpenAI, vLLM, llama.cpp, etc.)."""
-
-    @property
-    def provider_name(self) -> str:
-        return "openai"
-
-    def get_capabilities(self, model: str) -> ModelCapabilities:
-        return _lookup_capabilities(model, _OPENAI_CAPABILITIES, _OPENAI_DEFAULT)
-
-    # -- shared param logic --------------------------------------------------
-
-    def _apply_model_params(
-        self,
-        kwargs: dict[str, Any],
-        caps: ModelCapabilities,
-        temperature: float,
-        reasoning_effort: str,
-    ) -> None:
-        """Conditionally add temperature and reasoning_effort to *kwargs*.
-
-        - Models with ``supports_temperature=False`` (GPT-5 base, O-series)
-          never receive temperature.
-        - Models that list ``"none"`` in their effort values (GPT-5.1/5.2)
-          only receive temperature when reasoning is inactive.
-        - ``reasoning_effort`` is forwarded as a first-class API parameter
-          only for models that declare supported effort values.
-        """
-        if caps.supports_temperature:
-            # GPT-5.1/5.2: temperature only valid when reasoning_effort is "none"
-            if "none" in caps.reasoning_effort_values and reasoning_effort not in (
-                "none",
-                "",
-            ):
-                pass  # Skip temperature when reasoning is active
-            else:
-                kwargs["temperature"] = temperature
-        if caps.reasoning_effort_values and reasoning_effort and reasoning_effort != "none":
-            # Validate against supported values; fall back to model default
-            if reasoning_effort in caps.reasoning_effort_values:
-                kwargs["reasoning_effort"] = reasoning_effort
-            elif caps.default_reasoning_effort and caps.default_reasoning_effort != "none":
-                kwargs["reasoning_effort"] = caps.default_reasoning_effort
-
-    # -- web search ----------------------------------------------------------
-
-    def _apply_web_search(
-        self,
-        kwargs: dict[str, Any],
-        caps: ModelCapabilities,
-        tools: list[dict[str, Any]] | None,
-    ) -> list[dict[str, Any]] | None:
-        """Inject ``web_search_options`` for search models.
-
-        For models with ``supports_web_search``, the web search function tool
-        is removed (the model searches automatically) and ``web_search_options``
-        is added to the request kwargs.
-
-        Returns the (possibly filtered) tools list.
-        """
-        if not caps.supports_web_search:
-            return tools
-        # Remove web_search function tool — model has built-in search
-        if tools:
-            tools = [t for t in tools if t.get("function", {}).get("name") != "web_search"]
-            if not tools:
-                tools = None
-        kwargs["web_search_options"] = {}
-        return tools
-
-    # -- prompt cache retention -----------------------------------------------
-
-    @staticmethod
-    def _apply_cache_retention(kwargs: dict[str, Any], model: str) -> None:
-        """Enable 24-hour extended prompt cache retention for GPT-5.x models.
-
-        OpenAI caching is automatic (no code changes for basic caching), but
-        the default TTL is only 5-10 minutes.  Extended retention keeps cached
-        KV tensors for up to 24 hours at no additional cost, which is valuable
-        for workstreams with bursty activity patterns.
-        """
-        # GPT-5, GPT-5.1, GPT-5.2, GPT-5.3, GPT-5.4 and variants
-        if model.startswith("gpt-5"):
-            kwargs["prompt_cache_retention"] = "24h"
-
-    # -- tool search ---------------------------------------------------------
-
-    def _apply_tool_search(
-        self,
-        caps: ModelCapabilities,
-        tools: list[dict[str, Any]] | None,
-        deferred_names: frozenset[str] | None = None,
-    ) -> list[dict[str, Any]] | None:
-        """Mark deferred tools with ``defer_loading: true`` for native search.
-
-        For GPT-5.4+ models that support tool search, OpenAI's API handles
-        discovery automatically — no explicit search tool is needed.
-        """
-        if not caps.supports_tool_search or not deferred_names or not tools:
-            return tools
-        result = []
-        for tool in tools:
-            name = tool.get("function", {}).get("name", "")
-            if name in deferred_names:
-                result.append({**tool, "defer_loading": True})
-            else:
-                result.append(tool)
-        return result
-
-    # -- message sanitisation ------------------------------------------------
-
-    @staticmethod
-    def _sanitize_messages(
-        messages: list[dict[str, Any]],
-    ) -> list[dict[str, Any]]:
-        """Ensure assistant messages always have ``content`` or ``tool_calls``.
-
-        OpenAI-compatible APIs reject assistant messages that have neither.
-        This is a defensive catch-all; the upstream layers should already
-        guarantee well-formed messages.
-        """
-        out: list[dict[str, Any]] = []
-        for msg in messages:
-            if (
-                msg.get("role") == "assistant"
-                and msg.get("content") is None
-                and not msg.get("tool_calls")
-            ):
-                msg = {**msg, "content": ""}
-            out.append(msg)
-        return out
-
-    # -- streaming -----------------------------------------------------------
-
-    def create_streaming(
-        self,
-        *,
-        client: Any,
-        model: str,
-        messages: list[dict[str, Any]],
-        tools: list[dict[str, Any]] | None = None,
-        max_tokens: int = 4096,
-        temperature: float = 0.5,
-        reasoning_effort: str = "medium",
-        extra_params: dict[str, Any] | None = None,
-        deferred_names: frozenset[str] | None = None,
-        cancel_ref: list[Any] | None = None,
-    ) -> Iterator[StreamChunk]:
-        caps = self.get_capabilities(model)
-        messages = self._sanitize_messages(messages)
-        kwargs: dict[str, Any] = {
-            "model": model,
-            "messages": messages,
-            caps.token_param: max_tokens,
-            "stream": True,
-            "stream_options": {"include_usage": True},
-        }
-        self._apply_model_params(kwargs, caps, temperature, reasoning_effort)
-        self._apply_cache_retention(kwargs, model)
-        tools = self._apply_web_search(kwargs, caps, tools)
-        tools = self._apply_tool_search(caps, tools, deferred_names)
-        if tools:
-            kwargs["tools"] = tools
-        if extra_params:
-            kwargs["extra_body"] = extra_params
-
-        log.debug(
-            "openai.request",
-            model=model,
-            stream=True,
-            max_tokens=max_tokens,
-            message_count=len(messages),
-            tool_count=len(tools) if tools else 0,
-        )
-        stream = client.chat.completions.create(**kwargs)
-        if cancel_ref is not None:
-            cancel_ref.append(stream)
-        return self._iter_stream(stream)
-
-    def _iter_stream(self, stream: Any) -> Iterator[StreamChunk]:
-        """Convert OpenAI stream chunks to normalized StreamChunks."""
-        first = True
-        annotations: list[Any] = []
-        content_len = 0
-        tool_call_count = 0
-        last_finish_reason: str | None = None
-        completion_tokens: int | None = None
-        for chunk in stream:
-            sc = StreamChunk()
-
-            # Finish reason
-            if chunk.choices and chunk.choices[0].finish_reason:
-                sc.finish_reason = chunk.choices[0].finish_reason
-                last_finish_reason = sc.finish_reason
-
-            # Usage from final chunk
-            if hasattr(chunk, "usage") and chunk.usage is not None:
-                u = chunk.usage
-                pt = getattr(u, "prompt_tokens", None)
-                ct = getattr(u, "completion_tokens", None)
-                tt = getattr(u, "total_tokens", None)
-                completion_tokens = ct
-                if pt is not None and ct is not None:
-                    # Extract cached_tokens from prompt_tokens_details.
-                    # OpenAI caching is automatic with no write premium, so
-                    # cache_creation_tokens is always 0 (only Anthropic reports it).
-                    ptd = getattr(u, "prompt_tokens_details", None)
-                    cached = getattr(ptd, "cached_tokens", 0) if ptd else 0
-                    sc.usage = UsageInfo(
-                        prompt_tokens=pt,
-                        completion_tokens=ct,
-                        total_tokens=tt or (pt + ct),
-                        cache_read_tokens=cached or 0,
-                    )
-
-            if not chunk.choices:
-                if sc.usage:
-                    yield sc
-                continue
-
-            delta = chunk.choices[0].delta
-
-            # Reasoning field (vLLM --reasoning-parser, llama.cpp)
-            rc = getattr(delta, "reasoning", None) or getattr(delta, "reasoning_content", None)
-            if rc:
-                sc.reasoning_delta = rc
-
-            # Content
-            if delta.content:
-                sc.content_delta = delta.content
-                content_len += len(delta.content)
-
-            # Tool calls
-            if delta.tool_calls:
-                for tc_delta in delta.tool_calls:
-                    tcd = ToolCallDelta(index=tc_delta.index)
-                    if tc_delta.id:
-                        tcd.id = tc_delta.id
-                    if tc_delta.function:
-                        if tc_delta.function.name:
-                            tcd.name = tc_delta.function.name
-                        if tc_delta.function.arguments:
-                            tcd.arguments_delta = tc_delta.function.arguments
-                    sc.tool_call_deltas.append(tcd)
-                    tool_call_count += 1
-
-            # Accumulate url_citation annotations from search models
-            delta_anns = getattr(delta, "annotations", None)
-            if delta_anns:
-                annotations.extend(delta_anns)
-
-            has_content = sc.content_delta or sc.reasoning_delta or sc.tool_call_deltas
-            if has_content and first:
-                sc.is_first = True
-                first = False
-
-            if has_content or sc.finish_reason or sc.usage:
-                yield sc
-
-        log.debug(
-            "openai.response",
-            stream=True,
-            finish_reason=last_finish_reason,
-            content_length=content_len,
-            tool_call_deltas=tool_call_count,
-            completion_tokens=completion_tokens,
-        )
-
-        # Emit accumulated citations as a final info chunk
-        if annotations:
-            citation_text = self._format_citations("", annotations).strip()
-            if citation_text:
-                yield StreamChunk(info_delta=citation_text)
-
-    # -- non-streaming -------------------------------------------------------
-
-    def create_completion(
-        self,
-        *,
-        client: Any,
-        model: str,
-        messages: list[dict[str, Any]],
-        tools: list[dict[str, Any]] | None = None,
-        max_tokens: int = 4096,
-        temperature: float = 0.5,
-        reasoning_effort: str = "medium",
-        extra_params: dict[str, Any] | None = None,
-        deferred_names: frozenset[str] | None = None,
-    ) -> CompletionResult:
-        caps = self.get_capabilities(model)
-        messages = self._sanitize_messages(messages)
-        kwargs: dict[str, Any] = {
-            "model": model,
-            "messages": messages,
-            caps.token_param: max_tokens,
-            "stream": False,
-        }
-        self._apply_model_params(kwargs, caps, temperature, reasoning_effort)
-        self._apply_cache_retention(kwargs, model)
-        tools = self._apply_web_search(kwargs, caps, tools)
-        tools = self._apply_tool_search(caps, tools, deferred_names)
-        if tools:
-            kwargs["tools"] = tools
-        if extra_params:
-            kwargs["extra_body"] = extra_params
-
-        log.debug(
-            "openai.request",
-            model=model,
-            stream=False,
-            max_tokens=max_tokens,
-            message_count=len(messages),
-            tool_count=len(tools) if tools else 0,
-        )
-        response = client.chat.completions.create(**kwargs)
-        choice = response.choices[0]
-        msg = choice.message
-
-        tool_calls = None
-        if msg.tool_calls:
-            tool_calls = [
-                {
-                    "id": tc.id,
-                    "type": "function",
-                    "function": {
-                        "name": tc.function.name,
-                        "arguments": tc.function.arguments,
-                    },
-                }
-                for tc in msg.tool_calls
-            ]
-
-        # Extract url_citation annotations from web search models
-        content = msg.content or ""
-        annotations = getattr(msg, "annotations", None)
-        if annotations:
-            content = self._format_citations(content, annotations)
-
-        usage = None
-        if hasattr(response, "usage") and response.usage:
-            u = response.usage
-            ptd = getattr(u, "prompt_tokens_details", None)
-            cached = getattr(ptd, "cached_tokens", 0) if ptd else 0
-            usage = UsageInfo(
-                prompt_tokens=u.prompt_tokens,
-                completion_tokens=u.completion_tokens,
-                total_tokens=getattr(u, "total_tokens", None)
-                or (u.prompt_tokens + u.completion_tokens),
-                cache_read_tokens=cached or 0,
-            )
-
-        result = CompletionResult(
-            content=content,
-            tool_calls=tool_calls,
-            finish_reason=choice.finish_reason or "stop",
-            usage=usage,
-        )
-        log.debug(
-            "openai.response",
-            stream=False,
-            finish_reason=result.finish_reason,
-            content_length=len(content),
-            tool_call_count=len(tool_calls) if tool_calls else 0,
-            completion_tokens=usage.completion_tokens if usage else None,
-        )
-        return result
-
-    @staticmethod
-    def _format_citations(content: str, annotations: list[Any]) -> str:
-        """Append url_citation sources as footnotes at the end of the content."""
-        seen_urls: set[str] = set()
-        sources: list[str] = []
-        for ann in annotations:
-            ann_type = getattr(ann, "type", None)
-            if ann_type == "url_citation":
-                citation = getattr(ann, "url_citation", None)
-                if citation:
-                    title = getattr(citation, "title", "")
-                    url = getattr(citation, "url", "")
-                    if url and url not in seen_urls:
-                        seen_urls.add(url)
-                        sources.append(f"[{title}]({url})" if title else url)
-        if sources:
-            content += "\n\nSources:\n" + "\n".join(f"- {s}" for s in sources)
-        return content
-
-    # -- tool conversion -----------------------------------------------------
-
-    def convert_tools(
-        self,
-        tools: list[dict[str, Any]],
-    ) -> list[dict[str, Any]]:
-        return tools  # Already in OpenAI format
-
-    # -- retryable errors ----------------------------------------------------
-
-    @property
-    def retryable_error_names(self) -> frozenset[str]:
-        return frozenset(
-            {
-                "APIError",
-                "APIConnectionError",
-                "RateLimitError",
-                "Timeout",
-                "APITimeoutError",
-            }
-        )
+__all__ = [
+    "OpenAIChatCompletionsProvider",
+    "OpenAIProvider",
+    "OpenAIResponsesProvider",
+]

turnstone/core/providers/_openai_chat.py

@@ -0,0 +1,296 @@
+"""Chat Completions provider — for local model servers (vLLM, llama.cpp, SGLang).
+
+Wraps the OpenAI Chat Completions API (``/v1/chat/completions``).
+Commercial OpenAI models should use ``OpenAIResponsesProvider`` instead.
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+import structlog
+
+from turnstone.core.providers._openai_common import (
+    RETRYABLE_ERROR_NAMES,
+    apply_cache_retention,
+    apply_temperature_and_effort,
+    apply_tool_search,
+    extract_usage,
+    format_citations,
+    lookup_openai_capabilities,
+    sanitize_messages,
+)
+from turnstone.core.providers._protocol import (
+    CompletionResult,
+    ModelCapabilities,
+    StreamChunk,
+    ToolCallDelta,
+)
+
+log = structlog.get_logger(__name__)
+
+
+class OpenAIChatCompletionsProvider:
+    """Provider for local OpenAI-compatible servers (vLLM, llama.cpp, SGLang).
+
+    Uses the Chat Completions API (``/v1/chat/completions``).
+    """
+
+    @property
+    def provider_name(self) -> str:
+        return "openai-compatible"
+
+    def get_capabilities(self, model: str) -> ModelCapabilities:
+        return lookup_openai_capabilities(model)
+
+    # -- web search ----------------------------------------------------------
+
+    @staticmethod
+    def _apply_web_search(
+        kwargs: dict[str, Any],
+        caps: ModelCapabilities,
+        tools: list[dict[str, Any]] | None,
+    ) -> list[dict[str, Any]] | None:
+        """Inject ``web_search_options`` for search models.
+
+        For models with ``supports_web_search``, the web search function tool
+        is removed (the model searches automatically) and ``web_search_options``
+        is added to the request kwargs.
+
+        Returns the (possibly filtered) tools list.
+        """
+        if not caps.supports_web_search:
+            return tools
+        if tools:
+            tools = [t for t in tools if t.get("function", {}).get("name") != "web_search"]
+            if not tools:
+                tools = None
+        kwargs["web_search_options"] = {}
+        return tools
+
+    # -- streaming -----------------------------------------------------------
+
+    def create_streaming(
+        self,
+        *,
+        client: Any,
+        model: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.5,
+        reasoning_effort: str = "medium",
+        extra_params: dict[str, Any] | None = None,
+        deferred_names: frozenset[str] | None = None,
+        cancel_ref: list[Any] | None = None,
+    ) -> Iterator[StreamChunk]:
+        caps = self.get_capabilities(model)
+        messages = sanitize_messages(messages)
+        kwargs: dict[str, Any] = {
+            "model": model,
+            "messages": messages,
+            caps.token_param: max_tokens,
+            "stream": True,
+            "stream_options": {"include_usage": True},
+        }
+        apply_temperature_and_effort(kwargs, caps, temperature, reasoning_effort)
+        apply_cache_retention(kwargs, model)
+        tools = self._apply_web_search(kwargs, caps, tools)
+        tools = apply_tool_search(caps, tools, deferred_names)
+        if tools:
+            kwargs["tools"] = tools
+        if extra_params:
+            kwargs["extra_body"] = extra_params
+
+        log.debug(
+            "openai.chat.request",
+            model=model,
+            stream=True,
+            max_tokens=max_tokens,
+            message_count=len(messages),
+            tool_count=len(tools) if tools else 0,
+        )
+        stream = client.chat.completions.create(**kwargs)
+        if cancel_ref is not None:
+            cancel_ref.append(stream)
+        return self._iter_stream(stream)
+
+    def _iter_stream(self, stream: Any) -> Iterator[StreamChunk]:
+        """Convert OpenAI Chat Completions stream chunks to StreamChunks."""
+        first = True
+        annotations: list[Any] = []
+        content_len = 0
+        tool_call_count = 0
+        last_finish_reason: str | None = None
+        completion_tokens: int | None = None
+        for chunk in stream:
+            sc = StreamChunk()
+
+            # Finish reason
+            if chunk.choices and chunk.choices[0].finish_reason:
+                sc.finish_reason = chunk.choices[0].finish_reason
+                last_finish_reason = sc.finish_reason
+
+            # Usage from final chunk
+            if hasattr(chunk, "usage") and chunk.usage is not None:
+                sc.usage = extract_usage(chunk.usage)
+                if sc.usage:
+                    completion_tokens = sc.usage.completion_tokens
+
+            if not chunk.choices:
+                if sc.usage:
+                    yield sc
+                continue
+
+            delta = chunk.choices[0].delta
+
+            # Reasoning field (vLLM --reasoning-parser, llama.cpp)
+            rc = getattr(delta, "reasoning", None) or getattr(delta, "reasoning_content", None)
+            if rc:
+                sc.reasoning_delta = rc
+
+            # Content
+            if delta.content:
+                sc.content_delta = delta.content
+                content_len += len(delta.content)
+
+            # Tool calls
+            if delta.tool_calls:
+                for tc_delta in delta.tool_calls:
+                    tcd = ToolCallDelta(index=tc_delta.index)
+                    if tc_delta.id:
+                        tcd.id = tc_delta.id
+                    if tc_delta.function:
+                        if tc_delta.function.name:
+                            tcd.name = tc_delta.function.name
+                        if tc_delta.function.arguments:
+                            tcd.arguments_delta = tc_delta.function.arguments
+                    sc.tool_call_deltas.append(tcd)
+                    tool_call_count += 1
+
+            # Accumulate url_citation annotations from search models
+            delta_anns = getattr(delta, "annotations", None)
+            if delta_anns:
+                annotations.extend(delta_anns)
+
+            has_content = sc.content_delta or sc.reasoning_delta or sc.tool_call_deltas
+            if has_content and first:
+                sc.is_first = True
+                first = False
+
+            if has_content or sc.finish_reason or sc.usage:
+                yield sc
+
+        log.debug(
+            "openai.chat.response",
+            stream=True,
+            finish_reason=last_finish_reason,
+            content_length=content_len,
+            tool_call_deltas=tool_call_count,
+            completion_tokens=completion_tokens,
+        )
+
+        # Emit accumulated citations as a final info chunk
+        if annotations:
+            citation_text = format_citations("", annotations).strip()
+            if citation_text:
+                yield StreamChunk(info_delta=citation_text)
+
+    # -- non-streaming -------------------------------------------------------
+
+    def create_completion(
+        self,
+        *,
+        client: Any,
+        model: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.5,
+        reasoning_effort: str = "medium",
+        extra_params: dict[str, Any] | None = None,
+        deferred_names: frozenset[str] | None = None,
+    ) -> CompletionResult:
+        caps = self.get_capabilities(model)
+        messages = sanitize_messages(messages)
+        kwargs: dict[str, Any] = {
+            "model": model,
+            "messages": messages,
+            caps.token_param: max_tokens,
+            "stream": False,
+        }
+        apply_temperature_and_effort(kwargs, caps, temperature, reasoning_effort)
+        apply_cache_retention(kwargs, model)
+        tools = self._apply_web_search(kwargs, caps, tools)
+        tools = apply_tool_search(caps, tools, deferred_names)
+        if tools:
+            kwargs["tools"] = tools
+        if extra_params:
+            kwargs["extra_body"] = extra_params
+
+        log.debug(
+            "openai.chat.request",
+            model=model,
+            stream=False,
+            max_tokens=max_tokens,
+            message_count=len(messages),
+            tool_count=len(tools) if tools else 0,
+        )
+        response = client.chat.completions.create(**kwargs)
+        choice = response.choices[0]
+        msg = choice.message
+
+        tool_calls = None
+        if msg.tool_calls:
+            tool_calls = [
+                {
+                    "id": tc.id,
+                    "type": "function",
+                    "function": {
+                        "name": tc.function.name,
+                        "arguments": tc.function.arguments,
+                    },
+                }
+                for tc in msg.tool_calls
+            ]
+
+        # Extract url_citation annotations from web search models
+        content = msg.content or ""
+        annotations = getattr(msg, "annotations", None)
+        if annotations:
+            content = format_citations(content, annotations)
+
+        usage = extract_usage(getattr(response, "usage", None))
+
+        result = CompletionResult(
+            content=content,
+            tool_calls=tool_calls,
+            finish_reason=choice.finish_reason or "stop",
+            usage=usage,
+        )
+        log.debug(
+            "openai.chat.response",
+            stream=False,
+            finish_reason=result.finish_reason,
+            content_length=len(content),
+            tool_call_count=len(tool_calls) if tool_calls else 0,
+            completion_tokens=usage.completion_tokens if usage else None,
+        )
+        return result
+
+    # -- tool conversion -----------------------------------------------------
+
+    def convert_tools(
+        self,
+        tools: list[dict[str, Any]],
+    ) -> list[dict[str, Any]]:
+        return tools  # Already in OpenAI Chat Completions format
+
+    # -- retryable errors ----------------------------------------------------
+
+    @property
+    def retryable_error_names(self) -> frozenset[str]:
+        return RETRYABLE_ERROR_NAMES

turnstone/core/providers/_openai_common.py

@@ -0,0 +1,378 @@
+"""Shared helpers for OpenAI-family providers (Chat Completions & Responses).
+
+Capability table, temperature/reasoning gating, cache retention, citation
+formatting, and message sanitisation live here so both
+``OpenAIChatCompletionsProvider`` and ``OpenAIResponsesProvider`` stay DRY.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+from turnstone.core.providers._protocol import (
+    ModelCapabilities,
+    UsageInfo,
+    _lookup_capabilities,
+)
+
+# ---------------------------------------------------------------------------
+# Model capability table
+# ---------------------------------------------------------------------------
+
+OPENAI_CAPABILITIES: dict[str, ModelCapabilities] = {
+    # GPT-5 base — NO temperature support
+    "gpt-5": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        reasoning_effort_values=("minimal", "low", "medium", "high"),
+        default_reasoning_effort="medium",
+        supports_vision=True,
+    ),
+    "gpt-5-mini": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        reasoning_effort_values=("minimal", "low", "medium", "high"),
+        default_reasoning_effort="medium",
+        supports_vision=True,
+    ),
+    "gpt-5-nano": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        reasoning_effort_values=("minimal", "low", "medium", "high"),
+        default_reasoning_effort="medium",
+        supports_vision=True,
+    ),
+    # GPT-5 pro — high reasoning only, extended output
+    "gpt-5-pro": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=272000,
+        supports_temperature=False,
+        reasoning_effort_values=("high",),
+        default_reasoning_effort="high",
+        supports_vision=True,
+    ),
+    # GPT-5.1 — temperature OK when reasoning_effort=none (default)
+    "gpt-5.1": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        reasoning_effort_values=("none", "low", "medium", "high"),
+        default_reasoning_effort="none",
+        supports_vision=True,
+    ),
+    # GPT-5.2 — adds xhigh
+    "gpt-5.2": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
+        default_reasoning_effort="none",
+        supports_vision=True,
+    ),
+    # GPT-5.2 pro — always-reasoning variant
+    "gpt-5.2-pro": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        reasoning_effort_values=("medium", "high", "xhigh"),
+        default_reasoning_effort="medium",
+        supports_vision=True,
+    ),
+    # GPT-5.3 — same capabilities as 5.2 (matches gpt-5.3-chat-latest, codex)
+    "gpt-5.3": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
+        default_reasoning_effort="none",
+        supports_vision=True,
+    ),
+    # GPT-5.4 — 1M context window, native tool search
+    "gpt-5.4": ModelCapabilities(
+        context_window=1050000,
+        max_output_tokens=128000,
+        reasoning_effort_values=("none", "low", "medium", "high", "xhigh"),
+        default_reasoning_effort="none",
+        supports_tool_search=True,
+        supports_vision=True,
+    ),
+    # GPT-5.4 pro — always-reasoning, 1M context, native tool search
+    "gpt-5.4-pro": ModelCapabilities(
+        context_window=1050000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        reasoning_effort_values=("medium", "high", "xhigh"),
+        default_reasoning_effort="medium",
+        supports_tool_search=True,
+        supports_vision=True,
+    ),
+    # O-series reasoning models
+    "o1": ModelCapabilities(
+        context_window=200000,
+        max_output_tokens=100000,
+        supports_temperature=False,
+        supports_streaming=False,
+        supports_vision=True,
+    ),
+    "o1-mini": ModelCapabilities(
+        context_window=128000,
+        max_output_tokens=65536,
+        supports_temperature=False,
+        supports_streaming=False,
+        supports_vision=True,
+    ),
+    "o3": ModelCapabilities(
+        context_window=200000,
+        max_output_tokens=100000,
+        supports_temperature=False,
+        supports_vision=True,
+    ),
+    "o3-mini": ModelCapabilities(
+        context_window=200000,
+        max_output_tokens=100000,
+        supports_temperature=False,
+        supports_vision=True,
+    ),
+    "o3-pro": ModelCapabilities(
+        context_window=200000,
+        max_output_tokens=100000,
+        supports_temperature=False,
+        supports_streaming=False,
+        supports_vision=True,
+    ),
+    "o4-mini": ModelCapabilities(
+        context_window=200000,
+        max_output_tokens=100000,
+        supports_temperature=False,
+        supports_vision=True,
+    ),
+    # Search models — always search on every request, no reasoning_effort
+    "gpt-5-search-api": ModelCapabilities(
+        context_window=400000,
+        max_output_tokens=128000,
+        supports_temperature=False,
+        supports_web_search=True,
+        reasoning_effort_values=(),
+        supports_vision=True,
+    ),
+}
+
+# Default for unknown models (local servers: vLLM, llama.cpp, etc.)
+OPENAI_DEFAULT = ModelCapabilities()
+
+
+def lookup_openai_capabilities(model: str) -> ModelCapabilities:
+    """Find capabilities for *model* by longest prefix match."""
+    return _lookup_capabilities(model, OPENAI_CAPABILITIES, OPENAI_DEFAULT)
+
+
+# ---------------------------------------------------------------------------
+# Temperature and reasoning effort gating
+# ---------------------------------------------------------------------------
+
+
+def apply_temperature(
+    kwargs: dict[str, Any],
+    caps: ModelCapabilities,
+    temperature: float,
+    reasoning_effort: str,
+) -> None:
+    """Conditionally add temperature to *kwargs*.
+
+    - Models with ``supports_temperature=False`` (GPT-5 base, O-series)
+      never receive temperature.
+    - Models that list ``"none"`` in their effort values (GPT-5.1/5.2)
+      only receive temperature when reasoning is inactive.
+    """
+    if not caps.supports_temperature:
+        return
+    if "none" in caps.reasoning_effort_values and reasoning_effort not in ("none", ""):
+        return  # Skip temperature when reasoning is active
+    kwargs["temperature"] = temperature
+
+
+def resolve_reasoning_effort(caps: ModelCapabilities, reasoning_effort: str) -> str | None:
+    """Return the validated reasoning effort value, or ``None`` to omit.
+
+    Validates against supported values and falls back to model default.
+    """
+    if not caps.reasoning_effort_values or not reasoning_effort or reasoning_effort == "none":
+        return None
+    if reasoning_effort in caps.reasoning_effort_values:
+        return reasoning_effort
+    if caps.default_reasoning_effort and caps.default_reasoning_effort != "none":
+        return caps.default_reasoning_effort
+    return None
+
+
+def apply_temperature_and_effort(
+    kwargs: dict[str, Any],
+    caps: ModelCapabilities,
+    temperature: float,
+    reasoning_effort: str,
+) -> None:
+    """Conditionally add temperature and reasoning_effort to *kwargs*.
+
+    Chat Completions API version — reasoning effort is a flat parameter.
+    """
+    apply_temperature(kwargs, caps, temperature, reasoning_effort)
+    effort = resolve_reasoning_effort(caps, reasoning_effort)
+    if effort:
+        kwargs["reasoning_effort"] = effort
+
+
+# ---------------------------------------------------------------------------
+# Cache retention
+# ---------------------------------------------------------------------------
+
+
+def apply_cache_retention(kwargs: dict[str, Any], model: str) -> None:
+    """Enable 24-hour extended prompt cache retention for GPT-5.x models.
+
+    OpenAI caching is automatic (no code changes for basic caching), but
+    the default TTL is only 5-10 minutes.  Extended retention keeps cached
+    KV tensors for up to 24 hours at no additional cost, which is valuable
+    for workstreams with bursty activity patterns.
+    """
+    if model.startswith("gpt-5"):
+        kwargs["prompt_cache_retention"] = "24h"
+
+
+# ---------------------------------------------------------------------------
+# Tool search (native deferred loading)
+# ---------------------------------------------------------------------------
+
+
+def apply_tool_search(
+    caps: ModelCapabilities,
+    tools: list[dict[str, Any]] | None,
+    deferred_names: frozenset[str] | None = None,
+) -> list[dict[str, Any]] | None:
+    """Mark deferred tools with ``defer_loading: true`` for native search.
+
+    For GPT-5.4+ models that support tool search, OpenAI's API handles
+    discovery automatically — no explicit search tool is needed.
+    """
+    if not caps.supports_tool_search or not deferred_names or not tools:
+        return tools
+    result = []
+    for tool in tools:
+        name = tool.get("function", {}).get("name", "")
+        if name in deferred_names:
+            result.append({**tool, "defer_loading": True})
+        else:
+            result.append(tool)
+    return result
+
+
+# ---------------------------------------------------------------------------
+# Citation formatting
+# ---------------------------------------------------------------------------
+
+
+def format_citations(content: str, annotations: list[Any]) -> str:
+    """Append url_citation sources as footnotes at the end of the content."""
+    seen_urls: set[str] = set()
+    sources: list[str] = []
+    for ann in annotations:
+        ann_type = getattr(ann, "type", None)
+        if ann_type == "url_citation":
+            title: str = ""
+            url: str = ""
+            citation = getattr(ann, "url_citation", None)
+            if citation is not None:
+                # Chat Completions API: nested url_citation object
+                title = getattr(citation, "title", "") or ""
+                url = getattr(citation, "url", "") or ""
+            elif hasattr(ann, "url") and isinstance(getattr(ann, "url", None), str):
+                # Responses API: attributes directly on the annotation
+                title = getattr(ann, "title", "") or ""
+                url = getattr(ann, "url", "") or ""
+            if url and url not in seen_urls:
+                seen_urls.add(url)
+                sources.append(f"[{title}]({url})" if title else url)
+    if sources:
+        content += "\n\nSources:\n" + "\n".join(f"- {s}" for s in sources)
+    return content
+
+
+# ---------------------------------------------------------------------------
+# Message sanitisation (Chat Completions specific but shared for compat)
+# ---------------------------------------------------------------------------
+
+
+def sanitize_messages(
+    messages: list[dict[str, Any]],
+) -> list[dict[str, Any]]:
+    """Ensure assistant messages always have ``content`` or ``tool_calls``.
+
+    OpenAI-compatible APIs reject assistant messages that have neither.
+    This is a defensive catch-all; the upstream layers should already
+    guarantee well-formed messages.
+    """
+    out: list[dict[str, Any]] = []
+    for msg in messages:
+        if (
+            msg.get("role") == "assistant"
+            and msg.get("content") is None
+            and not msg.get("tool_calls")
+        ):
+            msg = {**msg, "content": ""}
+        out.append(msg)
+    return out
+
+
+# ---------------------------------------------------------------------------
+# Usage extraction
+# ---------------------------------------------------------------------------
+
+
+def extract_usage(usage_obj: Any) -> UsageInfo | None:
+    """Normalize usage from either Chat Completions or Responses API.
+
+    Chat Completions uses ``prompt_tokens`` / ``completion_tokens``.
+    Responses API uses ``input_tokens`` / ``output_tokens``.
+    We check for each in order, preferring the real SDK attribute names.
+    """
+    if usage_obj is None:
+        return None
+
+    # Token counts — prefer Chat Completions names, fall back to Responses API
+    pt = getattr(usage_obj, "prompt_tokens", None)
+    if not isinstance(pt, int):
+        pt = getattr(usage_obj, "input_tokens", None)
+    ct = getattr(usage_obj, "completion_tokens", None)
+    if not isinstance(ct, int):
+        ct = getattr(usage_obj, "output_tokens", None)
+    tt = getattr(usage_obj, "total_tokens", None)
+    if not isinstance(pt, int) or not isinstance(ct, int):
+        return None
+
+    # Cache tokens — Chat Completions: prompt_tokens_details.cached_tokens,
+    # Responses API: input_tokens_details.cached_tokens
+    ptd = getattr(usage_obj, "prompt_tokens_details", None)
+    if ptd is None:
+        ptd = getattr(usage_obj, "input_tokens_details", None)
+    cached = getattr(ptd, "cached_tokens", 0) if ptd is not None else 0
+
+    return UsageInfo(
+        prompt_tokens=pt,
+        completion_tokens=ct,
+        total_tokens=tt if isinstance(tt, int) else (pt + ct),
+        cache_read_tokens=cached if isinstance(cached, int) else 0,
+    )
+
+
+# ---------------------------------------------------------------------------
+# Retryable error names (shared across both OpenAI providers)
+# ---------------------------------------------------------------------------
+
+RETRYABLE_ERROR_NAMES: frozenset[str] = frozenset(
+    {
+        "APIError",
+        "APIConnectionError",
+        "RateLimitError",
+        "Timeout",
+        "APITimeoutError",
+    }
+)

turnstone/core/providers/_openai_responses.py

@@ -0,0 +1,556 @@
+"""Responses API provider — for commercial OpenAI models (GPT-5.x, O-series).
+
+Uses the OpenAI Responses API (``/v1/responses``) which natively supports
+reasoning, tool use, web search, and tool search without the limitations
+of the Chat Completions endpoint.
+"""
+
+from __future__ import annotations
+
+import json
+from typing import TYPE_CHECKING, Any
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+import structlog
+
+from turnstone.core.providers._openai_common import (
+    RETRYABLE_ERROR_NAMES,
+    apply_cache_retention,
+    apply_temperature,
+    apply_tool_search,
+    extract_usage,
+    format_citations,
+    lookup_openai_capabilities,
+    resolve_reasoning_effort,
+)
+from turnstone.core.providers._protocol import (
+    CompletionResult,
+    ModelCapabilities,
+    StreamChunk,
+    ToolCallDelta,
+)
+
+log = structlog.get_logger(__name__)
+
+
+def _convert_content_parts(parts: list[Any]) -> list[dict[str, Any]]:
+    """Convert Chat Completions content parts to Responses API format.
+
+    Handles text and image_url parts.  The Responses API uses
+    ``input_image`` instead of ``image_url``.
+    """
+    converted: list[dict[str, Any]] = []
+    for part in parts:
+        if not isinstance(part, dict):
+            continue
+        ptype = part.get("type", "")
+        if ptype == "text":
+            converted.append({"type": "input_text", "text": part.get("text", "")})
+        elif ptype == "image_url":
+            url_data = part.get("image_url", {})
+            url = url_data.get("url", "") if isinstance(url_data, dict) else ""
+            converted.append({"type": "input_image", "image_url": url})
+        else:
+            converted.append(part)
+    return converted
+
+
+class OpenAIResponsesProvider:
+    """Provider for commercial OpenAI models via the Responses API.
+
+    Translates between turnstone's internal OpenAI Chat Completions-like
+    message format and the Responses API input/output format.
+    """
+
+    @property
+    def provider_name(self) -> str:
+        return "openai"
+
+    def get_capabilities(self, model: str) -> ModelCapabilities:
+        return lookup_openai_capabilities(model)
+
+    # -- message conversion --------------------------------------------------
+
+    @staticmethod
+    def _convert_messages(
+        messages: list[dict[str, Any]],
+    ) -> tuple[str | None, list[dict[str, Any]]]:
+        """Convert Chat Completions messages to Responses API input items.
+
+        Returns ``(instructions, input_items)`` where *instructions* is the
+        concatenated system/developer messages (or ``None``) and *input_items*
+        is the Responses API ``input`` array.
+        """
+        instructions_parts: list[str] = []
+        items: list[dict[str, Any]] = []
+
+        for msg in messages:
+            role = msg.get("role", "")
+            content = msg.get("content")
+
+            if role in ("system", "developer"):
+                if isinstance(content, str) and content:
+                    instructions_parts.append(content)
+                elif isinstance(content, list):
+                    # Content parts — extract text
+                    for part in content:
+                        if isinstance(part, dict) and part.get("type") == "text":
+                            instructions_parts.append(part["text"])
+                continue
+
+            if role == "user":
+                item: dict[str, Any] = {"type": "message", "role": "user"}
+                if isinstance(content, str):
+                    item["content"] = content
+                elif isinstance(content, list):
+                    # Vision: content parts (text + image_url)
+                    item["content"] = _convert_content_parts(content)
+                else:
+                    item["content"] = content or ""
+                items.append(item)
+
+            elif role == "assistant":
+                # With store=False, provider_blocks cannot be replayed as input
+                # (output format != input format, and IDs aren't persisted).
+                # Rebuild from the normalized content/tool_calls instead.
+
+                # Text content → assistant message (plain string for input)
+                if content:
+                    items.append(
+                        {
+                            "type": "message",
+                            "role": "assistant",
+                            "content": content,
+                        }
+                    )
+
+                # Tool calls → function_call items
+                for tc in msg.get("tool_calls") or []:
+                    func = tc.get("function", {})
+                    items.append(
+                        {
+                            "type": "function_call",
+                            "call_id": tc.get("id", ""),
+                            "name": func.get("name", ""),
+                            "arguments": func.get("arguments", ""),
+                        }
+                    )
+
+            elif role == "tool":
+                # Tool result → function_call_output
+                output = content
+                if isinstance(content, list):
+                    # Structured content (e.g. vision) — serialize to string
+                    output = json.dumps(content)
+                items.append(
+                    {
+                        "type": "function_call_output",
+                        "call_id": msg.get("tool_call_id", ""),
+                        "output": output or "",
+                    }
+                )
+
+        instructions = "\n\n".join(instructions_parts) if instructions_parts else None
+        return instructions, items
+
+    # -- tool conversion -----------------------------------------------------
+
+    @staticmethod
+    def _convert_tools(
+        tools: list[dict[str, Any]] | None,
+        caps: ModelCapabilities,
+    ) -> list[dict[str, Any]] | None:
+        """Convert Chat Completions tool format to Responses API format.
+
+        Chat Completions: ``{"type": "function", "function": {"name", "description", "parameters"}}``
+        Responses API:    ``{"type": "function", "name", "description", "parameters", "strict": false}``
+
+        Also handles web_search injection for models that support it.
+        """
+        if not tools:
+            return None
+
+        converted: list[dict[str, Any]] = []
+        has_web_search_func = False
+
+        for tool in tools:
+            func = tool.get("function")
+            if not func:
+                converted.append(tool)
+                continue
+
+            name = func.get("name", "")
+
+            # web_search function tool → native web_search_tool
+            if name == "web_search" and caps.supports_web_search:
+                has_web_search_func = True
+                continue
+
+            item: dict[str, Any] = {
+                "type": "function",
+                "name": name,
+                "description": func.get("description", ""),
+                "parameters": func.get("parameters", {}),
+                "strict": False,
+            }
+            # Preserve defer_loading for tool search
+            if tool.get("defer_loading"):
+                item["defer_loading"] = True
+            converted.append(item)
+
+        # Inject native web search tool
+        if has_web_search_func or caps.supports_web_search:
+            converted.append({"type": "web_search"})
+
+        # Responses API requires a tool_search tool when defer_loading is used
+        if any(t.get("defer_loading") for t in converted):
+            converted.append({"type": "tool_search"})
+
+        return converted if converted else None
+
+    # -- parameter building --------------------------------------------------
+
+    def _build_kwargs(
+        self,
+        model: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None,
+        max_tokens: int,
+        temperature: float,
+        reasoning_effort: str,
+        deferred_names: frozenset[str] | None,
+    ) -> dict[str, Any]:
+        """Build the kwargs dict for ``client.responses.create/stream``."""
+        caps = self.get_capabilities(model)
+
+        instructions, input_items = self._convert_messages(messages)
+        tools = apply_tool_search(caps, tools, deferred_names)
+        converted_tools = self._convert_tools(tools, caps)
+
+        # Ensure web search is always injected for search-capable models,
+        # even when no function tools are registered (e.g. creative mode).
+        if caps.supports_web_search:
+            converted_tools = converted_tools or []
+            if not any(t.get("type") == "web_search" for t in converted_tools):
+                converted_tools.append({"type": "web_search"})
+
+        kwargs: dict[str, Any] = {
+            "model": model,
+            "input": input_items,
+            "max_output_tokens": max_tokens,
+            "store": False,
+        }
+
+        if instructions:
+            kwargs["instructions"] = instructions
+
+        if converted_tools:
+            kwargs["tools"] = converted_tools
+
+        apply_temperature(kwargs, caps, temperature, reasoning_effort)
+
+        # Reasoning effort → {"effort": value} dict (Responses API format)
+        effort = resolve_reasoning_effort(caps, reasoning_effort)
+        if effort:
+            kwargs["reasoning"] = {"effort": effort}
+
+        apply_cache_retention(kwargs, model)
+        return kwargs
+
+    # -- streaming -----------------------------------------------------------
+
+    def create_streaming(
+        self,
+        *,
+        client: Any,
+        model: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.5,
+        reasoning_effort: str = "medium",
+        extra_params: dict[str, Any] | None = None,
+        deferred_names: frozenset[str] | None = None,
+        cancel_ref: list[Any] | None = None,
+    ) -> Iterator[StreamChunk]:
+        if extra_params:
+            log.debug("openai.responses: extra_params ignored (not supported by Responses API)")
+        kwargs = self._build_kwargs(
+            model,
+            messages,
+            tools,
+            max_tokens,
+            temperature,
+            reasoning_effort,
+            deferred_names,
+        )
+        kwargs["stream"] = True
+
+        log.debug(
+            "openai.responses.request",
+            model=model,
+            stream=True,
+            max_tokens=max_tokens,
+            input_items=len(kwargs.get("input", [])),
+            tool_count=len(kwargs.get("tools", [])),
+        )
+
+        stream = client.responses.create(**kwargs)
+        if cancel_ref is not None:
+            cancel_ref.append(stream)
+        return self._iter_stream(stream)
+
+    def _iter_stream(self, stream: Any) -> Iterator[StreamChunk]:
+        """Convert Responses API stream events to StreamChunks."""
+        first = True
+        content_len = 0
+        tool_call_count = 0
+        last_finish: str | None = None
+        completion_tokens: int | None = None
+        # Track tool call indices by call_id for consistent ToolCallDelta.index
+        tool_call_indices: dict[str, int] = {}
+        # Collect output items for provider_blocks
+        provider_blocks: list[dict[str, Any]] = []
+        # Collect annotations across text parts
+        annotations: list[Any] = []
+
+        for event in stream:
+            event_type = getattr(event, "type", "")
+
+            # -- text content deltas --
+            if event_type == "response.output_text.delta":
+                delta_text = getattr(event, "delta", "")
+                if delta_text:
+                    sc = StreamChunk(content_delta=delta_text)
+                    content_len += len(delta_text)
+                    if first:
+                        sc.is_first = True
+                        first = False
+                    yield sc
+                continue
+
+            # -- reasoning deltas --
+            if event_type in (
+                "response.reasoning_text.delta",
+                "response.reasoning_summary_text.delta",
+            ):
+                delta_text = getattr(event, "delta", "")
+                if delta_text:
+                    sc = StreamChunk(reasoning_delta=delta_text)
+                    if first:
+                        sc.is_first = True
+                        first = False
+                    yield sc
+                continue
+
+            # -- new tool call (function_call output item added) --
+            if event_type == "response.output_item.added":
+                item = getattr(event, "item", None)
+                if item and getattr(item, "type", "") == "function_call":
+                    call_id = getattr(item, "call_id", "")
+                    item_id = getattr(item, "id", "")
+                    name = getattr(item, "name", "")
+                    idx = len(tool_call_indices)
+                    # Index by item_id — argument deltas reference this, not call_id
+                    tool_call_indices[item_id] = idx
+                    sc = StreamChunk(
+                        tool_call_deltas=[ToolCallDelta(index=idx, id=call_id, name=name)]
+                    )
+                    tool_call_count += 1
+                    if first:
+                        sc.is_first = True
+                        first = False
+                    yield sc
+                continue
+
+            # -- tool call argument deltas --
+            if event_type == "response.function_call_arguments.delta":
+                item_id = getattr(event, "item_id", "")
+                delta_args = getattr(event, "delta", "")
+                if delta_args:
+                    idx = tool_call_indices.get(item_id, 0)
+                    yield StreamChunk(
+                        tool_call_deltas=[ToolCallDelta(index=idx, arguments_delta=delta_args)]
+                    )
+                continue
+
+            # -- web search status --
+            if event_type == "response.web_search_call.searching":
+                yield StreamChunk(info_delta="[Searching…]")
+                continue
+            if event_type == "response.web_search_call.completed":
+                yield StreamChunk(info_delta="[Search complete]")
+                continue
+
+            # -- output item done (capture for provider_blocks) --
+            if event_type == "response.output_item.done":
+                item = getattr(event, "item", None)
+                if item:
+                    item_dict = item.model_dump() if hasattr(item, "model_dump") else {}
+                    if item_dict:
+                        provider_blocks.append(item_dict)
+                    # Collect annotations from completed text parts
+                    if getattr(item, "type", "") == "message":
+                        for content_part in getattr(item, "content", []):
+                            part_anns = getattr(content_part, "annotations", None)
+                            if part_anns:
+                                annotations.extend(part_anns)
+                continue
+
+            # -- response completed --
+            if event_type == "response.completed":
+                response = getattr(event, "response", None)
+                if response:
+                    status = getattr(response, "status", "completed")
+                    last_finish = "stop" if status == "completed" else "length"
+                    usage = extract_usage(getattr(response, "usage", None))
+                    if usage:
+                        completion_tokens = usage.completion_tokens
+                    sc = StreamChunk(
+                        finish_reason=last_finish,
+                        usage=usage,
+                    )
+                    if provider_blocks:
+                        sc.provider_blocks = provider_blocks
+                    yield sc
+                continue
+
+            # -- error --
+            if event_type == "response.failed":
+                response = getattr(event, "response", None)
+                error = getattr(response, "error", None) if response else None
+                error_msg = getattr(error, "message", "Unknown error") if error else "Unknown error"
+                raise RuntimeError(f"Responses API error: {error_msg}")
+
+        log.debug(
+            "openai.responses.response",
+            stream=True,
+            finish_reason=last_finish,
+            content_length=content_len,
+            tool_call_count=tool_call_count,
+            completion_tokens=completion_tokens,
+        )
+
+        # Emit accumulated citations as a final info chunk
+        if annotations:
+            citation_text = format_citations("", annotations).strip()
+            if citation_text:
+                yield StreamChunk(info_delta=citation_text)
+
+    # -- non-streaming -------------------------------------------------------
+
+    def create_completion(
+        self,
+        *,
+        client: Any,
+        model: str,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.5,
+        reasoning_effort: str = "medium",
+        extra_params: dict[str, Any] | None = None,
+        deferred_names: frozenset[str] | None = None,
+    ) -> CompletionResult:
+        if extra_params:
+            log.debug("openai.responses: extra_params ignored (not supported by Responses API)")
+        kwargs = self._build_kwargs(
+            model,
+            messages,
+            tools,
+            max_tokens,
+            temperature,
+            reasoning_effort,
+            deferred_names,
+        )
+
+        log.debug(
+            "openai.responses.request",
+            model=model,
+            stream=False,
+            max_tokens=max_tokens,
+            input_items=len(kwargs.get("input", [])),
+            tool_count=len(kwargs.get("tools", [])),
+        )
+
+        response = client.responses.create(**kwargs)
+        return self._parse_response(response)
+
+    def _parse_response(self, response: Any) -> CompletionResult:
+        """Convert a Responses API ``Response`` object to ``CompletionResult``."""
+        content_parts: list[str] = []
+        tool_calls: list[dict[str, Any]] = []
+        provider_blocks: list[dict[str, Any]] = []
+        all_annotations: list[Any] = []
+
+        for item in getattr(response, "output", []):
+            item_type = getattr(item, "type", "")
+
+            if item_type == "message":
+                for content_part in getattr(item, "content", []):
+                    part_type = getattr(content_part, "type", "")
+                    if part_type == "output_text":
+                        content_parts.append(getattr(content_part, "text", ""))
+                        anns = getattr(content_part, "annotations", None)
+                        if anns:
+                            all_annotations.extend(anns)
+                    elif part_type == "refusal":
+                        content_parts.append(f"[Refused: {getattr(content_part, 'refusal', '')}]")
+
+            elif item_type == "function_call":
+                tool_calls.append(
+                    {
+                        "id": getattr(item, "call_id", ""),
+                        "type": "function",
+                        "function": {
+                            "name": getattr(item, "name", ""),
+                            "arguments": getattr(item, "arguments", ""),
+                        },
+                    }
+                )
+
+            # Capture all output items for provider_blocks (multi-turn)
+            item_dict = item.model_dump() if hasattr(item, "model_dump") else {}
+            if item_dict:
+                provider_blocks.append(item_dict)
+
+        content = "".join(content_parts)
+        if all_annotations:
+            content = format_citations(content, all_annotations)
+
+        status = getattr(response, "status", "completed")
+        finish_reason = "stop" if status == "completed" else "length"
+        usage = extract_usage(getattr(response, "usage", None))
+
+        result = CompletionResult(
+            content=content,
+            tool_calls=tool_calls if tool_calls else None,
+            finish_reason=finish_reason,
+            usage=usage,
+            provider_blocks=provider_blocks,
+        )
+        log.debug(
+            "openai.responses.response",
+            stream=False,
+            finish_reason=finish_reason,
+            content_length=len(content),
+            tool_call_count=len(tool_calls),
+            completion_tokens=usage.completion_tokens if usage else None,
+        )
+        return result
+
+    # -- tool conversion (public interface) ----------------------------------
+
+    def convert_tools(
+        self,
+        tools: list[dict[str, Any]],
+    ) -> list[dict[str, Any]]:
+        return tools  # Conversion happens internally in _build_kwargs
+
+    # -- retryable errors ----------------------------------------------------
+
+    @property
+    def retryable_error_names(self) -> frozenset[str]:
+        return RETRYABLE_ERROR_NAMES

turnstone/core/rule_registry.py

@@ -0,0 +1,245 @@
+"""Rule registry — thread-safe merged view of built-in + DB rules.
+
+Provides the heuristic rule table and output guard pattern set used by
+the intent judge (Facet 1) and output guard (Facet 2).  Built-in rules
+are defined in ``judge.py`` and ``output_guard.py``.  Custom rules are
+stored in the ``heuristic_rules`` and ``output_guard_patterns`` tables.
+
+Merge strategy (per name):
+  - DB row with matching name → replaces built-in
+  - DB row with builtin=1, enabled=0 → disables built-in
+  - DB row with builtin=0 → new custom rule
+  - No DB row → built-in used as-is
+
+The registry is thread-safe: ``reload()`` acquires a lock, rebuilds the
+merged view, then atomically swaps the cached snapshots.
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+import threading
+import types
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any
+
+from turnstone.core.output_guard import OutputGuardPatternDef as OutputGuardPatternDef
+
+if TYPE_CHECKING:
+    from turnstone.core.storage._protocol import StorageBackend
+
+log = logging.getLogger(__name__)
+
+# -- Public dataclasses ------------------------------------------------------
+
+_TIER_ORDER = {"critical": 0, "high": 1, "medium": 2, "low": 3}
+_RE_FLAGS_MAP = {
+    "IGNORECASE": re.IGNORECASE,
+    "MULTILINE": re.MULTILINE,
+    "DOTALL": re.DOTALL,
+}
+
+
+@dataclass(frozen=True)
+class HeuristicRuleDef:
+    """A heuristic pattern-matching rule for intent validation."""
+
+    name: str
+    risk_level: str  # critical/high/medium/low
+    confidence: float  # 0.0-1.0
+    recommendation: str  # approve/review/deny
+    tool_pattern: str  # fnmatch pattern for func_name
+    arg_patterns: list[str]  # regex patterns matched against args
+    intent_template: str  # may use {func_name}, {arg_snippet}
+    reasoning_template: str
+    tier: str  # critical/high/medium/low — evaluation order
+    priority: int = 0  # within-tier ordering (higher = first)
+
+
+def _compile_flags(flags_str: str) -> int:
+    """Parse comma-separated flag names into regex flags integer."""
+    if not flags_str:
+        return 0
+    result = 0
+    for f in flags_str.split(","):
+        f = f.strip()
+        if f in _RE_FLAGS_MAP:
+            result |= _RE_FLAGS_MAP[f]
+    return result
+
+
+class RuleRegistry:
+    """Thread-safe in-memory cache of merged built-in + DB rules.
+
+    When ``storage`` is None (standalone CLI, tests), only built-in rules
+    are used.  Call ``reload()`` after admin writes to refresh the cache.
+    """
+
+    def __init__(self, storage: StorageBackend | None = None) -> None:
+        self._storage = storage
+        self._lock = threading.Lock()
+        self._heuristic_rules: tuple[HeuristicRuleDef, ...] = ()
+        self._output_patterns: dict[str, tuple[OutputGuardPatternDef, ...]] = {}
+        self._version = 0
+        self.reload()
+
+    def reload(self) -> None:
+        """Re-read DB, merge with built-ins, and swap cache atomically."""
+        h_rules = self._merge_heuristic_rules()
+        o_patterns = self._merge_output_patterns()
+        with self._lock:
+            self._heuristic_rules = tuple(h_rules)
+            self._output_patterns = {cat: tuple(pats) for cat, pats in o_patterns.items()}
+            self._version += 1
+
+    @property
+    def heuristic_rules(self) -> tuple[HeuristicRuleDef, ...]:
+        """Immutable snapshot of merged heuristic rules."""
+        return self._heuristic_rules
+
+    @property
+    def output_patterns(
+        self,
+    ) -> types.MappingProxyType[str, tuple[OutputGuardPatternDef, ...]]:
+        """Immutable snapshot of output guard patterns grouped by category."""
+        return types.MappingProxyType(self._output_patterns)
+
+    @property
+    def version(self) -> int:
+        """Monotonic counter incremented on each reload."""
+        return self._version
+
+    # -- Merge logic -----------------------------------------------------------
+
+    def _merge_heuristic_rules(self) -> list[HeuristicRuleDef]:
+        """Merge built-in heuristic rules with DB overrides/custom rules."""
+        from turnstone.core.judge import _HEURISTIC_RULES
+
+        # Start with built-ins keyed by name
+        by_name: dict[str, HeuristicRuleDef] = {}
+        for rule in _HEURISTIC_RULES:
+            by_name[rule.name] = HeuristicRuleDef(
+                name=rule.name,
+                risk_level=rule.risk_level,
+                confidence=rule.confidence,
+                recommendation=rule.recommendation,
+                tool_pattern=rule.tool_pattern,
+                arg_patterns=list(rule.arg_patterns),
+                intent_template=rule.intent_template,
+                reasoning_template=rule.reasoning_template,
+                tier=rule.risk_level,  # built-in tier = risk_level
+                priority=0,
+            )
+
+        if self._storage is None:
+            return self._sort_heuristic(list(by_name.values()))
+
+        # Overlay DB rules
+        try:
+            db_rules = self._storage.list_heuristic_rules()
+        except Exception:
+            log.exception("Failed to load heuristic rules from storage")
+            return self._sort_heuristic(list(by_name.values()))
+
+        disabled_builtins: set[str] = set()
+        for row in db_rules:
+            name = row["name"]
+            if row.get("builtin") and not row.get("enabled"):
+                disabled_builtins.add(name)
+                continue
+            if not row.get("enabled"):
+                continue
+            import json
+
+            arg_patterns_raw: Any = row.get("arg_patterns", "[]")
+            if isinstance(arg_patterns_raw, str):
+                try:
+                    arg_patterns_raw = json.loads(arg_patterns_raw)
+                except (json.JSONDecodeError, TypeError):
+                    arg_patterns_raw = []
+            by_name[name] = HeuristicRuleDef(
+                name=name,
+                risk_level=row.get("risk_level", "medium"),
+                confidence=row.get("confidence", 0.7),
+                recommendation=row.get("recommendation", "review"),
+                tool_pattern=row.get("tool_pattern", "*"),
+                arg_patterns=arg_patterns_raw,
+                intent_template=row.get("intent_template", ""),
+                reasoning_template=row.get("reasoning_template", ""),
+                tier=row.get("tier", "medium"),
+                priority=row.get("priority", 0),
+            )
+
+        for name in disabled_builtins:
+            by_name.pop(name, None)
+
+        return self._sort_heuristic(list(by_name.values()))
+
+    @staticmethod
+    def _sort_heuristic(rules: list[HeuristicRuleDef]) -> list[HeuristicRuleDef]:
+        """Sort: critical first, then high, medium, low; within tier by priority desc."""
+        return sorted(
+            rules,
+            key=lambda r: (_TIER_ORDER.get(r.tier, 4), -r.priority),
+        )
+
+    def _merge_output_patterns(self) -> dict[str, list[OutputGuardPatternDef]]:
+        """Merge built-in output guard patterns with DB overrides/custom patterns."""
+        from turnstone.core.output_guard import _BUILTIN_OG_PATTERNS
+
+        by_name: dict[str, OutputGuardPatternDef] = {}
+        for pat in _BUILTIN_OG_PATTERNS:
+            by_name[pat.name] = pat
+
+        if self._storage is None:
+            return self._group_by_category(list(by_name.values()))
+
+        try:
+            db_patterns = self._storage.list_output_guard_patterns()
+        except Exception:
+            log.exception("Failed to load output guard patterns from storage")
+            return self._group_by_category(list(by_name.values()))
+
+        disabled_builtins: set[str] = set()
+        for row in db_patterns:
+            name = row["name"]
+            if row.get("builtin") and not row.get("enabled"):
+                disabled_builtins.add(name)
+                continue
+            if not row.get("enabled"):
+                continue
+            try:
+                flags_int = _compile_flags(row.get("pattern_flags", ""))
+                compiled = re.compile(row["pattern"], flags_int)
+            except re.error:
+                log.warning("Invalid regex in output guard pattern %r, skipping", name)
+                continue
+            by_name[name] = OutputGuardPatternDef(
+                name=name,
+                category=row.get("category", "info_disclosure"),
+                risk_level=row.get("risk_level", "medium"),
+                compiled=compiled,
+                flag_name=row.get("flag_name", name),
+                annotation=row.get("annotation", ""),
+                is_credential=bool(row.get("is_credential")),
+                redact_label=row.get("redact_label", ""),
+                priority=row.get("priority", 0),
+            )
+
+        for name in disabled_builtins:
+            by_name.pop(name, None)
+
+        return self._group_by_category(list(by_name.values()))
+
+    @staticmethod
+    def _group_by_category(
+        patterns: list[OutputGuardPatternDef],
+    ) -> dict[str, list[OutputGuardPatternDef]]:
+        """Group patterns by category, sorted by priority desc within each."""
+        grouped: dict[str, list[OutputGuardPatternDef]] = {}
+        for pat in patterns:
+            grouped.setdefault(pat.category, []).append(pat)
+        for cat in grouped:
+            grouped[cat].sort(key=lambda p: -p.priority)
+        return grouped

turnstone/core/sandbox.py

@@ -236,14 +236,14 @@ def _math_exec_in_process(code: str, result_queue: multiprocessing.Queue[tuple[s
             ):
                 ns[name] = getattr(sympy, name)
         except ImportError:
-            pass
+            pass  # optional dependency
 
         try:
             import numpy as _np
 
             ns["np"] = ns["numpy"] = _np
         except ImportError:
-            pass
+            pass  # optional dependency
 
         try:
             import scipy  # type: ignore[import-untyped]
@@ -260,7 +260,7 @@ def _math_exec_in_process(code: str, result_queue: multiprocessing.Queue[tuple[s
             ns["gamma"] = scipy.special.gamma
             ns["beta"] = scipy.special.beta
         except ImportError:
-            pass
+            pass  # optional dependency
 
         # Strip __builtins__ from all pre-imported modules so
         # module.__builtins__['__import__'] can't bypass _safe_import.

turnstone/core/session.py

@@ -98,7 +98,7 @@ if TYPE_CHECKING:
     from collections.abc import Iterator
 
     from turnstone.core.config_store import ConfigStore
-    from turnstone.core.healthcheck import BackendHealthMonitor
+    from turnstone.core.healthcheck import BackendHealthTracker, HealthTrackerRegistry
     from turnstone.core.judge import IntentJudge, JudgeConfig
     from turnstone.core.mcp_client import MCPClientManager
     from turnstone.core.model_registry import ModelConfig, ModelRegistry
@@ -288,7 +288,7 @@ class ChatSession:
         mcp_client: MCPClientManager | None = None,
         registry: ModelRegistry | None = None,
         model_alias: str | None = None,
-        health_monitor: BackendHealthMonitor | None = None,
+        health_registry: HealthTrackerRegistry | None = None,
         node_id: str | None = None,
         ws_id: str | None = None,
         tool_search: str = "auto",
@@ -307,12 +307,12 @@ class ChatSession:
         self.model = model
         self._registry = registry
         self._model_alias = model_alias
-        self._health_monitor = health_monitor
+        self._health_registry = health_registry
         # Resolve provider for the current model
         self._provider: LLMProvider = (
             registry.get_provider(model_alias)
             if registry and model_alias
-            else create_provider("openai")
+            else create_provider("openai-compatible")
         )
         self._cached_capabilities: ModelCapabilities | None = None
         self.ui = ui
@@ -340,6 +340,15 @@ class ChatSession:
         self._username = username
         self._client_type = client_type
         self._config_store = config_store
+        # Initialize rule registry for configurable judge rules
+        self._rule_registry = None
+        if config_store is not None:
+            try:
+                from turnstone.core.rule_registry import RuleRegistry
+
+                self._rule_registry = RuleRegistry(storage=config_store.storage)
+            except Exception:
+                log.debug("rule_registry.init_failed", exc_info=True)
         self._memory_config = memory_config or MemoryConfig()
         self._ws_id = ws_id or uuid.uuid4().hex
         self._title_generated = False
@@ -456,7 +465,7 @@ class ChatSession:
     def _judge_cfg(self) -> JudgeConfig | None:
         """Live judge behavioral config — reads from ConfigStore when available.
 
-        LLM client fields (model, provider, base_url, api_key) stay frozen
+        The model alias stays frozen
         from session creation time since changing them would require tearing
         down and rebuilding the IntentJudge instance.
         """
@@ -471,9 +480,6 @@ class ChatSession:
         return JudgeConfig(
             enabled=cs.get("judge.enabled"),
             model=jc.model,
-            provider=jc.provider,
-            base_url=jc.base_url,
-            api_key=jc.api_key,
             confidence_threshold=cs.get("judge.confidence_threshold"),
             max_context_ratio=cs.get("judge.max_context_ratio"),
             timeout=cs.get("judge.timeout"),
@@ -886,9 +892,34 @@ class ChatSession:
             self._tool_error_flags[call_id] = True
         self.ui.on_tool_result(call_id, name, output, is_error=is_error)
 
-    def _truncate_output(self, output: str) -> str:
-        """Truncate tool output to self.tool_truncation chars, keeping head + tail."""
+    def _remaining_token_budget(self) -> int:
+        """Estimate how many tokens are available for new content.
+
+        Reserves a response budget (capped at 25% of context window, since
+        ``max_tokens`` is an upper bound, not guaranteed consumption) plus
+        a 5% safety margin.  Returns at least 0.
+        """
+        used = self._system_tokens + sum(self._msg_tokens)
+        response_reserve = min(self.max_tokens, self.context_window // 4)
+        safety_margin = int(self.context_window * 0.05)
+        return max(0, self.context_window - used - response_reserve - safety_margin)
+
+    def _truncate_output(self, output: str, remaining_budget_tokens: int | None = None) -> str:
+        """Truncate tool output, keeping head + tail.
+
+        The effective limit is the *minimum* of:
+        - ``self.tool_truncation`` (fixed cap, defaults to 50% of context)
+        - ``remaining_budget_tokens`` converted to chars (if provided)
+
+        This ensures a single tool result cannot overflow the context window
+        even when the conversation is already partially full.
+        """
         limit = self.tool_truncation
+        if remaining_budget_tokens is not None:
+            budget_chars = int(remaining_budget_tokens * self._chars_per_token)
+            limit = min(limit, budget_chars)
+        if limit <= 0:
+            return f"[Output truncated — {len(output)} chars exceeded context budget]"
         if len(output) <= limit:
             return output
         half = limit // 2
@@ -924,10 +955,8 @@ class ChatSession:
             if asst_msg:
                 snippet += f"\nAssistant: {asst_msg}"
             snippet += "\n\nTitle:"
-            result = self._provider.create_completion(
-                client=self.client,
-                model=self.model,
-                messages=[
+            result = self._utility_completion(
+                [
                     {
                         "role": "system",
                         "content": (
@@ -942,9 +971,6 @@ class ChatSession:
                     {"role": "user", "content": snippet},
                 ],
                 max_tokens=200,
-                temperature=0.3,
-                reasoning_effort="low",
-                extra_params=self._provider_extra_params(reasoning_effort="low"),
             )
             raw = (result.content or "").strip()
             # Take first line, strip quotes
@@ -1076,29 +1102,38 @@ class ChatSession:
         self._chat_template_kwargs_base: dict[str, Any] = {
             "reasoning_effort": self.reasoning_effort,
         }
-        self._chat_template_kwargs: dict[str, Any] = dict(self._chat_template_kwargs_base)
 
         # -- Developer message --
         if self.creative_mode:
             dev_parts = [
                 "# Instructions",
                 "",
-                "You are a creative writing partner. Use the analysis channel to "
-                "think through structure, voice, and intent before drafting.",
+                (
+                    "You are a creative writing partner. Use the analysis channel to "
+                    "think through structure, voice, and intent before drafting."
+                ),
                 "",
                 "Craft principles:",
                 "- Ground scenes in concrete sensory detail — what is seen, heard, felt.",
-                "- Vary rhythm. Short sentences hit hard. Longer ones carry the reader "
-                "through texture and nuance, building toward something.",
-                "- Dialogue should do at least two things: reveal character AND advance "
-                "plot or tension. Cut anything that's just exchanging information.",
-                "- Earn your abstractions. Don't say 'she felt sad' — show the thing "
-                "that makes the reader feel it.",
+                (
+                    "- Vary rhythm. Short sentences hit hard. Longer ones carry the reader "
+                    "through texture and nuance, building toward something."
+                ),
+                (
+                    "- Dialogue should do at least two things: reveal character AND advance "
+                    "plot or tension. Cut anything that's just exchanging information."
+                ),
+                (
+                    "- Earn your abstractions. Don't say 'she felt sad' — show the thing "
+                    "that makes the reader feel it."
+                ),
                 "- Trust subtext. Leave room for the reader.",
                 "",
-                "Match the user's genre and tone. If they want literary fiction, write "
-                "literary fiction. If they want pulp, write pulp with conviction. "
-                "Never condescend to the form.",
+                (
+                    "Match the user's genre and tone. If they want literary fiction, write "
+                    "literary fiction. If they want pulp, write pulp with conviction. "
+                    "Never condescend to the form."
+                ),
             ]
         else:
             # Compose system message from modular components
@@ -1110,7 +1145,7 @@ class ChatSession:
                 if storage:
                     db_policies = storage.list_prompt_policies()
             except Exception:
-                pass
+                log.debug("Failed to load prompt policies from storage", exc_info=True)
             now = datetime.now().astimezone()
             ctx = SessionContext(
                 current_datetime=now.strftime("%Y-%m-%dT%H:%M"),
@@ -1272,15 +1307,47 @@ class ChatSession:
         reasoning_effort: str | None = None,
         provider: LLMProvider | None = None,
     ) -> dict[str, Any] | None:
-        """Build provider-specific extra parameters."""
+        """Build provider-specific extra parameters.
+
+        ``chat_template_kwargs`` is only meaningful for local model servers
+        (``openai-compatible``).  Commercial OpenAI rejects it as an unknown
+        parameter, and handles ``reasoning_effort`` natively.
+        """
         prov = provider or self._provider
-        if prov.provider_name == "openai":
+        if prov.provider_name == "openai-compatible":
             kwargs = dict(self._chat_template_kwargs_base)
             if reasoning_effort:
                 kwargs["reasoning_effort"] = reasoning_effort
             return {"chat_template_kwargs": kwargs}
         return None
 
+    def _utility_completion(
+        self,
+        messages: list[dict[str, Any]],
+        *,
+        max_tokens: int = 4096,
+        temperature: float = 0.3,
+        reasoning_effort: str = "low",
+    ) -> CompletionResult:
+        """Run a lightweight internal completion (title gen, compaction, extraction).
+
+        Threads ``reasoning_effort`` through both the direct keyword (for
+        commercial providers) and ``extra_params`` (for local model servers)
+        so callers don't need to duplicate it.  ``max_tokens`` is clamped to
+        the model's advertised output limit so small models don't error.
+        """
+        caps = self._get_capabilities()
+        clamped = min(max_tokens, caps.max_output_tokens) if caps.max_output_tokens else max_tokens
+        return self._provider.create_completion(
+            client=self.client,
+            model=self.model,
+            messages=messages,
+            max_tokens=clamped,
+            temperature=temperature,
+            reasoning_effort=reasoning_effort,
+            extra_params=self._provider_extra_params(reasoning_effort=reasoning_effort),
+        )
+
     # -- tool search helpers --------------------------------------------------
 
     def _get_active_tools(self) -> list[dict[str, Any]] | None:
@@ -1340,45 +1407,90 @@ class ChatSession:
     _MAX_RETRIES = 3
     _RETRY_BASE_DELAY = 1.0  # seconds
 
+    def _get_health_tracker(self) -> BackendHealthTracker | None:
+        """Get the health tracker for this session's current backend.
+
+        Uses a read-only lookup — only returns trackers that were already
+        created eagerly at startup or during model reload.
+
+        Returns ``None`` when no health registry is configured, the model
+        alias is unknown, or no tracker exists for this backend yet.
+        """
+        if not self._health_registry or not self._registry or not self._model_alias:
+            return None
+        return self._health_registry.get_tracker_for_alias(self._registry, self._model_alias)
+
     def _create_stream_with_retry(self, msgs: list[dict[str, Any]]) -> Iterator[StreamChunk]:
         """Create a streaming request with retry on transient errors.
 
         If all retries fail and a fallback chain is configured, tries each
-        fallback model in order before giving up.  Checks the circuit breaker
-        before attempting a call — fast-fails when the backend is unreachable.
+        fallback model in order before giving up.  Records success/failure
+        on the per-backend health tracker for observability.
         """
-        # Circuit breaker check — fast-fail if backend is known to be down
-        if self._health_monitor and not self._health_monitor.acquire_request_permit():
-            raise ConnectionError("Backend unreachable (circuit breaker open)")
+        tracker = self._get_health_tracker()
 
         try:
             result = self._try_stream(self.client, self.model, msgs)
-            if self._health_monitor:
-                self._health_monitor.record_success()
+            if tracker:
+                tracker.record_success()
             return result
-        except BaseException as primary_err:
-            if self._health_monitor:
-                self._health_monitor.record_failure()
-            if isinstance(primary_err, (KeyboardInterrupt, SystemExit)):
-                raise
+        except Exception as primary_err:
+            if tracker:
+                tracker.record_failure()
             if not self._registry or not self._registry.fallback:
                 raise
-            # Try each fallback model.  Fallbacks may use different backends;
-            # we intentionally do NOT call record_success/failure for fallbacks —
-            # recovery of the primary backend is detected by the background probe.
+            # Try each fallback model.  Prefer non-degraded backends first,
+            # but still try degraded ones as a last resort.
+            degraded_fallbacks: list[str] = []
             for alias in self._registry.fallback:
                 if alias == self._model_alias:
                     continue
-                try:
-                    fb_client, fb_model, _ = self._registry.resolve(alias)
-                    fb_provider = self._registry.get_provider(alias)
-                    self.ui.on_info(f"[Primary model failed, falling back to {alias}]")
-                    return self._try_stream(fb_client, fb_model, msgs, provider=fb_provider)
-                except Exception as fb_err:
-                    self.ui.on_info(f"[Fallback {alias} also failed: {fb_err}]")
-                    continue
+                # Skip degraded backends on the first pass
+                if self._health_registry:
+                    fb_tracker = self._health_registry.get_tracker_for_alias(self._registry, alias)
+                    if fb_tracker and fb_tracker.is_degraded:
+                        degraded_fallbacks.append(alias)
+                        continue
+                stream = self._try_fallback(alias, msgs)
+                if stream is not None:
+                    return stream
+            # Second pass: try degraded backends as last resort
+            for alias in degraded_fallbacks:
+                self.ui.on_info(f"[Fallback {alias} is degraded, trying anyway]")
+                stream = self._try_fallback(alias, msgs)
+                if stream is not None:
+                    return stream
             raise primary_err
 
+    def _try_fallback(self, alias: str, msgs: list[dict[str, Any]]) -> Iterator[StreamChunk] | None:
+        """Attempt a single fallback model. Returns stream or None.
+
+        Records success/failure on the fallback's health tracker so
+        the two-pass ordering (healthy-first, then degraded) learns
+        across request cycles.
+
+        Caller must ensure ``self._registry`` is not ``None``.
+        """
+        assert self._registry is not None
+        fb_tracker = (
+            self._health_registry.get_tracker_for_alias(self._registry, alias)
+            if self._health_registry
+            else None
+        )
+        try:
+            fb_client, fb_model, _ = self._registry.resolve(alias)
+            fb_provider = self._registry.get_provider(alias)
+            self.ui.on_info(f"[Primary model failed, falling back to {alias}]")
+            result = self._try_stream(fb_client, fb_model, msgs, provider=fb_provider)
+            if fb_tracker:
+                fb_tracker.record_success()
+            return result
+        except Exception as fb_err:
+            if fb_tracker:
+                fb_tracker.record_failure()
+            self.ui.on_info(f"[Fallback {alias} also failed: {fb_err}]")
+            return None
+
     def _try_stream(
         self,
         client: Any,
@@ -1546,7 +1658,44 @@ class ChatSession:
                 self._emit_state("thinking")
                 self.ui.on_thinking_start()
                 try:
-                    stream = self._create_stream_with_retry(msgs)
+                    try:
+                        stream = self._create_stream_with_retry(msgs)
+                    except Exception as ctx_err:
+                        # Context overflow recovery: if the API rejects the
+                        # request due to exceeding the context window, compact
+                        # the conversation and retry once.
+                        err_text = str(ctx_err).lower()
+                        is_ctx_overflow = any(
+                            s in err_text
+                            for s in (
+                                "context length",
+                                "maximum context",
+                                "too many tokens",
+                                "prompt is too long",
+                                "input tokens",
+                            )
+                        )
+                        if not is_ctx_overflow:
+                            raise
+                        log.warning(
+                            "Context overflow detected (%s), compacting and retrying",
+                            type(ctx_err).__name__,
+                        )
+                        self.ui.on_info("\n[Context overflow — auto-compacting and retrying]")
+                        # Stop thinking indicator before compact (which has
+                        # its own thinking start/stop) to avoid nested spinners.
+                        self.ui.on_thinking_stop()
+                        try:
+                            self._compact_messages(auto=True)
+                            msgs = self._full_messages()
+                            self.ui.on_thinking_start()
+                            stream = self._create_stream_with_retry(msgs)
+                        except Exception:
+                            log.warning(
+                                "Compact-and-retry failed, raising original error",
+                                exc_info=True,
+                            )
+                            raise ctx_err from None
                     assistant_msg = self._stream_response(stream, my_generation)
                 finally:
                     # Only clear if this generation is still active —
@@ -1712,6 +1861,12 @@ class ChatSession:
                                         tc_id, p["text"], _tc_names.get(tc_id, "")
                                     )
 
+                    # Safety truncation: clamp output to remaining context budget
+                    # so a single large result cannot overflow the context window.
+                    if isinstance(output, str):
+                        budget = self._remaining_token_budget()
+                        output = self._truncate_output(output, remaining_budget_tokens=budget)
+
                     tool_msg: dict[str, Any] = {
                         "role": "tool",
                         "tool_call_id": tc_id,
@@ -2482,14 +2637,9 @@ class ChatSession:
             result: CompletionResult | None = None
             for attempt in range(self._MAX_RETRIES + 1):
                 try:
-                    result = self._provider.create_completion(
-                        client=self.client,
-                        model=self.model,
-                        messages=summary_msgs,
+                    result = self._utility_completion(
+                        summary_msgs,
                         max_tokens=summary_max_tokens,
-                        temperature=0.3,
-                        reasoning_effort="low",
-                        extra_params=self._provider_extra_params(reasoning_effort="low"),
                     )
                     break
                 except Exception as e:
@@ -2568,7 +2718,6 @@ class ChatSession:
             return None
         if self._judge is not None:
             return self._judge
-            return None
         # Frozen config required for IntentJudge init (LLM client fields).
         # _judge_cfg already returns None when _judge_config is None, but
         # this guard makes the dependency explicit for type narrowing.
@@ -2584,6 +2733,8 @@ class ChatSession:
                 session_client=self.client,
                 session_model=self.model,
                 context_window=caps.context_window,
+                rule_registry=self._rule_registry,
+                model_registry=self._registry,
             )
         except Exception:
             log.warning("judge.init_failed", exc_info=True)
@@ -2669,7 +2820,13 @@ class ChatSession:
         """
         from turnstone.core.output_guard import evaluate_output
 
-        assessment = evaluate_output(output, func_name=func_name, call_id=call_id)
+        og_patterns = None
+        rule_reg = self._rule_registry
+        if rule_reg is not None:
+            og_patterns = rule_reg.output_patterns
+        assessment = evaluate_output(
+            output, func_name=func_name, call_id=call_id, patterns=og_patterns
+        )
         if assessment.risk_level == "none":
             return output
 
@@ -2787,7 +2944,8 @@ class ChatSession:
                 continue
 
             cid, output = results[i]
-            assert isinstance(output, str)  # plan always returns text
+            if not isinstance(output, str):
+                raise TypeError(f"plan_agent must return str, got {type(output).__name__}")
             plan_path = f".plan-{self._ws_id}.md"
 
             if not self.auto_approve:
@@ -2840,7 +2998,10 @@ class ChatSession:
                     with open(plan_path, "w") as f:
                         f.write(output)
                 except OSError:
-                    pass
+                    log.warning("Failed to write plan to %s", plan_path, exc_info=True)
+                    output += "\n\n---\nPlan could not be saved to disk."
+                    results[i] = (cid, output)
+                    continue
 
             # Always include file path in the tool result so the
             # outer model knows where the plan lives on disk.
@@ -2919,7 +3080,7 @@ class ChatSession:
                     "call_id": call_id,
                     "func_name": func_name,
                     "header": f"\u2717 {func_name}: {exc}",
-                    "preview": f"    {RED}{preview}{RESET}",
+                    "preview": f"    {preview}",
                     "needs_approval": False,
                     "error": (
                         f"JSON parse error for tool '{func_name}': {exc}\n"
@@ -3309,9 +3470,10 @@ class ChatSession:
                 "error": "Error: provide old_string/new_string or edits array, not both",
             }
         if has_batch:
-            assert isinstance(raw_edits, list)
+            # raw_edits is guaranteed to be a list by the has_batch check above
+            batch_edits: list[Any] = raw_edits  # type: ignore[assignment]
             edits: list[dict[str, Any]] = []
-            for i, e in enumerate(raw_edits):
+            for i, e in enumerate(batch_edits):
                 if not isinstance(e, dict):
                     return {
                         "call_id": call_id,
@@ -3511,7 +3673,7 @@ class ChatSession:
                 "call_id": call_id,
                 "func_name": "man",
                 "header": "\u2717 man: invalid page name",
-                "preview": f"    {RED}{page}{RESET}",
+                "preview": f"    {page}",
                 "needs_approval": False,
                 "error": f"Error: invalid page name {page!r}",
             }
@@ -3557,7 +3719,7 @@ class ChatSession:
                 "call_id": call_id,
                 "func_name": "web_fetch",
                 "header": "\u2717 web_fetch: invalid url",
-                "preview": f"    {RED}{url}{RESET}",
+                "preview": f"    {url}",
                 "needs_approval": False,
                 "error": f"Error: URL must start with http:// or https:// (got {url!r})",
             }
@@ -3568,12 +3730,12 @@ class ChatSession:
                 "call_id": call_id,
                 "func_name": "web_fetch",
                 "header": "\u2717 web_fetch: blocked (private network)",
-                "preview": f"    {RED}{url}{RESET}",
+                "preview": f"    {url}",
                 "needs_approval": False,
                 "error": f"Error: {ssrf_err}",
             }
         q_preview = question[:200] + ("..." if len(question) > 200 else "")
-        preview = f"    {DIM}{url}\n    Q: {q_preview}{RESET}"
+        preview = f"    {url}\n    Q: {q_preview}"
         return {
             "call_id": call_id,
             "func_name": "web_fetch",
@@ -3619,7 +3781,7 @@ class ChatSession:
         if topic not in ("general", "news", "finance"):
             topic = "general"
         q_preview = query[:200] + ("..." if len(query) > 200 else "")
-        preview = f"    {DIM}{q_preview}{RESET}"
+        preview = f"    {q_preview}"
         return {
             "call_id": call_id,
             "func_name": "web_search",
@@ -3658,7 +3820,7 @@ class ChatSession:
             "call_id": call_id,
             "func_name": "tool_search",
             "header": f"\u2699 tool_search: {query[:80]}",
-            "preview": f"    {DIM}{query}{RESET}",
+            "preview": f"    {query}",
             "needs_approval": False,
             "execute": self._exec_tool_search,
             "query": query,
@@ -3692,7 +3854,7 @@ class ChatSession:
             "call_id": call_id,
             "func_name": "task_agent",
             "header": "\u2699 task_agent (autonomous agent)",
-            "preview": f"    {DIM}{preview_text}{RESET}",
+            "preview": f"    {preview_text}",
             "needs_approval": True,
             "approval_label": "task_agent",
             "execute": self._exec_task,
@@ -3716,7 +3878,7 @@ class ChatSession:
             "call_id": call_id,
             "func_name": "plan_agent",
             "header": "\u2699 plan_agent (planning agent)",
-            "preview": f"    {DIM}{preview_text}{RESET}",
+            "preview": f"    {preview_text}",
             "needs_approval": True,
             "approval_label": "plan_agent",
             "execute": self._exec_plan,
@@ -4197,7 +4359,7 @@ class ChatSession:
                     if isinstance(parsed, list):
                         return " ".join(str(t) for t in parsed)
                 except (ValueError, TypeError):
-                    pass
+                    pass  # falls back to raw string
                 return raw
 
             # Build corpus from name + description + tags + category
@@ -4270,7 +4432,7 @@ class ChatSession:
             "call_id": call_id,
             "func_name": func_name,
             "header": f"\u2699 mcp:{display}",
-            "preview": f"{DIM}{preview}{RESET}",
+            "preview": preview,
             "needs_approval": True,
             "approval_label": func_name,
             "execute": self._exec_mcp_tool,
@@ -4348,7 +4510,7 @@ class ChatSession:
             "call_id": call_id,
             "func_name": "read_resource",
             "header": "\u2699 read_resource",
-            "preview": f"{DIM}    uri: {uri}{RESET}",
+            "preview": f"    uri: {uri}",
             "needs_approval": True,
             "approval_label": f"mcp_resource__{self._normalize_resource_uri(uri)}",
             "execute": self._exec_read_resource,
@@ -4825,6 +4987,12 @@ class ChatSession:
             label_b = "(provided content)"
             lines_b = (content_b or "").splitlines(keepends=True)
 
+        # When content_b is a baseline, swap so diff reads as "what changed"
+        # (--- old/baseline, +++ new/current file).
+        if content_b is not None:
+            lines_a, lines_b = lines_b, lines_a
+            path_a, label_b = label_b, path_a
+
         # Stream diff with early cutoff to avoid large allocations
         max_chars = self.tool_truncation or 262_144
         chunks: list[str] = []
@@ -4882,12 +5050,10 @@ class ChatSession:
             tools = _without_tool(tools, "web_search")
 
         # Build extra params for agent calls
-        agent_extra: dict[str, Any] | None = None
-        if agent_provider.provider_name == "openai":
-            agent_kwargs = dict(self._chat_template_kwargs_base)
-            if reasoning_effort:
-                agent_kwargs["reasoning_effort"] = reasoning_effort
-            agent_extra = {"chat_template_kwargs": agent_kwargs}
+        agent_extra = self._provider_extra_params(
+            reasoning_effort=reasoning_effort,
+            provider=agent_provider,
+        )
 
         def _api_call(
             messages: list[dict[str, Any]],
@@ -6167,26 +6333,30 @@ class ChatSession:
             return call_id, msg
 
         if not text.strip():
-            return call_id, "(empty response from URL)"
+            msg = "Error: fetch returned empty response"
+            self._report_tool_result(call_id, "web_fetch", msg, is_error=True)
+            return call_id, msg
 
         original_len = len(text)
         self.ui.on_info(f"fetched {original_len} chars, extracting...")
 
-        # Phase 2: truncate for summarization context
-        max_content = 50_000
+        # Phase 2: truncate for summarization context.
+        # Reserve ~25% of the context window for the extraction prompt
+        # overhead (system message, URL, question) and response tokens.
+        # Convert token budget to chars using the calibrated ratio.
+        max_content = int(self.context_window * self._chars_per_token * 0.75)
+        max_content = min(max(max_content, 50_000), 500_000)  # 50k–500k
         if len(text) > max_content:
-            text = (
-                text[: max_content // 2]
-                + f"\n\n... [{len(text) - max_content} chars omitted] ...\n\n"
-                + text[-(max_content // 2) :]
-            )
+            # Prefer the beginning — page content is usually top-heavy.
+            text = text[:max_content] + f"\n\n... [{len(text) - max_content} chars truncated] ...\n"
 
-        # Phase 3: summarization API call
+        # Phase 3: summarization API call.
+        # Use a generous max_tokens so thinking models don't starve the
+        # visible answer, and pass reasoning_effort="low" to avoid wasting
+        # budget on deep reasoning for a simple extraction task.
         try:
-            result = self._provider.create_completion(
-                client=self.client,
-                model=self.model,
-                messages=[
+            result = self._utility_completion(
+                [
                     {
                         "role": "system",
                         "content": (
@@ -6206,11 +6376,12 @@ class ChatSession:
                         ),
                     },
                 ],
-                max_tokens=2000,
+                max_tokens=8192,
                 temperature=0.2,
-                extra_params=self._provider_extra_params(),
             )
-            answer = result.content or "(no answer)"
+            answer = result.content or ""
+            if not answer:
+                answer = "Error: extraction returned no answer"
         except Exception as e:
             answer = f"Extraction failed (page was fetched but summarization errored): {e}"
 
@@ -6218,7 +6389,7 @@ class ChatSession:
             call_id,
             "web_fetch",
             answer,
-            is_error=answer.startswith("Extraction failed"),
+            is_error=answer.startswith(("Error:", "Extraction failed")),
         )
 
         return call_id, answer
@@ -6244,6 +6415,7 @@ class ChatSession:
             self._report_tool_result(call_id, "web_search", msg, is_error=True)
             return call_id, msg
 
+        output = self._truncate_output(output)
         self._report_tool_result(call_id, "web_search", output)
         return call_id, output
 

turnstone/core/settings_registry.py

@@ -43,6 +43,17 @@ def _build_registry() -> dict[str, SettingDef]:
             "model",
             help="Which AI model to use for conversations. Leave empty to use the provider's default.",
         ),
+        SettingDef(
+            "model.default_alias",
+            "str",
+            "",
+            "Default model alias for new sessions (empty = use config.toml [model].default)",
+            "model",
+            help="Which named model alias to use for new sessions. When empty, falls back to "
+            "the [model].default setting in config.toml (which defaults to 'default'). "
+            "Change this at runtime to switch all new sessions to a different model "
+            "without restarting.",
+        ),
         SettingDef(
             "model.temperature",
             "float",
@@ -335,43 +346,15 @@ def _build_registry() -> dict[str, SettingDef]:
         ),
         # -- health ---------------------------------------------------------
         SettingDef(
-            "health.backend_probe_interval",
-            "int",
-            30,
-            "Backend health probe interval in seconds",
-            "health",
-            min_value=5,
-            help="How often to check whether the AI model backend (e.g. OpenAI API) is reachable.",
-        ),
-        SettingDef(
-            "health.backend_probe_timeout",
+            "health.failure_threshold",
             "int",
             5,
-            "Backend health probe timeout in seconds",
+            "Consecutive failures before backend is marked degraded",
             "health",
             min_value=1,
-        ),
-        SettingDef(
-            "health.circuit_breaker_threshold",
-            "int",
-            5,
-            "Consecutive failures before circuit opens",
-            "health",
-            min_value=1,
-            help="If the AI backend fails this many times in a row, the circuit breaker trips "
-            "and stops sending requests for a cooldown period. This prevents cascading failures "
-            "and wasted API calls when the backend is down.",
-            reference_url="https://martinfowler.com/bliki/CircuitBreaker.html",
-        ),
-        SettingDef(
-            "health.circuit_breaker_cooldown",
-            "int",
-            60,
-            "Seconds before half-open retry",
-            "health",
-            min_value=5,
-            help="After the circuit breaker trips, wait this long before sending a single test "
-            "request to see if the backend has recovered.",
+            help="If the AI backend fails this many times in a row, it is marked as degraded. "
+            "Degraded backends are deprioritised in the fallback chain but requests are never "
+            "blocked. The backend recovers automatically when a request succeeds.",
         ),
         # -- judge ----------------------------------------------------------
         SettingDef(
@@ -394,16 +377,6 @@ def _build_registry() -> dict[str, SettingDef]:
             "to use the same model (self-consistency), or specify a different model for "
             "cross-model evaluation.",
         ),
-        SettingDef("judge.provider", "str", "", "Provider for judge model", "judge"),
-        SettingDef("judge.base_url", "str", "", "Base URL for judge model API", "judge"),
-        SettingDef(
-            "judge.api_key",
-            "str",
-            "",
-            "API key for judge model",
-            "judge",
-            is_secret=True,
-        ),
         SettingDef(
             "judge.confidence_threshold",
             "float",

turnstone/core/skill_sources.py

@@ -199,7 +199,7 @@ async def _fetch_resource_contents(
                 if resp.status_code == 200:
                     return rf["path"], resp.text
             except httpx.HTTPError:
-                pass
+                pass  # best-effort fetch, skip on failure
         return None
 
     results = await asyncio.gather(*[_fetch_one(rf) for rf in resource_files])
@@ -399,7 +399,7 @@ async def fetch_skills_from_github_repo(url: str) -> list[SkillPackage]:
                     if r.status_code == 200 and len(r.content) <= _MAX_SKILL_MD_SIZE:
                         return p, r.text
                 except httpx.HTTPError:
-                    pass
+                    pass  # best-effort fetch, skip on failure
             return None
 
         md_results = await asyncio.gather(*[_fetch_skill_md(p) for p in skill_md_paths])

turnstone/core/storage/__init__.py

@@ -4,10 +4,16 @@ Supports SQLite (default, zero-config) and PostgreSQL (multi-node, production).
 """
 
 from turnstone.core.storage._protocol import StorageBackend
-from turnstone.core.storage._registry import get_storage, init_storage, reset_storage
+from turnstone.core.storage._registry import (
+    StorageUnavailableError,
+    get_storage,
+    init_storage,
+    reset_storage,
+)
 
 __all__ = [
     "StorageBackend",
+    "StorageUnavailableError",
     "get_storage",
     "init_storage",
     "reset_storage",

turnstone/core/storage/_protocol.py

@@ -1066,6 +1066,90 @@ class StorageBackend(Protocol):
         """Delete a prompt policy. Returns True if existed."""
         ...
 
+    # -- Heuristic rules -------------------------------------------------------
+
+    def create_heuristic_rule(
+        self,
+        rule_id: str,
+        name: str,
+        risk_level: str,
+        confidence: float,
+        recommendation: str,
+        tool_pattern: str,
+        arg_patterns: str = "[]",
+        intent_template: str = "",
+        reasoning_template: str = "",
+        tier: str = "medium",
+        priority: int = 0,
+        builtin: bool = False,
+        enabled: bool = True,
+        created_by: str = "",
+    ) -> None:
+        """Create a heuristic rule. No-op if rule_id already exists."""
+        ...
+
+    def get_heuristic_rule(self, rule_id: str) -> dict[str, Any] | None:
+        """Return heuristic rule dict or None."""
+        ...
+
+    def get_heuristic_rule_by_name(self, name: str) -> dict[str, Any] | None:
+        """Return heuristic rule dict by name or None."""
+        ...
+
+    def list_heuristic_rules(self, enabled_only: bool = False) -> list[dict[str, Any]]:
+        """Return heuristic rules ordered by tier priority then rule priority."""
+        ...
+
+    def update_heuristic_rule(self, rule_id: str, **fields: Any) -> bool:
+        """Update specified fields on a heuristic rule. Returns True if found."""
+        ...
+
+    def delete_heuristic_rule(self, rule_id: str) -> bool:
+        """Delete a heuristic rule. Returns True if existed."""
+        ...
+
+    # -- Output guard patterns -------------------------------------------------
+
+    def create_output_guard_pattern(
+        self,
+        pattern_id: str,
+        name: str,
+        category: str,
+        risk_level: str,
+        pattern: str,
+        flag_name: str,
+        annotation: str,
+        pattern_flags: str = "",
+        is_credential: bool = False,
+        redact_label: str = "",
+        priority: int = 0,
+        builtin: bool = False,
+        enabled: bool = True,
+        created_by: str = "",
+    ) -> None:
+        """Create an output guard pattern. No-op if pattern_id already exists."""
+        ...
+
+    def get_output_guard_pattern(self, pattern_id: str) -> dict[str, Any] | None:
+        """Return output guard pattern dict or None."""
+        ...
+
+    def get_output_guard_pattern_by_name(self, name: str) -> dict[str, Any] | None:
+        """Return output guard pattern dict by name or None."""
+        ...
+
+    def list_output_guard_patterns(self, enabled_only: bool = False) -> list[dict[str, Any]]:
+        """Return output guard patterns ordered by category then priority."""
+        ...
+
+    def update_output_guard_pattern(self, pattern_id: str, **fields: Any) -> bool:
+        """Update specified fields on an output guard pattern. Returns True if found."""
+        ...
+
+    def delete_output_guard_pattern(self, pattern_id: str) -> bool:
+        """Delete an output guard pattern. Returns True if existed."""
+        ...
+
     # -- TLS / ACME (lacme Store) ----------------------------------------------
 
     def save_tls_account_key(self, key_id: str, key_pem: str) -> None:

turnstone/core/storage/_registry.py

@@ -15,6 +15,14 @@ log = get_logger(__name__)
 _storage: StorageBackend | None = None
 
 
+class StorageUnavailableError(Exception):
+    """Raised when the database is unreachable.
+
+    The storage layer has already logged a clean one-liner — callers
+    should catch this to avoid duplicate tracebacks.
+    """
+
+
 def init_storage(
     backend: str = "sqlite",
     *,

turnstone/core/storage/_schema.py

@@ -652,3 +652,59 @@ tls_certificates = sa.Table(
     sa.Column("expires_at", sa.Text, nullable=False),
     sa.Column("meta", sa.Text, nullable=True),
 )
+
+# ---------------------------------------------------------------------------
+# Heuristic rules — configurable intent validation patterns (admin-managed)
+# ---------------------------------------------------------------------------
+
+heuristic_rules = sa.Table(
+    "heuristic_rules",
+    metadata,
+    sa.Column("rule_id", sa.Text, primary_key=True),
+    sa.Column("name", sa.Text, nullable=False, unique=True),
+    sa.Column("risk_level", sa.Text, nullable=False),
+    sa.Column("confidence", sa.Float, nullable=False),
+    sa.Column("recommendation", sa.Text, nullable=False),
+    sa.Column("tool_pattern", sa.Text, nullable=False),
+    sa.Column("arg_patterns", sa.Text, nullable=False, server_default="[]"),
+    sa.Column("intent_template", sa.Text, nullable=False),
+    sa.Column("reasoning_template", sa.Text, nullable=False),
+    sa.Column("tier", sa.Text, nullable=False),
+    sa.Column("priority", sa.Integer, nullable=False, server_default="0"),
+    sa.Column("builtin", sa.Integer, nullable=False, server_default="0"),
+    sa.Column("enabled", sa.Integer, nullable=False, server_default="1"),
+    sa.Column("created_by", sa.Text, nullable=False, server_default=""),
+    sa.Column("created", sa.Text, nullable=False),
+    sa.Column("updated", sa.Text, nullable=False),
+)
+
+sa.Index("idx_heuristic_rules_enabled", heuristic_rules.c.enabled)
+sa.Index("idx_heuristic_rules_tier", heuristic_rules.c.tier)
+
+# ---------------------------------------------------------------------------
+# Output guard patterns — configurable output scanning patterns (admin-managed)
+# ---------------------------------------------------------------------------
+
+output_guard_patterns = sa.Table(
+    "output_guard_patterns",
+    metadata,
+    sa.Column("pattern_id", sa.Text, primary_key=True),
+    sa.Column("name", sa.Text, nullable=False, unique=True),
+    sa.Column("category", sa.Text, nullable=False),
+    sa.Column("risk_level", sa.Text, nullable=False),
+    sa.Column("pattern", sa.Text, nullable=False),
+    sa.Column("pattern_flags", sa.Text, nullable=False, server_default=""),
+    sa.Column("flag_name", sa.Text, nullable=False),
+    sa.Column("annotation", sa.Text, nullable=False),
+    sa.Column("is_credential", sa.Integer, nullable=False, server_default="0"),
+    sa.Column("redact_label", sa.Text, nullable=False, server_default=""),
+    sa.Column("priority", sa.Integer, nullable=False, server_default="0"),
+    sa.Column("builtin", sa.Integer, nullable=False, server_default="0"),
+    sa.Column("enabled", sa.Integer, nullable=False, server_default="1"),
+    sa.Column("created_by", sa.Text, nullable=False, server_default=""),
+    sa.Column("created", sa.Text, nullable=False),
+    sa.Column("updated", sa.Text, nullable=False),
+)
+
+sa.Index("idx_ogp_enabled", output_guard_patterns.c.enabled)
+sa.Index("idx_ogp_category", output_guard_patterns.c.category)

turnstone/core/storage/_utils.py

@@ -109,6 +109,38 @@ MODEL_DEFINITION_MUTABLE = frozenset(
     }
 )
 PROMPT_POLICY_MUTABLE = frozenset({"name", "content", "tool_gate", "priority", "enabled"})
+HEURISTIC_RULE_MUTABLE = frozenset(
+    {
+        "name",
+        "risk_level",
+        "confidence",
+        "recommendation",
+        "tool_pattern",
+        "arg_patterns",
+        "intent_template",
+        "reasoning_template",
+        "tier",
+        "priority",
+        "builtin",
+        "enabled",
+    }
+)
+OUTPUT_GUARD_PATTERN_MUTABLE = frozenset(
+    {
+        "name",
+        "category",
+        "risk_level",
+        "pattern",
+        "pattern_flags",
+        "flag_name",
+        "annotation",
+        "is_credential",
+        "redact_label",
+        "priority",
+        "builtin",
+        "enabled",
+    }
+)
 VERDICT_MUTABLE = frozenset(
     {
         "user_decision",
@@ -149,7 +181,7 @@ def scan_skill_content(content: str, allowed_tools: str) -> tuple[str, str, str]
                     if not tools:
                         tools = None
             except (json.JSONDecodeError, TypeError):
-                pass
+                pass  # falls back to None (no tool filter)
         result = scan_skill(content, tools)
         return result.tier, json.dumps(result.to_dict(), ensure_ascii=False), SCANNER_VERSION
     except Exception:

turnstone/core/storage/migrations/versions/032_prompt_policy_permission.py

@@ -0,0 +1,39 @@
+"""Grant admin.prompt_policies permission to builtin-admin role.
+
+Migration 031 created the prompt_policies table but did not add the
+corresponding permission to the builtin-admin role, causing 403 on
+/v1/api/admin/prompt-policies for all users.
+
+Revision ID: 032
+Revises: 031
+Create Date: 2026-04-05
+"""
+
+import sqlalchemy as sa
+from alembic import op
+
+revision = "032"
+down_revision = "031"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+    conn.execute(
+        sa.text(
+            "UPDATE roles SET permissions = permissions || ',admin.prompt_policies' "
+            "WHERE role_id = 'builtin-admin' "
+            "AND permissions NOT LIKE '%admin.prompt_policies%'"
+        )
+    )
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+    conn.execute(
+        sa.text(
+            "UPDATE roles SET permissions = REPLACE(permissions, ',admin.prompt_policies', '') "
+            "WHERE role_id = 'builtin-admin'"
+        )
+    )

turnstone/core/storage/migrations/versions/033_judge_rules.py

@@ -0,0 +1,82 @@
+"""Create heuristic_rules and output_guard_patterns tables for configurable judge.
+
+Revision ID: 033
+Revises: 032
+Create Date: 2026-04-04
+"""
+
+import sqlalchemy as sa
+from alembic import op
+
+revision = "033"
+down_revision = "032"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "heuristic_rules",
+        sa.Column("rule_id", sa.Text, primary_key=True),
+        sa.Column("name", sa.Text, nullable=False, unique=True),
+        sa.Column("risk_level", sa.Text, nullable=False),
+        sa.Column("confidence", sa.Float, nullable=False),
+        sa.Column("recommendation", sa.Text, nullable=False),
+        sa.Column("tool_pattern", sa.Text, nullable=False),
+        sa.Column("arg_patterns", sa.Text, nullable=False, server_default="[]"),
+        sa.Column("intent_template", sa.Text, nullable=False),
+        sa.Column("reasoning_template", sa.Text, nullable=False),
+        sa.Column("tier", sa.Text, nullable=False),
+        sa.Column("priority", sa.Integer, nullable=False, server_default="0"),
+        sa.Column("builtin", sa.Integer, nullable=False, server_default="0"),
+        sa.Column("enabled", sa.Integer, nullable=False, server_default="1"),
+        sa.Column("created_by", sa.Text, nullable=False, server_default=""),
+        sa.Column("created", sa.Text, nullable=False),
+        sa.Column("updated", sa.Text, nullable=False),
+    )
+    op.create_index("idx_heuristic_rules_enabled", "heuristic_rules", ["enabled"])
+    op.create_index("idx_heuristic_rules_tier", "heuristic_rules", ["tier"])
+
+    op.create_table(
+        "output_guard_patterns",
+        sa.Column("pattern_id", sa.Text, primary_key=True),
+        sa.Column("name", sa.Text, nullable=False, unique=True),
+        sa.Column("category", sa.Text, nullable=False),
+        sa.Column("risk_level", sa.Text, nullable=False),
+        sa.Column("pattern", sa.Text, nullable=False),
+        sa.Column("pattern_flags", sa.Text, nullable=False, server_default=""),
+        sa.Column("flag_name", sa.Text, nullable=False),
+        sa.Column("annotation", sa.Text, nullable=False),
+        sa.Column("is_credential", sa.Integer, nullable=False, server_default="0"),
+        sa.Column("redact_label", sa.Text, nullable=False, server_default=""),
+        sa.Column("priority", sa.Integer, nullable=False, server_default="0"),
+        sa.Column("builtin", sa.Integer, nullable=False, server_default="0"),
+        sa.Column("enabled", sa.Integer, nullable=False, server_default="1"),
+        sa.Column("created_by", sa.Text, nullable=False, server_default=""),
+        sa.Column("created", sa.Text, nullable=False),
+        sa.Column("updated", sa.Text, nullable=False),
+    )
+    op.create_index("idx_ogp_enabled", "output_guard_patterns", ["enabled"])
+    op.create_index("idx_ogp_category", "output_guard_patterns", ["category"])
+
+    # Grant admin.judge permission to builtin-admin role
+    conn = op.get_bind()
+    conn.execute(
+        sa.text(
+            "UPDATE roles SET permissions = permissions || ',admin.judge' "
+            "WHERE role_id = 'builtin-admin' "
+            "AND permissions NOT LIKE '%admin.judge%'"
+        )
+    )
+
+
+def downgrade() -> None:
+    op.drop_table("output_guard_patterns")
+    op.drop_table("heuristic_rules")
+    conn = op.get_bind()
+    conn.execute(
+        sa.text(
+            "UPDATE roles SET permissions = REPLACE(permissions, ',admin.judge', '') "
+            "WHERE role_id = 'builtin-admin'"
+        )
+    )

turnstone/core/watch.py

@@ -271,9 +271,13 @@ class WatchRunner:
     # -- Main loop -----------------------------------------------------------
 
     def _run(self) -> None:
+        from turnstone.core.storage._registry import StorageUnavailableError
+
         while not self._stop_event.is_set():
             try:
                 self._tick()
+            except StorageUnavailableError:
+                pass  # already logged by storage layer
             except Exception:
                 log.exception("watch_runner.tick_error")
             self._stop_event.wait(self._check_interval)
@@ -365,7 +369,7 @@ class WatchRunner:
                     created_dt = datetime.fromisoformat(created).replace(tzinfo=UTC)
                     elapsed_secs = (now - created_dt).total_seconds()
                 except (ValueError, TypeError):
-                    pass
+                    pass  # elapsed stays 0.0
 
             message = format_watch_message(
                 name=watch_row["name"],

turnstone/core/web.py

@@ -6,14 +6,20 @@ import socket
 from html import unescape as _html_unescape
 from urllib.parse import urlparse
 
+_RE_INVISIBLE = re.compile(
+    r"<(script|style|template|noscript)\b[^>]*>.*?</\1\s*>",
+    re.DOTALL | re.IGNORECASE,
+)
 _RE_TAGS = re.compile(r"<[^>]+>")
 _RE_WS = re.compile(r"[ \t]+")
 _RE_BLANKLINES = re.compile(r"\n{3,}")
 
 
 def strip_html(html: str) -> str:
-    """Convert HTML to plain text: strip tags, decode entities, collapse whitespace."""
-    text = _RE_TAGS.sub("", html)
+    """Convert HTML to plain text: strip invisible elements, tags, decode entities."""
+    # Remove elements whose content should never appear as text
+    text = _RE_INVISIBLE.sub("", html)
+    text = _RE_TAGS.sub("", text)
     text = _html_unescape(text)
     text = _RE_WS.sub(" ", text)
     text = _RE_BLANKLINES.sub("\n\n", text)

turnstone/deploy/__init__.py

@@ -0,0 +1,5 @@
+"""Bundled deployment templates (compose files, overlays).
+
+These files are included in the wheel so that ``turnstone-bootstrap`` can
+extract them for users who install via pip/pipx and don't have a git clone.
+"""

turnstone/deploy/compose.yaml

@@ -0,0 +1,173 @@
+# =============================================================================
+# Turnstone Docker Compose Stack — Production
+#
+# This file is bundled with the turnstone wheel and written by
+# turnstone-bootstrap for users who install via pip/pipx.
+# It pulls pre-built images from ghcr.io instead of building locally.
+#
+# Usage:
+#   Infra only:           docker compose up
+#   Single node:          docker compose --profile production up
+#   Production (PG):      docker compose --profile production up
+#                         (set DB_BACKEND, DATABASE_URL, POSTGRES_PASSWORD in .env)
+#
+# Set TURNSTONE_IMAGE_TAG in .env to pin the image version (default: latest).
+# =============================================================================
+
+name: turnstone
+
+networks:
+  turnstone-net:
+    driver: bridge
+
+volumes:
+  turnstone-data:
+  workspace:
+  postgres-data:
+
+services:
+  # -------------------------------------------------------------------
+  # PostgreSQL — production database (profile: production)
+  # -------------------------------------------------------------------
+  postgres:
+    image: pgautoupgrade/pgautoupgrade:18-alpine
+    profiles:
+      - production
+    command:
+      - postgres
+      - -c
+      - max_connections=${POSTGRES_MAX_CONNECTIONS:-300}
+      - -c
+      - shared_buffers=128MB
+    environment:
+      POSTGRES_DB: turnstone
+      POSTGRES_USER: ${POSTGRES_USER:-turnstone}
+      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?POSTGRES_PASSWORD is required for production profile}
+      PGDATA: /var/lib/postgresql/data
+    volumes:
+      - postgres-data:/var/lib/postgresql/data
+    networks:
+      - turnstone-net
+    healthcheck:
+      test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-turnstone}"]
+      interval: 5s
+      timeout: 3s
+      retries: 5
+      start_period: 30s
+    deploy:
+      resources:
+        limits:
+          memory: 1G
+          cpus: '1.0'
+    restart: unless-stopped
+
+  # -------------------------------------------------------------------
+  # turnstone-server — Web UI + chat workstreams + LLM interaction
+  # -------------------------------------------------------------------
+  server:
+    image: ghcr.io/turnstonelabs/turnstone:${TURNSTONE_IMAGE_TAG:-latest}
+    profiles:
+      - production
+    command:
+      - sh
+      - -c
+      - >-
+        turnstone-server
+        --host 0.0.0.0
+        --port 8080
+        --base-url "$${LLM_BASE_URL}"
+        --api-key "$${OPENAI_API_KEY}"
+        $${MODEL:+--model $$MODEL}
+        $${SKIP_PERMISSIONS:+--skip-permissions}
+        $${MCP_CONFIG:+--mcp-config $$MCP_CONFIG}
+    ports:
+      - "${SERVER_PORT:-8080}:8080"
+    volumes:
+      - turnstone-data:/data
+      - ${WORKSPACE_MOUNT:-workspace}:/workspace
+    environment:
+      - LLM_BASE_URL=${LLM_BASE_URL:-http://host.docker.internal:8000/v1}
+      - OPENAI_API_KEY=${OPENAI_API_KEY:-dummy}
+      - TAVILY_API_KEY=${TAVILY_API_KEY:-}
+      - SKIP_PERMISSIONS=${SKIP_PERMISSIONS:-}
+      # Generate with: python -c "import secrets; print(secrets.token_hex(32))"
+      - TURNSTONE_JWT_SECRET=${TURNSTONE_JWT_SECRET:?Set TURNSTONE_JWT_SECRET in .env}
+      - MODEL=${MODEL:-}
+      - MCP_CONFIG=${MCP_CONFIG:-}
+      - TURNSTONE_DB_BACKEND=${DB_BACKEND:-sqlite}
+      - TURNSTONE_DB_URL=${DATABASE_URL:-}
+      - TURNSTONE_NODE_ID=${TURNSTONE_NODE_ID:-}
+      - TURNSTONE_ADVERTISE_URL=${TURNSTONE_ADVERTISE_URL:-http://server:8080}
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    networks:
+      - turnstone-net
+    depends_on:
+      postgres:
+        condition: service_healthy
+        required: false
+    healthcheck:
+      test: ["CMD", "python", "/usr/local/bin/healthcheck.py", "http://127.0.0.1:8080/health"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+      start_period: 60s
+    restart: unless-stopped
+
+  # -------------------------------------------------------------------
+  # turnstone-console — Cluster dashboard
+  # -------------------------------------------------------------------
+  console:
+    image: ghcr.io/turnstonelabs/turnstone:${TURNSTONE_IMAGE_TAG:-latest}
+    command:
+      - turnstone-console
+      - --host=0.0.0.0
+      - --port=8090
+    ports:
+      - "${CONSOLE_PORT:-8090}:8090"
+    environment:
+      # Generate with: python -c "import secrets; print(secrets.token_hex(32))"
+      - TURNSTONE_JWT_SECRET=${TURNSTONE_JWT_SECRET:?Set TURNSTONE_JWT_SECRET in .env}
+      - TURNSTONE_DB_BACKEND=${DB_BACKEND:-sqlite}
+      - TURNSTONE_DB_URL=${DATABASE_URL:-}
+      - TURNSTONE_CONSOLE_URL=http://console:8090
+    networks:
+      - turnstone-net
+    healthcheck:
+      test: ["CMD", "python", "/usr/local/bin/healthcheck.py", "http://127.0.0.1:8090/health"]
+      interval: 10s
+      timeout: 5s
+      retries: 3
+      start_period: 10s
+    restart: unless-stopped
+
+  # -------------------------------------------------------------------
+  # turnstone-channel — Channel gateway (Discord, Slack, etc.)
+  # Requires TURNSTONE_DISCORD_TOKEN to enable Discord adapter
+  # -------------------------------------------------------------------
+  channel:
+    image: ghcr.io/turnstonelabs/turnstone:${TURNSTONE_IMAGE_TAG:-latest}
+    profiles:
+      - production
+    command:
+      - sh
+      - -c
+      - >-
+        turnstone-channel
+        --http-host=0.0.0.0
+        $${TURNSTONE_DISCORD_GUILD:+--discord-guild $$TURNSTONE_DISCORD_GUILD}
+    environment:
+      - TURNSTONE_DISCORD_TOKEN=${TURNSTONE_DISCORD_TOKEN:-}
+      - TURNSTONE_DISCORD_GUILD=${TURNSTONE_DISCORD_GUILD:-0}
+      # Generate with: python -c "import secrets; print(secrets.token_hex(32))"
+      - TURNSTONE_JWT_SECRET=${TURNSTONE_JWT_SECRET:?Set TURNSTONE_JWT_SECRET in .env}
+      - TURNSTONE_DB_BACKEND=${DB_BACKEND:-postgresql}
+      - TURNSTONE_DB_URL=${DATABASE_URL:-postgresql+psycopg://${POSTGRES_USER:-turnstone}:${POSTGRES_PASSWORD:-turnstone}@postgres:5432/turnstone}
+      - TURNSTONE_CHANNEL_ADVERTISE_URL=http://channel:8091
+    networks:
+      - turnstone-net
+    depends_on:
+      postgres:
+        condition: service_healthy
+        required: false
+    restart: unless-stopped

turnstone/eval.py

@@ -45,7 +45,11 @@ _MCP_ONLY_TOOLS = frozenset({"read_resource", "use_prompt"})
 
 def _detect_provider(base_url: str) -> str:
     """Infer provider name from a base URL."""
-    if "anthropic.com" in base_url:
+    from urllib.parse import urlparse
+
+    normalized = base_url if "://" in base_url else f"https://{base_url}"
+    hostname = urlparse(normalized).hostname or ""
+    if hostname == "anthropic.com" or hostname.endswith(".anthropic.com"):
         return "anthropic"
     return "openai"
 

turnstone/sdk/events.py

@@ -313,10 +313,10 @@ class NodeSnapshotEvent(ClusterEvent):
 
 @dataclass
 class HealthChangedEvent(ClusterEvent):
-    """Circuit breaker state transition on a server node."""
+    """Backend health state transition on a server node."""
 
     type: str = "health_changed"
-    circuit_state: str = ""
+    backend_status: str = ""  # "healthy" or "degraded"
 
 
 @dataclass

turnstone/server.py

@@ -923,7 +923,7 @@ async def events_sse(request: Request) -> Response:
                         return
                     yield {"data": json.dumps(event)}
                 except queue.Empty:
-                    pass
+                    pass  # poll timeout, retry
         finally:
             _metrics.record_sse_disconnect()
             ui._unregister_listener(client_queue)
@@ -1045,7 +1045,7 @@ async def global_events_sse(request: Request) -> Response:
                     )
                     yield {"data": json.dumps(event)}
                 except queue.Empty:
-                    pass
+                    pass  # poll timeout, retry
         finally:
             _metrics.record_sse_disconnect()
             with listeners_lock:
@@ -1214,8 +1214,20 @@ def _build_health_dict(app_state: Any) -> dict[str, Any]:
     mgr: WorkstreamManager = app_state.workstreams
     wss = mgr.list_all()
     states = _count_ws_states(wss)
-    monitor = getattr(app_state, "health_monitor", None)
-    backend_ok = monitor.is_healthy if monitor else True
+    health_reg = getattr(app_state, "health_registry", None)
+    registry = getattr(app_state, "registry", None)
+    tracker = None
+    if health_reg and registry:
+        # Prefer ConfigStore runtime override, fall back to registry default
+        config_store = getattr(app_state, "config_store", None)
+        effective_alias = None
+        if config_store:
+            effective_alias = config_store.get("model.default_alias") or None
+        if effective_alias:
+            tracker = health_reg.get_tracker_for_alias(registry, effective_alias)
+        if tracker is None:
+            tracker = health_reg.get_tracker_for_alias(registry, registry.default)
+    backend_ok = tracker.is_healthy if tracker else True
     data: dict[str, Any] = {
         "status": "ok" if backend_ok else "degraded",
         "version": __version__,
@@ -1226,7 +1238,6 @@ def _build_health_dict(app_state: Any) -> dict[str, Any]:
         "workstreams": {"total": len(wss), **states},
         "backend": {
             "status": "up" if backend_ok else "down",
-            "circuit_state": monitor.circuit_state.value if monitor else "closed",
         },
     }
     mc = getattr(app_state, "mcp_client", None)
@@ -1652,7 +1663,8 @@ async def create_workstream(request: Request) -> JSONResponse:
             ws_id=requested_ws_id,
             client_type=body.get("client_type", "") or "",
         )
-        assert isinstance(ws.ui, WebUI)
+        if not isinstance(ws.ui, WebUI):
+            raise TypeError(f"Expected WebUI, got {type(ws.ui).__name__}")
         if skip or body.get("auto_approve", False):
             ws.ui.auto_approve = True
         # Register watch runner for this workstream
@@ -1752,7 +1764,7 @@ async def create_workstream(request: Request) -> JSONResponse:
 
                     _gs().set_workstream_override(ws.id, node_id, reason="local")
                 except Exception:
-                    pass  # best-effort; routing will still work via resume
+                    log.debug("Failed to set routing override for %s", ws.id, exc_info=True)
 
         # If an initial_message was provided, send it as the first user message.
         # This replaces the old bridge behavior where CreateWorkstreamMessage
@@ -2148,10 +2160,18 @@ def internal_model_reload(request: Request) -> JSONResponse:
         provider=cli_args["provider"],
         storage=get_storage(),
     )
+    # Allow runtime override of the default alias via ConfigStore
+    effective_default = new_registry.default
+    cs = getattr(request.app.state, "config_store", None)
+    if cs:
+        cs_alias = cs.get("model.default_alias")
+        if cs_alias and cs_alias in new_registry.models:
+            effective_default = cs_alias
+
     try:
         registry.reload(
             new_registry.models,
-            new_registry.default,
+            effective_default,
             new_registry.fallback,
             new_registry.agent_model,
         )
@@ -2159,6 +2179,14 @@ def internal_model_reload(request: Request) -> JSONResponse:
         return JSONResponse({"status": "error", "reason": str(exc)}, status_code=422)
     finally:
         new_registry.shutdown()
+
+    # Ensure health trackers exist for any newly-added backends
+    health_reg = getattr(request.app.state, "health_registry", None)
+    if health_reg:
+        for alias in registry.list_aliases():
+            cfg = registry.get_config(alias)
+            health_reg.get_tracker(provider=cfg.provider, base_url=cfg.base_url)
+
     return JSONResponse({"status": "ok", "aliases": registry.list_aliases()})
 
 
@@ -2210,13 +2238,51 @@ async def internal_migrate(request: Request) -> JSONResponse:
 # ---------------------------------------------------------------------------
 
 
-def _emit_health_changed(circuit_state: str, gq: queue.Queue[dict[str, Any]]) -> None:
+def _emit_health_changed(
+    status: str, gq: queue.Queue[dict[str, Any]], app_state: Any = None
+) -> None:
     """Push a health_changed event onto the global SSE queue.
 
-    Called from the BackendHealthMonitor callback on circuit breaker transitions.
+    Called from the BackendHealthTracker callback on state transitions.
+    *status* is ``"healthy"`` or ``"degraded"``.
+
+    Also updates the global ``turnstone_backend_up`` metric using the
+    effective default backend's health (not the backend that triggered
+    this callback, which may be a non-default fallback).
     """
+    if app_state is not None:
+        _update_backend_metric(app_state)
     with contextlib.suppress(queue.Full):
-        gq.put_nowait({"type": "health_changed", "circuit_state": circuit_state})
+        gq.put_nowait(
+            {
+                "type": "health_changed",
+                "backend_status": status,
+            }
+        )
+
+
+def _update_backend_metric(app_state: Any) -> None:
+    """Update ``turnstone_backend_up`` from the effective default's tracker.
+
+    Called on any backend state change.  Only the effective default
+    backend drives this global metric — fallback backend transitions
+    do not affect it.
+    """
+    health_reg = getattr(app_state, "health_registry", None)
+    registry = getattr(app_state, "registry", None)
+    if not health_reg or not registry:
+        return
+    config_store = getattr(app_state, "config_store", None)
+    effective = None
+    if config_store:
+        effective = config_store.get("model.default_alias") or None
+    tracker = None
+    if effective:
+        tracker = health_reg.get_tracker_for_alias(registry, effective)
+    if tracker is None:
+        tracker = health_reg.get_tracker_for_alias(registry, registry.default)
+    if tracker is not None:
+        _metrics.set_backend_status(tracker.is_healthy)
 
 
 def _aggregate_emitter_thread(
@@ -2389,10 +2455,14 @@ async def _lifespan(app: Starlette) -> AsyncGenerator[None, None]:
 
         async def _heartbeat_loop() -> None:
             """Periodically update service heartbeat."""
+            from turnstone.core.storage._registry import StorageUnavailableError
+
             while True:
                 await asyncio.sleep(30)
                 try:
                     await asyncio.to_thread(_svc_storage.heartbeat_service, "server", _svc_node_id)
+                except StorageUnavailableError:
+                    pass  # already logged by storage layer
                 except Exception:
                     log.exception("server.heartbeat_failed")
 
@@ -2415,8 +2485,7 @@ async def _lifespan(app: Starlette) -> AsyncGenerator[None, None]:
         await tls_client.stop_renewal()
     if app.state.watch_runner:
         app.state.watch_runner.stop()
-    if app.state.health_monitor:
-        app.state.health_monitor.stop()
+    # health_registry is stateless (no background threads) — nothing to stop
     if app.state.mcp_client:
         app.state.mcp_client.shutdown()
     if app.state.registry:
@@ -2457,7 +2526,7 @@ def create_app(
     skip_permissions: bool,
     jwt_secret: str = "",
     auth_storage: Any = None,
-    health_monitor: Any = None,
+    health_registry: Any = None,
     rate_limiter: Any = None,
     mcp_client: Any = None,
     mcp_ref: list[Any] | None = None,
@@ -2537,7 +2606,7 @@ def create_app(
     app.state.skip_permissions = skip_permissions
     app.state.jwt_secret = jwt_secret
     app.state.auth_storage = auth_storage
-    app.state.health_monitor = health_monitor
+    app.state.health_registry = health_registry
     app.state.rate_limiter = rate_limiter
     app.state.mcp_client = mcp_client
     app.state.mcp_ref = mcp_ref
@@ -2679,7 +2748,7 @@ def main() -> None:
             if host and host != "localhost":
                 return f"{host}_{suffix}"
         except OSError:
-            pass
+            pass  # hostname unavailable, fall back to UUID
         return uuid.uuid4().hex[:12]
 
     _node_id = os.environ.get("TURNSTONE_NODE_ID") or _default_node_id()
@@ -2730,10 +2799,10 @@ def main() -> None:
 
         model, detected_ctx = detect_model(client, provider=provider_name, fatal=False)
         if model is None:
-            # LLM backend unreachable — start with a placeholder model name.
-            # The health monitor will report degraded and the circuit breaker
-            # will prevent requests until the backend comes up.
-            model = "unavailable"
+            # LLM backend unreachable — no CLI model specified.
+            # Set empty so load_model_registry skips the CLI "default"
+            # entry and relies on DB / config.toml models instead.
+            model = ""
 
     # Use detected context window, fall back to ConfigStore override or 32768
     cfg_ctx = config_store.get("model.context_window")
@@ -2758,6 +2827,11 @@ def main() -> None:
         storage=_get_storage(),
     )
 
+    # Apply runtime default alias override from ConfigStore (if set)
+    cs_default_alias = config_store.get("model.default_alias")
+    if cs_default_alias and registry.has_alias(cs_default_alias):
+        registry.reload(registry.models, cs_default_alias, registry.fallback, registry.agent_model)
+
     # Initialize MCP client (connects to configured MCP servers, if any)
     from turnstone.core.mcp_client import create_mcp_client
 
@@ -2771,56 +2845,33 @@ def main() -> None:
     # including ones created by internal_mcp_reload after startup.
     _mcp_ref: list[Any] = [mcp_client]
 
-    # Backend health monitor with circuit breaker
-    from turnstone.core.healthcheck import BackendHealthMonitor
-
-    def _handle_model_change(new_model_id: str, new_ctx: int | None) -> None:
-        """Called from health probe thread when backend model changes."""
-        cli_args = getattr(getattr(app, "state", None), "cli_model_args", None)
-        if not cli_args or cli_args.get("_user_specified_model"):
-            return
-        old_model = cli_args["model"]
-        ctx = new_ctx or cli_args["context_window"]
-        log.info("Backend model changed: %s -> %s (ctx=%s)", old_model, new_model_id, ctx)
-        new_reg = None
-        try:
-            new_reg = load_model_registry(
-                base_url=cli_args["base_url"],
-                api_key=cli_args["api_key"],
-                model=new_model_id,
-                context_window=ctx,
-                provider=cli_args["provider"],
-                storage=get_storage(),
-            )
-            registry.reload(new_reg.models, new_reg.default, new_reg.fallback, new_reg.agent_model)
-            # Update cli_model_args only after successful reload
-            cli_args["model"] = new_model_id
-            cli_args["context_window"] = ctx
-        except Exception:
-            log.warning("Model change reload failed", exc_info=True)
-        finally:
-            if new_reg is not None:
-                new_reg.shutdown()
+    # Per-backend passive health tracking (no active probes / circuit breakers)
+    from turnstone.core.healthcheck import HealthTrackerRegistry
 
     # Set up global event queue for state-change broadcasts (created early so
-    # the health monitor callback can reference it).
+    # the health tracker callback can reference it).
     global_queue: queue.Queue[dict[str, Any]] = queue.Queue(maxsize=10000)
     global_listeners: list[queue.Queue[dict[str, Any]]] = []
     global_listeners_lock = threading.Lock()
     WebUI._global_queue = global_queue
 
-    health_monitor = BackendHealthMonitor(
-        client=client,
-        probe_interval=config_store.get("health.backend_probe_interval"),
-        probe_timeout=config_store.get("health.backend_probe_timeout"),
-        failure_threshold=config_store.get("health.circuit_breaker_threshold"),
-        cooldown=config_store.get("health.circuit_breaker_cooldown"),
-        provider=provider_name,
-        initial_model=model,
-        on_model_changed=_handle_model_change,
-        on_state_changed=lambda state: _emit_health_changed(state, global_queue),
+    # Mutable ref so the health callback can access app.state after app
+    # creation (same pattern as _mcp_ref).
+    _app_ref: list[Any] = [None]
+
+    health_registry = HealthTrackerRegistry(
+        failure_threshold=config_store.get("health.failure_threshold"),
+        on_state_changed=lambda _backend, state: _emit_health_changed(
+            state, global_queue, _app_ref[0].state if _app_ref[0] else None
+        ),
     )
-    health_monitor.start()
+
+    # Eagerly create trackers for all registered backends.  Sessions use
+    # read-only lookups (get_tracker_for_alias) and never create trackers
+    # on the hot path, so every backend must be registered here.
+    for _alias in registry.list_aliases():
+        _cfg = registry.get_config(_alias)
+        health_registry.get_tracker(provider=_cfg.provider, base_url=_cfg.base_url)
 
     # Per-IP rate limiter
     from turnstone.core.ratelimit import RateLimiter
@@ -2841,9 +2892,6 @@ def main() -> None:
         return JudgeConfig(
             enabled=config_store.get("judge.enabled"),
             model=config_store.get("judge.model"),
-            provider=config_store.get("judge.provider"),
-            base_url=config_store.get("judge.base_url"),
-            api_key=config_store.get("judge.api_key"),
             confidence_threshold=config_store.get("judge.confidence_threshold"),
             max_context_ratio=config_store.get("judge.max_context_ratio"),
             timeout=config_store.get("judge.timeout"),
@@ -2870,6 +2918,17 @@ def main() -> None:
         )
 
     # Session factory — captures shared config (including config_store for hot-reload)
+    def _effective_default_alias() -> str:
+        """Return the runtime-effective default model alias.
+
+        Checks ConfigStore for a ``model.default_alias`` override first,
+        then falls back to the registry's static default.
+        """
+        cs_alias: str = config_store.get("model.default_alias")
+        if cs_alias and registry.has_alias(cs_alias):
+            return cs_alias
+        return registry.default
+
     def session_factory(
         ui: SessionUI | None,
         model_alias: str | None = None,
@@ -2879,6 +2938,9 @@ def main() -> None:
         client_type: str = "",
     ) -> ChatSession:
         assert ui is not None
+        # Resolve the effective alias once and use it consistently
+        # for both client resolution and ChatSession.model_alias.
+        model_alias = model_alias or _effective_default_alias()
         r_client, r_model, r_cfg = registry.resolve(model_alias)
         # Read MCP client from shared ref — may have been replaced after startup
         # by internal_mcp_reload (Sync to Nodes) when no --mcp-config was passed.
@@ -2897,7 +2959,7 @@ def main() -> None:
                     if _u:
                         _username = _u.get("username", "")
             except Exception:
-                pass
+                log.debug("Failed to resolve username for uid %s", uid, exc_info=True)
 
         # Re-resolve from ConfigStore so new workstreams pick up hot-reloaded settings.
         live_memory_config = _build_memory_config()
@@ -2919,8 +2981,8 @@ def main() -> None:
             tool_truncation=config_store.get("tools.truncation"),
             mcp_client=live_mcp_client,
             registry=registry,
-            model_alias=model_alias or registry.default,
-            health_monitor=health_monitor,
+            model_alias=model_alias,
+            health_registry=health_registry,
             node_id=_node_id,
             ws_id=ws_id,
             tool_search=config_store.get("tools.search"),
@@ -2985,7 +3047,8 @@ def main() -> None:
         name="default",
         ui_factory=lambda wid: WebUI(ws_id=wid),
     )
-    assert isinstance(ws.ui, WebUI)
+    if not isinstance(ws.ui, WebUI):
+        raise TypeError(f"Expected WebUI, got {type(ws.ui).__name__}")
     if config_store.get("tools.skip_permissions"):
         ws.ui.auto_approve = True
 
@@ -3042,7 +3105,7 @@ def main() -> None:
         skip_permissions=_skip_perms,
         jwt_secret=jwt_secret,
         auth_storage=get_storage(),
-        health_monitor=health_monitor,
+        health_registry=health_registry,
         rate_limiter=rate_limiter,
         mcp_client=mcp_client,
         mcp_ref=_mcp_ref,
@@ -3056,6 +3119,9 @@ def main() -> None:
         advertise_url=_advertise_url,
     )
 
+    # Wire app ref so health callbacks can access app.state for metrics
+    _app_ref[0] = app
+
     # Store CLI model args for hot-reload (internal_model_reload reads these)
     app.state.cli_model_args = {
         "base_url": base_url,
@@ -3077,9 +3143,8 @@ def main() -> None:
             log.info("MCP tools: %d from %d server(s)", len(mcp_tools), mcp_client.server_count)
         mcp_client.set_storage(get_storage())
     log.info(
-        "Health monitor: probe every %ss, circuit breaker threshold=%s",
-        config_store.get("health.backend_probe_interval"),
-        config_store.get("health.circuit_breaker_threshold"),
+        "Health tracking: failure_threshold=%s",
+        config_store.get("health.failure_threshold"),
     )
     if rate_limiter.enabled:
         log.info(

turnstone/shared_static/base.css

@@ -66,7 +66,7 @@
   --accent-dim: rgba(140, 94, 27, 0.1);
   --accent-glow: rgba(140, 94, 27, 0.05);
   --green: #047857;
-  --red: #dc2626;
+  --red: #b91c1c;
   --yellow: #b45309;
   --cyan: #0e7490;
   --magenta: #7c3aed;
@@ -512,6 +512,10 @@ body {
   overflow: hidden;
   text-overflow: ellipsis;
 }
+#toast.toast-error {
+  border-color: var(--red, #c44);
+  color: var(--red, #c44);
+}
 #toast.show {
   opacity: 1;
   transform: translateX(-50%) translateY(0);

turnstone/shared_static/hls-1.6.15/LICENSE

@@ -0,0 +1,28 @@
+Copyright (c) 2017 Dailymotion (http://www.dailymotion.com)
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+src/remux/mp4-generator.js and src/demux/exp-golomb.ts implementation in this project
+are derived from the HLS library for video.js (https://github.com/videojs/videojs-contrib-hls)
+
+That work is also covered by the Apache 2 License, following copyright:
+Copyright (c) 2013-2015 Brightcove
+
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

turnstone/shared_static/toast.js

@@ -6,18 +6,20 @@ var _toastTimer = null;
 var _toastShowing = false;
 var _TOAST_TIMEOUT = window.TURNSTONE_TOAST_TIMEOUT || 3000;
 
-function showToast(message) {
+function showToast(message, type) {
   var el = document.getElementById("toast");
   if (!el) return;
   if (_toastShowing) {
-    _toastQueue.push(message);
+    _toastQueue.push({ message: message, type: type });
     return;
   }
-  _displayToast(el, message);
+  _displayToast(el, message, type);
 }
 
-function _displayToast(el, message) {
+function _displayToast(el, message, type) {
   el.textContent = message;
+  el.classList.remove("toast-error");
+  if (type === "error") el.classList.add("toast-error");
   el.classList.add("show");
   _toastShowing = true;
   if (_toastTimer) clearTimeout(_toastTimer);
@@ -27,7 +29,8 @@ function _displayToast(el, message) {
     _toastTimer = null;
     if (_toastQueue.length) {
       setTimeout(function () {
-        _displayToast(el, _toastQueue.shift());
+        var item = _toastQueue.shift();
+        _displayToast(el, item.message, item.type);
       }, 300);
     }
   }, _TOAST_TIMEOUT);

turnstone/ui/static/app.js

@@ -172,13 +172,20 @@ Pane.prototype._createDOM = function () {
   this.inputEl = document.createElement("textarea");
   this.inputEl.className = "pane-input";
   this.inputEl.rows = 1;
-  this.inputEl.placeholder = "Type a message\u2026 (Shift+Enter for newline)";
+  this._isTouch = window.matchMedia(
+    "(hover: none) and (pointer: coarse)",
+  ).matches;
+  this.inputEl.placeholder = this._isTouch
+    ? "Type a message\u2026"
+    : "Type a message\u2026 (Shift+Enter for newline)";
   this.inputEl.setAttribute("aria-label", "Message input");
   this.inputEl.addEventListener("input", function () {
     self._autoResize();
   });
   this.inputEl.addEventListener("keydown", function (e) {
-    if (e.key === "Enter" && !e.shiftKey) {
+    // On touch devices, let Enter insert newlines — users tap Send button.
+    // On desktop, Enter sends and Shift+Enter inserts a newline.
+    if (e.key === "Enter" && !e.shiftKey && !self._isTouch) {
       e.preventDefault();
       self.sendMessage();
     }
@@ -861,13 +868,23 @@ Pane.prototype.replayHistory = function (messages) {
             cmd.className = "tool-cmd";
             try {
               var args = JSON.parse(tc.arguments);
-              var preview = Object.values(args)[0] || "";
               if (tc.name === "bash") {
+                var preview = Object.values(args)[0] || "";
                 cmd.innerHTML =
                   '<span class="dollar">$ </span>' +
                   escapeHtml(String(preview));
               } else {
-                cmd.textContent = String(preview).substring(0, 200);
+                var parts = [];
+                var keys = Object.keys(args);
+                for (var k = 0; k < keys.length; k++) {
+                  var val = args[keys[k]];
+                  var valStr =
+                    val === null || val === undefined ? "null" : String(val);
+                  if (valStr.length > 80)
+                    valStr = valStr.substring(0, 77) + "...";
+                  parts.push(keys[k] + ": " + valStr);
+                }
+                cmd.textContent = parts.join("\n");
               }
             } catch (e) {
               cmd.textContent = tc.arguments.substring(0, 100);
@@ -906,16 +923,21 @@ Pane.prototype.replayHistory = function (messages) {
           /^Blocked/.test(stripped);
         var isToolError = !!msg.is_error;
         if (stripped && !isDenied) {
-          var out = document.createElement("div");
-          out.className =
-            "tool-output" + (isToolError ? " tool-output-error" : "");
-          out.textContent = stripped;
-          if (stripped.split("\n").length > 10) {
-            makeCollapsible(out);
+          var media = !isToolError ? tryParseMedia(stripped) : null;
+          if (media) {
+            var embed = buildMediaEmbed(media, stripped);
+            var bdg = lastToolBlock.querySelector(".approval-badge");
+            if (bdg) lastToolBlock.insertBefore(embed, bdg);
+            else lastToolBlock.appendChild(embed);
+          } else {
+            var out = renderToolOutput(stripped, isToolError);
+            if (out.textContent.split("\n").length > 10) {
+              makeCollapsible(out);
+            }
+            var bdg = lastToolBlock.querySelector(".approval-badge");
+            if (bdg) lastToolBlock.insertBefore(out, bdg);
+            else lastToolBlock.appendChild(out);
           }
-          var bdg = lastToolBlock.querySelector(".approval-badge");
-          if (bdg) lastToolBlock.insertBefore(out, bdg);
-          else lastToolBlock.appendChild(out);
         }
         if (isToolError && !lastToolBlock.classList.contains("denied")) {
           lastToolBlock.classList.add("error");
@@ -1221,10 +1243,18 @@ Pane.prototype.appendToolOutput = function (callId, name, output, isError) {
   var stripped = stripAnsi(output || "").trim();
   if (!stripped) return;
 
-  // Style tool output as error when indicated by isError flag
-  var out = document.createElement("div");
-  out.className = "tool-output" + (isError ? " tool-output-error" : "");
-  out.textContent = stripped;
+  // Detect structured media output and render interactive embed
+  if (!isError) {
+    var media = tryParseMedia(stripped);
+    if (media) {
+      var embed = buildMediaEmbed(media, stripped);
+      target.after(embed);
+      this.scrollToBottom();
+      return;
+    }
+  }
+
+  var out = renderToolOutput(stripped, isError);
 
   // Mark the parent approval block as errored
   if (isError) {
@@ -1239,7 +1269,7 @@ Pane.prototype.appendToolOutput = function (callId, name, output, isError) {
     }
   }
 
-  if (stripped.split("\n").length > 10) {
+  if (out.textContent.split("\n").length > 10) {
     makeCollapsible(out);
   }
 
@@ -2122,15 +2152,14 @@ function pollHealth() {
       var el = document.getElementById("health-indicator");
       if (!el) return;
       if (data.status === "degraded") {
-        el.textContent = "backend down";
+        el.textContent = "backend degraded";
         el.className = "health-degraded";
         el.title =
-          "Circuit: " +
-          ((data.backend && data.backend.circuit_state) || "unknown");
+          "Backend: " + ((data.backend && data.backend.status) || "unknown");
         el.setAttribute(
           "aria-label",
-          "Backend degraded. Circuit: " +
-            ((data.backend && data.backend.circuit_state) || "unknown"),
+          "Backend degraded: " +
+            ((data.backend && data.backend.status) || "unknown"),
         );
       } else {
         el.textContent = "";
@@ -2795,12 +2824,7 @@ function updateDashFooter(agg) {
     parts.push(formatUptime(agg.uptime_seconds) + " uptime");
   statsEl.textContent = parts.join(" \u00b7 ");
   if (_lastHealth && _lastHealth.status === "degraded") {
-    statsEl.textContent +=
-      " \u00b7 backend down (circuit " +
-      (_lastHealth.backend && _lastHealth.backend.circuit_state
-        ? _lastHealth.backend.circuit_state
-        : "unknown") +
-      ")";
+    statsEl.textContent += " \u00b7 backend degraded";
   }
 }
 
@@ -3170,6 +3194,404 @@ function makeCollapsible(el) {
   });
 }
 
+// ===========================================================================
+//  12a. Media embed renderer (MCP tool output with stream_url / results)
+// ===========================================================================
+
+function tryParseMedia(text) {
+  try {
+    var obj = JSON.parse(text);
+  } catch (e) {
+    return null;
+  }
+  if (obj && typeof obj.stream_url === "string") return obj;
+  if (obj && obj.name && obj.type && obj.id) return obj;
+  if (obj && Array.isArray(obj.results) && obj.results.length > 0) return obj;
+  if (obj && Array.isArray(obj.sessions)) return obj;
+  return null;
+}
+
+function _formatRuntime(item) {
+  var mins = 0;
+  if (typeof item.runtime_minutes === "number") {
+    mins = Math.round(item.runtime_minutes);
+  } else if (typeof item.runtime_ticks === "number") {
+    mins = Math.round(item.runtime_ticks / 600000000);
+  }
+  if (!mins) return "";
+  var h = Math.floor(mins / 60);
+  var m = mins % 60;
+  return h > 0 ? h + "h " + m + "m" : m + "m";
+}
+
+function _redactApiKeys(text) {
+  // Query-string style: api_key=VALUE
+  var redacted = text.replace(
+    /(?:api_key|apiKey|api-key|token)=[^&\s"]+/g,
+    function (m) {
+      return m.split("=")[0] + "=***";
+    },
+  );
+  // JSON style: "api_key": "VALUE"
+  redacted = redacted.replace(
+    /(["'](?:api_key|apiKey|api-key|token)["']\s*:\s*["'])([^"']*)(['"])/gi,
+    "$1***$3",
+  );
+  return redacted;
+}
+
+/**
+ * Try to pretty-print JSON text with indentation and API key redaction.
+ * Returns a formatted string if valid JSON, otherwise null.
+ */
+function _tryPrettyJson(text) {
+  try {
+    var obj = JSON.parse(text);
+  } catch (e) {
+    return null;
+  }
+  return _redactApiKeys(JSON.stringify(obj, null, 2));
+}
+
+/**
+ * Render tool output text into a DOM element.
+ * If the text is valid JSON, pretty-prints it with indentation.
+ * Otherwise renders as plain text. Always redacts API keys.
+ */
+function renderToolOutput(stripped, isError) {
+  var out = document.createElement("div");
+  out.className = "tool-output" + (isError ? " tool-output-error" : "");
+  if (!isError) {
+    var pretty = _tryPrettyJson(stripped);
+    if (pretty) {
+      out.textContent = pretty;
+      return out;
+    }
+  }
+  out.textContent = _redactApiKeys(stripped);
+  return out;
+}
+
+function buildMediaEmbed(media, rawJson) {
+  var wrapper = document.createElement("div");
+  wrapper.className = "media-embed";
+
+  if (media.stream_url) {
+    var card = buildMediaCard(media);
+    card.querySelector(".media-card-info").appendChild(buildPlayButton(media));
+    wrapper.appendChild(card);
+  } else if (media.results) {
+    wrapper.appendChild(
+      buildMediaResultsList(media.results, media.total_count),
+    );
+  } else if (media.sessions) {
+    wrapper.appendChild(buildMediaResultsList(media.sessions, null));
+  } else if (media.name && media.type && media.id) {
+    wrapper.appendChild(buildMediaCard(media));
+  }
+
+  // Collapsed raw JSON for inspection (with redacted API keys)
+  var raw = document.createElement("div");
+  raw.className = "tool-output";
+  raw.textContent = _tryPrettyJson(rawJson) || _redactApiKeys(rawJson);
+  makeCollapsible(raw);
+  wrapper.appendChild(raw);
+
+  return wrapper;
+}
+
+function buildMediaCard(item) {
+  var card = document.createElement("div");
+  card.className = "media-card";
+
+  // Thumbnail
+  var thumbUrl = item.thumbnail_url || item.image_url || "";
+  if (thumbUrl) {
+    var img = document.createElement("img");
+    img.className = "media-card-thumb";
+    img.loading = "lazy";
+    img.alt = item.title || item.name || "Media thumbnail";
+    img.onerror = function () {
+      this.style.display = "none";
+    };
+    img.src = thumbUrl;
+    card.appendChild(img);
+  }
+
+  // Info container
+  var info = document.createElement("div");
+  info.className = "media-card-info";
+
+  // Title (Year)
+  var title = document.createElement("div");
+  title.className = "media-card-title";
+  var titleText = item.title || item.name || "Untitled";
+  if (item.year || item.production_year) {
+    titleText += " (" + (item.year || item.production_year) + ")";
+  }
+  title.textContent = titleText;
+  info.appendChild(title);
+
+  // Metadata line: type, runtime, genres
+  var metaParts = [];
+  if (item.type || item.media_type) {
+    metaParts.push(item.type || item.media_type);
+  }
+  var runtime = _formatRuntime(item);
+  if (runtime) metaParts.push(runtime);
+  if (item.genres && item.genres.length) {
+    metaParts.push(item.genres.join(", "));
+  }
+  if (metaParts.length) {
+    var meta = document.createElement("div");
+    meta.className = "media-card-meta";
+    meta.textContent = metaParts.join(" \u00b7 ");
+    info.appendChild(meta);
+  }
+
+  card.appendChild(info);
+  return card;
+}
+
+function buildPlayButton(media) {
+  var btn = document.createElement("button");
+  btn.className = "media-play-btn";
+  btn.type = "button";
+  btn.dataset.streamUrl = media.stream_url || "";
+  btn.dataset.hlsUrl = media.hls_url || "";
+  btn.dataset.audioOnly =
+    media.audio_only === true ||
+    (media.container &&
+      /^(mp3|flac|ogg|aac|wma|wav|m4a|opus)$/i.test(media.container))
+      ? "true"
+      : "false";
+  btn.dataset.directStream =
+    media.supports_direct_play || media.supports_direct_stream
+      ? "true"
+      : "false";
+
+  btn.setAttribute(
+    "aria-label",
+    "Play " + (media.title || media.name || "media"),
+  );
+
+  var icon = document.createElement("span");
+  icon.textContent = "\u25b6";
+  btn.appendChild(icon);
+  var label = document.createElement("span");
+  label.textContent = "Play";
+  btn.appendChild(label);
+  return btn;
+}
+
+function buildMediaResultsList(results, totalCount) {
+  var container = document.createElement("div");
+  container.className = "media-results-list";
+
+  for (var i = 0; i < results.length; i++) {
+    var item = results[i];
+    var row = document.createElement("div");
+    row.className = "media-result-row";
+
+    // Small thumbnail
+    var thumbUrl = item.thumbnail_url || item.image_url || "";
+    if (thumbUrl) {
+      var img = document.createElement("img");
+      img.className = "media-result-thumb";
+      img.loading = "lazy";
+      img.alt = item.name || item.title || "Media thumbnail";
+      img.onerror = function () {
+        this.style.display = "none";
+      };
+      img.src = thumbUrl;
+      row.appendChild(img);
+    }
+
+    // Title (Year)
+    var titleSpan = document.createElement("span");
+    titleSpan.className = "media-result-title";
+    var titleText = item.name || item.title || "Untitled";
+    if (item.year || item.production_year) {
+      titleText += " (" + (item.year || item.production_year) + ")";
+    }
+    titleSpan.textContent = titleText;
+    row.appendChild(titleSpan);
+
+    // Metadata: type, runtime or season info
+    var metaParts = [];
+    if (item.type || item.media_type) {
+      metaParts.push(item.type || item.media_type);
+    }
+    var runtime = _formatRuntime(item);
+    if (runtime) metaParts.push(runtime);
+    if (item.season_name) metaParts.push(item.season_name);
+    if (
+      typeof item.index_number === "number" &&
+      typeof item.parent_index_number === "number"
+    ) {
+      metaParts.push(
+        "S" +
+          String(item.parent_index_number).padStart(2, "0") +
+          "E" +
+          String(item.index_number).padStart(2, "0"),
+      );
+    }
+    if (metaParts.length) {
+      var metaSpan = document.createElement("span");
+      metaSpan.className = "media-result-meta";
+      metaSpan.textContent = " \u00b7 " + metaParts.join(" \u00b7 ");
+      row.appendChild(metaSpan);
+    }
+
+    container.appendChild(row);
+  }
+
+  // "showing X of Y results" footer
+  if (typeof totalCount === "number" && totalCount > results.length) {
+    var count = document.createElement("div");
+    count.className = "media-results-count";
+    count.textContent =
+      "showing " + results.length + " of " + totalCount + " results";
+    container.appendChild(count);
+  }
+
+  return container;
+}
+
+// ---------------------------------------------------------------------------
+//  HLS lazy-loader (follows mermaid.js pattern from renderer.js:724-751)
+// ---------------------------------------------------------------------------
+var _hlsState = "idle";
+var _hlsQueue = [];
+
+function _loadHls(callback) {
+  if (_hlsState === "ready") {
+    callback();
+    return;
+  }
+  _hlsQueue.push(callback);
+  if (_hlsState === "loading") return;
+  _hlsState = "loading";
+  var script = document.createElement("script");
+  script.src = "/shared/hls-1.6.15/hls.min.js";
+  script.onload = function () {
+    _hlsState = "ready";
+    var q = _hlsQueue;
+    _hlsQueue = [];
+    for (var i = 0; i < q.length; i++) q[i]();
+  };
+  script.onerror = function () {
+    _hlsState = "idle";
+    var q = _hlsQueue;
+    _hlsQueue = [];
+    // Fall through — _activatePlayer will use stream_url since Hls is undefined
+    for (var i = 0; i < q.length; i++) q[i]();
+  };
+  document.head.appendChild(script);
+}
+
+function _isHlsUrl(url) {
+  return typeof url === "string" && /\.m3u8(\?|$)/i.test(url);
+}
+
+// ---------------------------------------------------------------------------
+//  Click-to-play delegated handler (follows img-placeholder pattern)
+// ---------------------------------------------------------------------------
+function _activatePlayer(btn) {
+  var url = btn.dataset.streamUrl;
+  var hlsUrl = btn.dataset.hlsUrl;
+  var isAudio = btn.dataset.audioOnly === "true";
+  var directStream = btn.dataset.directStream === "true";
+
+  var player = document.createElement(isAudio ? "audio" : "video");
+  player.controls = true;
+  player.autoplay = true;
+  player.className = "media-player";
+
+  // Prefer direct stream when the source supports it; fall back to HLS
+  // only when transcoding is needed.
+  if (directStream && url) {
+    player.src = url;
+  } else if (
+    hlsUrl &&
+    !isAudio &&
+    typeof Hls !== "undefined" &&
+    Hls.isSupported()
+  ) {
+    var hls = new Hls();
+    hls.loadSource(hlsUrl);
+    hls.attachMedia(player);
+  } else if (
+    hlsUrl &&
+    !isAudio &&
+    player.canPlayType("application/vnd.apple.mpegurl")
+  ) {
+    player.src = hlsUrl;
+  } else {
+    player.src = url;
+  }
+
+  player.addEventListener("error", function () {
+    var card = player.closest(".media-embed");
+    var titleEl = card ? card.querySelector(".media-card-title") : null;
+    var label = titleEl ? ": " + titleEl.textContent : "";
+
+    var err = document.createElement("div");
+    err.className = "media-player-error";
+    err.setAttribute("role", "alert");
+    err.textContent = "Failed to load stream" + label;
+
+    var retry = document.createElement("button");
+    retry.className = "media-play-btn";
+    retry.type = "button";
+    retry.dataset.streamUrl = url;
+    retry.dataset.hlsUrl = hlsUrl || "";
+    retry.dataset.audioOnly = String(isAudio);
+    retry.dataset.directStream = String(directStream);
+    retry.setAttribute("aria-label", "Retry" + label);
+    retry.appendChild(document.createTextNode("\u25b6 Retry"));
+
+    var container = document.createElement("div");
+    container.appendChild(err);
+    container.appendChild(retry);
+    player.replaceWith(container);
+  });
+
+  btn.replaceWith(player);
+}
+
+document.addEventListener("click", function (e) {
+  var btn = e.target.closest(".media-play-btn");
+  if (!btn) return;
+  e.preventDefault();
+  btn.disabled = true;
+  var labelEl = btn.querySelector("span:last-child");
+  if (labelEl) {
+    labelEl.textContent = "Loading\u2026";
+  } else {
+    btn.textContent = "\u25b6 Loading\u2026";
+  }
+
+  var hlsUrl = btn.dataset.hlsUrl;
+  var isAudio = btn.dataset.audioOnly === "true";
+
+  // If HLS URL present and not audio, ensure hls.js is loaded first
+  if (hlsUrl && !isAudio && _isHlsUrl(hlsUrl)) {
+    _loadHls(function () {
+      _activatePlayer(btn);
+    });
+  } else {
+    _activatePlayer(btn);
+  }
+});
+
+document.addEventListener("keydown", function (e) {
+  if (e.key !== "Enter") return;
+  var btn = e.target.closest(".media-play-btn");
+  if (!btn) return;
+  btn.click();
+});
+
 // ===========================================================================
 //  13. Plan review dialog
 // ===========================================================================

turnstone/ui/static/renderer.js

@@ -26,6 +26,7 @@ function inlineMarkdown(text) {
   text = text.replace(/~~(.+?)~~/g, "<del>$1</del>");
   // Images (must come before links — render as click-to-load placeholder)
   text = text.replace(/!\[([^\]]*)\]\(([^)]+)\)/g, function (m, alt, url) {
+    if (!/^\s*(https?:\/\/|data:image\/)/i.test(url)) return m;
     var safeAlt = alt || "Image";
     var domain = "";
     try {
@@ -53,9 +54,9 @@ function inlineMarkdown(text) {
       "</span>"
     );
   });
-  // Links (block javascript: scheme)
+  // Links (allow http, https, and same-origin relative URLs only)
   text = text.replace(/\[([^\]]+)\]\(([^)]+)\)/g, function (m, label, url) {
-    if (/^\s*javascript:/i.test(url)) return m;
+    if (!/^\s*(https?:\/\/|\/(?!\/))/i.test(url)) return m;
     return (
       '<a href="' +
       url +
@@ -89,8 +90,16 @@ function inlineMarkdown(text) {
 document.addEventListener("click", function (e) {
   var ph = e.target.closest(".img-placeholder");
   if (!ph) return;
+  var raw = ph.getAttribute("data-src") || "";
+  if (!/^(https?:\/\/|data:image\/)/i.test(raw)) return;
+  var src;
+  try {
+    src = new URL(raw).href;
+  } catch (_e) {
+    return;
+  }
   var img = document.createElement("img");
-  img.src = ph.getAttribute("data-src");
+  img.src = src;
   img.alt = ph.getAttribute("data-alt");
   img.loading = "lazy";
   ph.replaceWith(img);

turnstone/ui/static/style.css

@@ -867,7 +867,7 @@ body { position: static; }
 .approval-tool { padding: 8px 12px; border-bottom: 1px solid var(--border); }
 .approval-tool:last-of-type { border-bottom: none; }
 .approval-tool .tool-name { color: var(--yellow); font-weight: 600; font-size: 11px; margin-bottom: 3px; }
-.approval-tool .tool-cmd { color: var(--fg-bright); white-space: pre-wrap; word-break: break-all; }
+.approval-tool .tool-cmd { color: var(--fg-bright); white-space: pre-wrap; word-break: break-all; max-height: 120px; overflow: hidden; }
 .approval-tool .tool-cmd .dollar { color: var(--green); }
 .approval-tool .tool-diff { white-space: pre-wrap; font-size: 12px; margin-top: 4px; }
 .approval-tool .tool-diff .diff-del { color: var(--red); }
@@ -961,6 +961,128 @@ body { position: static; }
   letter-spacing: 0.03em;
 }
 
+/* ==========================================================================
+   Media embed cards (MCP tool output with stream_url / results)
+   ========================================================================== */
+.media-embed {
+  border-top: 1px solid var(--border);
+  background: var(--code-bg);
+}
+.media-card {
+  display: flex;
+  gap: 12px;
+  padding: 10px 12px;
+  align-items: flex-start;
+}
+.media-card-thumb {
+  width: 80px;
+  height: 120px;
+  object-fit: cover;
+  border-radius: var(--radius-sm);
+  background: var(--bg-surface);
+  flex-shrink: 0;
+}
+.media-card-info {
+  flex: 1;
+  min-width: 0;
+}
+.media-card-title {
+  font-family: var(--font-display);
+  font-size: 14px;
+  font-weight: 600;
+  color: var(--fg-bright);
+  margin-bottom: 2px;
+}
+.media-card-meta {
+  font-size: 11px;
+  color: var(--fg-dim);
+  margin-bottom: 6px;
+}
+.media-play-btn {
+  display: inline-flex;
+  align-items: center;
+  gap: 6px;
+  padding: 4px 12px;
+  font-size: 12px;
+  font-family: var(--font-mono);
+  color: var(--accent);
+  background: transparent;
+  border: 1px solid var(--accent);
+  border-radius: var(--radius-sm);
+  cursor: pointer;
+  transition: background 0.12s ease;
+}
+.media-play-btn:hover {
+  background: rgba(229, 160, 66, 0.1);
+}
+.media-play-btn:focus-visible {
+  outline: 2px solid var(--accent);
+  outline-offset: 2px;
+}
+.media-play-btn:active {
+  background: rgba(229, 160, 66, 0.2);
+}
+.media-play-btn:disabled {
+  opacity: 0.5;
+  cursor: wait;
+}
+.media-player {
+  width: 100%;
+  max-height: 480px;
+  background: #000;
+  border-radius: 0;
+}
+audio.media-player {
+  max-height: 54px;
+}
+.media-player-error {
+  color: var(--red);
+  font-size: 12px;
+  padding: 8px 12px;
+  background: var(--code-bg);
+}
+.media-results-list {
+  padding: 6px 12px;
+}
+.media-result-row {
+  display: flex;
+  gap: 8px;
+  padding: 4px 0;
+  align-items: center;
+  font-size: 12px;
+  border-bottom: 1px solid var(--border);
+}
+.media-result-row:last-child {
+  border-bottom: none;
+}
+.media-result-thumb {
+  width: 32px;
+  height: 32px;
+  object-fit: cover;
+  border-radius: var(--radius-sm);
+  background: var(--bg-surface);
+  flex-shrink: 0;
+}
+.media-result-title {
+  color: var(--fg-bright);
+  font-weight: 500;
+}
+.media-result-meta {
+  color: var(--fg-dim);
+  font-size: 11px;
+}
+.media-results-count {
+  text-align: right;
+  font-size: 10px;
+  color: var(--fg-dim);
+  padding: 4px 0;
+}
+@media (max-width: 480px) {
+  .media-card { flex-direction: column; }
+  .media-card-thumb { width: 100%; height: auto; max-height: 200px; }
+  .media-player { max-height: 280px; }
+}
+
 /* ==========================================================================
    Plan review dialog
    ========================================================================== */
@@ -1467,6 +1589,7 @@ body { position: static; }
   #health-indicator, #theme-toggle,
   #mcp-status, .msg-assistant tbody tr,
   .msg-assistant .img-placeholder,
+  .media-play-btn,
   #new-ws-cancel, #new-ws-submit,
   #new-ws-box input, #new-ws-box select,
   .split-handle, .pane-action-btn,

uv.lock

@@ -155,7 +155,7 @@ wheels = [
 
 [[package]]
 name = "anthropic"
-version = "0.88.0"
+version = "0.89.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
@@ -167,9 +167,9 @@ dependencies = [
     { name = "sniffio" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/86/68/565f13059c0a6a6fd5f96f306f2a0fb478a0e1174ec18a4df16b5fac9379/anthropic-0.88.0.tar.gz", hash = "sha256:f4c7f6863d08c869913516f08d658fe53caaf8bcc4fbea3218df343d2a876c58", size = 596654, upload-time = "2026-04-01T19:59:05.287Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/60/af/862e216dd6c5e9bc02fb374eeaaa19017c51b90ddfa5692668a3811947bd/anthropic-0.89.0.tar.gz", hash = "sha256:f3d75b8ccef4b35f3702639519e461eba437d4bcdfabb69378c65a02ab7bda66", size = 596758, upload-time = "2026-04-03T18:57:01.348Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ad/ac/68f646998160c9f2e6f9353a31dd87292ef02b915b455aaf70a52a059a75/anthropic-0.88.0-py3-none-any.whl", hash = "sha256:71898b32332bc75d9739bc10095288d40a29605da6d00da2fe832b1aa036552f", size = 478338, upload-time = "2026-04-01T19:59:03.832Z" },
+    { url = "https://files.pythonhosted.org/packages/22/ba/9f973f22abb512d5d17428a76e4ecbc8d49b9dd1b5a1152576d48c24dc1d/anthropic-0.89.0-py3-none-any.whl", hash = "sha256:c6d23854af798f2471ca3bc653cca394d392cc272fe803d3da9d63575b8445f0", size = 478847, upload-time = "2026-04-03T18:56:59.54Z" },
 ]
 
 [[package]]
@@ -401,14 +401,14 @@ wheels = [
 
 [[package]]
 name = "click"
-version = "8.3.1"
+version = "8.3.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
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