Local lanes dropped the knob's graded value unless the operator declared
reasoning_effort_values (and, on the template channel, an effort key) —
picking Max sent a bare thinking toggle and the effort select
degenerated into seven positions that all meant 'on'. The user's
setting now always rides:
- openai-compatible: the flat reasoning_effort param carries the knob
verbatim (effort_passthrough on the lane default); declared values
still snap ordinally, and a declared effort_param still claims the
template channel and suppresses the flat param.
- anthropic-compatible: the graded value rides chat_template_kwargs
alongside the toggle whenever reasoning control is engaged — under
the operator's effort_param, else the conventional fallback key
(reasoning_effort); templates that don't reference the kwarg ignore
it. thinking_mode=none still injects nothing.
- Commercial lanes untouched: empty declared values still mean 'no
effort control' (o1-mini) and the ordinal snap is unchanged.
Golden writer now pins ensure_ascii=False: the baselines' literal em
dashes came from a hand edit (03f82521) the default-escaping writer
could never reproduce — regens no longer churn unrelated lines.
Local-lane model ids are operator-chosen strings (vLLM
--served-model-name), so a prefix collision with a cloud model id
inherited that model's sampling and effort contract: a box named
o3-distill silently lost temperature support, and one named
gpt-5.5-my-finetune was sent gpt-5.5's snapped reasoning_effort values
it never declared. Both surfaces of the lane now return plain defaults
(OPENAI_COMPAT_DEFAULT in _openai_common): the chat class directly, and
the responses pin via a compat-mode OpenAIResponsesProvider mirroring
AnthropicProvider(compat=True). Everything beyond the defaults is
declared by the operator on the model definition, matching the
anthropic-compatible lane and lookup_model_capabilities' documented
'no static table for local models' contract. The commercial openai
lane (Responses-only) is untouched.
Pre-split tests that reached commercial rows through the chat-class
OpenAIProvider alias now source them from lookup_openai_capabilities;
their subject (registry rows + shared gating helpers) is unchanged.
Capability-registry corrections verified against the official OpenAI
reasoning guide, the Azure reasoning-models matrix (2026-06 revision),
and the Anthropic models-overview/effort/migration pages (2026-07):
OpenAI (vocabulary confirmed none/minimal/low/medium/high/xhigh — no
"max" level exists; knob max rides the xhigh ceiling via the ordinal
snap):
- o1/o3/o3-mini/o3-pro/o4-mini declare low/medium/high (every o-series
model except o1-mini) — without declared values the session knob was
silently dropped for these models. o1-mini stays effort-free.
- gpt-5.5 default corrected none -> medium (5.5 reasons by default,
unlike 5.1-5.4).
- gpt-5.1-codex-max gets an explicit row: it prefix-matched the
gpt-5.1 row (no xhigh), capping the knob's xhigh at high on the one
model xhigh was introduced for.
Anthropic (effort-page matrix):
- claude-sonnet-5 row added — it previously fell through to
_ANTHROPIC_DEFAULT (manual budgets, 200k ctx, no effort), all wrong:
adaptive-by-default thinking (manual budgets are a 400), sampling
params rejected, 1M ctx / 128k out, effort low..max incl. xhigh.
- claude-sonnet-4-6 gains its documented "max" effort level (knob
xhigh now rides max, not high) and the stale 64k max_output becomes
the documented 128k.
- fable-5 / opus-4-8 / opus-4-7 / opus-4-6 / opus-4-5 rows verified
correct as declared.
Knob semantics completed: resolve_reasoning_effort now forwards the
knob's "none" position verbatim when the model DECLARES an explicit
none level (gpt-5.1+, grok-4.3) — omitting the param there leaves a
reasoning-on server default (gpt-5.5: medium) in charge of a knob
that promises off. Models without a declared none still omit, and
none is never a snap target. Parity harness swaps its synthetic
openai shape for the real gpt-5.5 registry row.
The knob domain grew xhigh/max after the snapping fallbacks were
written, which silently inverted their semantics: off-list meant
"unrecognized string" then, but now usually means "above the model's
ceiling", where falling back to the default tier is directionally
wrong (grok-4.3 at knob max got low; values low/medium/high at knob
xhigh got medium; Anthropic manual mode gave xhigh/max a 4096 budget
while high got 16384).
One rule everywhere now, via snap_reasoning_effort in _protocol:
exact match wins; otherwise the smallest declared level ranking at or
above the knob; above the ceiling, the ceiling. "none" is never a
snap target, and default_reasoning_effort only catches values the
ordinal snap cannot rank.
- resolve_reasoning_effort (flat chat / responses / validated
effort_param lanes) snaps ordinally: xhigh over (low, medium, high)
now sends high; xhigh over DeepSeek-style (high, max) sends max —
matching DeepSeek's official xhigh-to-max aliasing, so a declared
values list now reproduces that contract instead of defeating it.
- _map_reasoning_to_effort (native output_config) rounds up too:
knob xhigh on Opus 4.6 (low, medium, high, max) rides max instead
of silently dropping output_config.
- EFFORT_BUDGET_MAP is monotone across the whole knob domain:
minimal/low 1024 (API floor), medium 4096, high 16384, xhigh 32768,
max 65536. Unknown strings still fall to the 4096 default.
Google defaults are unaffected (ceiling and default coincide at
high); wire goldens unchanged. Parity harness caught the budget
clamp interacting with its own max_tokens during development —
capture budget raised above the largest manual budget.
Seven knob positions render as seven behaviors in the UI, but the real
ladder depends on the lane and the model: qwen3.6 has two (off/on),
DeepSeek-V4 three, Claude 4.6 five. Operators had no way to see which
positions alias — the confusion class behind silently-equal effort
levels.
providers/effort_ladder.py projects the knob domain through the same
mapping functions the providers use at request time (resolve_reasoning_
effort, reasoning_template_kwargs, the manual budget map — hoisted to a
shared constant so the projection can't drift), yielding
{value, effective} rows where equal tokens promise identical requests.
/v1/api/models rows now carry the ladder (guarded per row), and
POST /v1/api/admin/models/effort-ladder computes it for the admin
modal's unsaved edits.
The admin per-model effort select and the skill launch-config effort
select annotate aliased positions ("Max (= high)", "None (model
default)") with a sends-tooltip; annotations refresh as thinking-mode /
effort-param / capabilities fields change. The ladder describes what
Turnstone sends — server-side templates may alias further (DeepSeek-V4
folds low/medium into its default high tier).
Post effort-knob rework, "Enabled" (manual) means knob-controlled —
effort none turns thinking off. Operators who want the pre-#771
always-on behavior (knob never disables) previously had to hand-write
thinking_mode "adaptive" into the raw capabilities JSON. The dropdown
now offers all three representable modes — None / Effort-knob
controlled / Always on — and the edit-load lift captures adaptive
instead of relegating it to raw JSON.
Cross-checked online: Qwen3.6's template documents enable_thinking +
preserve_thinking only — no effort parameter exists (vLLM's flat
reasoning_effort convenience boolean-maps to the same toggle).
DeepSeek-V4 officially accepts reasoning_effort high/max with Think
High as the default thinking tier and low/medium→high, xhigh→max
aliasing — so freeform effort_param passthrough matches the contract
exactly, and a declared values list omitting xhigh/max would make
Think Max unreachable. Live probes on both boxes agree with the
official contracts once the default-tier framing is applied.
Verified findings applied:
- adaptive thinking_mode never knob-disables: the shared mapping now
sends the toggle unconditionally true for adaptive (the native
adaptive branch ignores the knob's none), while manual keeps the
knob-driven contract. Restores the invariant the deleted chat-lane
code upheld.
- a set effort_param suppresses the flat top-level reasoning_effort on
the chat lane: the template channel replaces it — double-sending
could 400 on schema-strict servers and disagree with operator pins.
- admin edit-save no longer drops a stored thinking_param when the
thinking-mode dropdown is empty: the raw-JSON strip now only fires
when a mode value actually round-trips through the dropdown.
- effort_param persistence gated on the local-server lanes so a value
lingering across a provider switch never lands on commercial rows.
- three stale _compat_extra_params references renamed to
merge_reasoning_template_kwargs.
Documented dispositions (no code change): the knob-none-disables flip
on upgrade is intentional and now carries an upgrade note; gateways
fronting real Claude belong on provider=anthropic with a custom
base_url (the compat lane is vLLM-schema-only); nonstandard
thinking_mode strings staying inert is the intended allowlist
contract. The real anthropic provider is unaffected throughout —
official Claude models keep native thinking/output_config.
Hoist the compat-lane injection into _protocol.merge_reasoning_template_kwargs
(next to ModelCapabilities — one implementation for both local-server lanes)
and retire OpenAIChatCompletionsProvider._apply_thinking_mode in its favor:
_finalize_extra_body now receives the session effort knob, so thinking_mode
manual/adaptive maps knob "none" to an explicit thinking_param false
(previously the toggle was unconditionally true) and caps.effort_param
carries the graded effort key on chat completions too. Operator
server_compat pins still win; the Responses surface is untouched (native
reasoning handles effort itself).
The admin Models form grows an "Effort param" field that round-trips like
thinking_param: lifted out of the raw capabilities JSON on edit-load,
re-added on save, cleared by emptying the field.
Verified live against qwen3.6-27b /v1/chat/completions: knob medium streams
reasoning_content, knob none suppresses it.
The compat lane sent no reasoning control at all: vLLM's /v1/messages
has no thinking request field, thinking_mode stayed "none", and the
session effort knob was silently dropped. The reasoning levers live in
the chat template, so fold them into extra_body chat_template_kwargs
(_compat_extra_params): thinking_mode manual/adaptive maps the knob
onto caps.thinking_param (effort "none" = off, mirroring the native
manual-mode contract), and caps.effort_param (new ModelCapabilities
field) carries a graded effort value for gpt-oss-style templates,
validated against reasoning_effort_values when declared. Operator
server_compat entries win on key collision; native thinking params,
temperature forcing, and output_config never fire on compat.
resolve_reasoning_effort moves from _openai_common to _protocol next to
ModelCapabilities — importing it into _anthropic would otherwise cross
provider families.
The admin Models form now shows and round-trips the thinking-mode
dropdown for this lane; the #661 hide was premised on thinking_mode
being inert here, which this change inverts.
Verified live against qwen3.6-27b on vLLM /v1/messages: knob medium
streams a thinking block, knob none suppresses it, an operator pin
beats the knob.
turnstone-eval was misnamed: it was a prompt optimizer, not a measurement
harness. Split the 3252-line turnstone/eval.py into a strictly one-way
dependency (optimizer -> eval-core; core never imports the optimizer):
- turnstone/eval/core.py measurement substrate — everything up to and
including _run_iteration: provider detection, NullUI, HeadlessSession,
the test runner, score_run, aggregation, and neutral reporting.
- turnstone/eval/cli.py new measure-only `turnstone-eval` — the old
--no-optimize path promoted to the whole job (one _run_iteration call,
then print the summary table).
- turnstone/optimizer.py the UCB self-modify loop and its multi-agent
pipeline (analyst/optimizer/observer/diversifier/tool optimizer), now
`turnstone-optimizer`; imports from eval.core only.
- turnstone/eval/__init__.py re-exports the core public API for
back-compat (score_run, _match_action, _run_iteration, HeadlessSession).
_apply_tool_overrides lives in core (HeadlessSession needs it) rather than
alongside the other tree helpers, so the dependency stays one-way.
Breaking change: `turnstone-eval` now measures; use `turnstone-optimizer`
to optimize. Both code paths are behaviour-preserving — the moved function
bodies are byte-identical.
Built-in persona base prompts move from inline DB text / base.md into
prompts/personas/<slug>.md — code-owned, PR-reviewable, drift-proof.
base.md / base_coordinator.md become personas/engineer.md / orchestrator.md.
Prompt source is now explicit in storage instead of inferred in app logic:
a new base_prompt_file column plus CHECK (base_prompt IS NOT NULL OR
base_prompt_file IS NOT NULL) — two nullable columns, never both empty.
Resolution is a coalesce (base_prompt else load(base_prompt_file)), frozen
into the workstream stamp at creation. base_prompt_file marks a persona as
built-in (code-only, un-archivable); an operator override on a built-in is
allowed and wins over the file. "Inherit the kind default" is a
workstream-creation act (is_default), not a persona-row state.
Migration 063:
- seeds reference their file (base_prompt NULL); no runtime file reads —
the backfill's frozen prompt text is inlined as a point-in-time snapshot
so migration history stays self-contained and reproducible.
- every existing workstream is stamped by kind (creative -> writer, else
the kind default), set-based (INSERT..SELECT via temp tables) with the
persona column added after the bulk writes to shorten its lock window.
Storage guards (both backends): operators must supply base_prompt;
built-ins can't be archived or have base_prompt_file set via the API;
clearing an operator persona's only source is rejected.
Follow-ups reviewed alongside (#756): soft-set visibility docstring scoped
to per-process; _apply_persona_snapshot / _current_persona_snapshot own the
stamp round-trip; spawn approval-header args (skill/name/target_node)
flattened+capped like persona; server-side tool injection generalized to
replace-only (client-def gated, incl. the xAI include forwarding). Seed
copy revised (researcher soft; de-costumed prose; engineer de-biased).
New test_schema_parity asserts create_all matches the alembic head.
Closes#683 groundwork; ruff + strict mypy clean, full suite green.
Spec models now describe what the endpoints do: ListPersonasResponse
declares the tool_inventory the shelf depends on, both console create
models declare persona, CreatePersonaRequest declares org_id, and
UpdatePersonaRequest documents the null-vs-absent split (null clears
base_prompt/tool_allowlist, null on flags/kinds is ignored). Console
OpenAPI regenerated.
Protocol contracts match the implementations: update_persona's return
covers the no-op case, create_persona's raises-list is complete, and
both extended row-shape docstrings gain their tail columns plus the
append-only rule. The workstreams.persona comments say slug, not
display name.
Page corrections from the docs review: personas.md documents the
creative_mode-to-writer migration conversion, the mid-session /resume
MCP-lever behavior, visibility-based nudge gating, the soft-set
prompt-cache cost, and the executive tool list — and drops internal
jargon. The changelog entry moves under [Unreleased] with the house
breaking-marker style and the auto-conversion note. coordinator-skills
and the API tour stop using persona to mean framing; governance,
api-reference, sdk, console, tools, and memory pick up the new
permission family, endpoints, kwargs, picker, and lever caveats.
docs/personas.md covers the four levers, the resolve-once/stamp-forever
snapshot semantics, the seed matrix, per-surface selection, authoring
rules, and RBAC; architecture.md's config-persistence paragraph swaps
the removed creative_mode for the persona stamp.
* refactor(doctor): replace turnstone-bootstrap with turnstone-doctor
turnstone-bootstrap was an LLM setup wizard for Day-0; run.sh now owns install.
Repurpose its LLM/conversation plumbing into turnstone-doctor — a diagnose-only
tool for a running cluster.
- Preflight detects the install kind (docker-compose/systemd/pip/source) from
config.toml + TURNSTONE_* env, with secret redaction.
- Self-configuring brain resolves the cluster's own model from config/env/storage
read-only (no migrations, no create_all), falling back to interactive
selection; the attempt itself is the LLM-backend health check.
- Deterministic version check: installed version, cluster drift via the console's
authoritative /health, and latest upstream stable/experimental (offline-safe).
- Read-only diagnostic tools (read_file, compose/systemd/journal, http_health,
check_llm_backend, node_health, finish) behind one secret-scrubbing chokepoint;
no generic shell, so read-only is structural.
- node_health reaches a node the right way for the detected install kind
(exec-into-container for compose, direct HTTP otherwise), overridable per node
for mixed clusters.
- mTLS-aware: forwards [database] SSL params and reports node-mesh mTLS instead of
mislabelling healthy nodes "unreachable".
init_storage gains a backward-compatible create_tables override for read-only
opens. Entry point turnstone-bootstrap -> turnstone-doctor; README/QUICKSTART/
architecture/docker docs, the bundled compose header, run.sh, and the CI smoke
updated. CHANGELOG deferred.
* fix(doctor): address Copilot + CodeQL review findings on #718
Validated all seven review findings (none false positives) and fixed:
- check_llm_backend now applies the same scheme / metadata-host guard as
http_health (extracted to _assert_safe_http_url), so a model-supplied
base_url can't be steered at the cloud metadata endpoint or a file:// URL.
- node_health no longer double-appends the default port when the operator
passes host:port (regression: 10.0.0.5:8081 -> http://10.0.0.5:8081:8080).
- node_health install_type enum uses "git-source" to match the label the
rest of the module and the prompt/report show the model (a schema-strict
provider would otherwise reject the value the model is told to use).
- _read_api_creds takes base_url + api_key as a unit from the first config
source that defines either field, then env-fills, instead of splicing the
two across different config files into a pair that exists in no real config.
- _mask_secrets masks assignment-shaped content inside comment lines, so a
commented-out real secret can't leak through read_file / the report; prose
comments (no KEY=value shape) still pass through untouched.
- drop the mixed import styles CodeQL flagged in doctor.py and test_doctor.py.
Adds 5 tests; ruff + mypy clean; full doctor suite passes (129).
A cancelled agent previously discarded its own ledger and reported a bare
"(task interrupted by user)" — fabricating the *outcome* (read downstream
as "nothing happened"), which invites a double-send as readily as a
dropped record causes an orphan. Make the fold-back honest, and propagate
an owner's cancel down the coordinator subtree.
- task_agent (single + parallel): on cancel, fold back a deterministic
disposition built from the agent's in-memory ledger — actions completed,
the in-flight action flagged outcome-UNKNOWN, and not-started calls —
instead of the opaque interrupted string.
- coordinator cancel now auto-propagates to its direct children via a
post_cancel hook on the shared cancel handler (cooperative fan-out; no
blocking drain).
- synthesized cancelled tool results now read outcome-UNKNOWN rather than
implying the call never ran.
- remove the now-redundant stop_cascade operator endpoint (handler, route,
OpenAPI spec + schema, tests, docs); a coordinator cancel supersedes it.
The judges and the regex ReDoS probe ran a blocking call on a
ThreadPoolExecutor and abandoned the worker with shutdown(wait=False) on
timeout or cancel. concurrent.futures joins every executor worker from an
atexit hook regardless of wait=False, so a wedged call could pin
interpreter exit — and hang the test suite at shutdown.
Add turnstone/core/deadline.py::run_with_deadline: run a blocking callable
on a daemon thread bounded by a wall-clock timeout and an optional cancel
event. A daemon worker is never joined at exit, so abandoning one is safe.
Migrate three sites onto it:
- OutputGuardJudge.evaluate()
- IntentJudge._evaluate_single / _run_judge — this also removes
_ExecutorPoisonedError and the executor-restart dance: per-call daemon
threads can't poison a shared single-slot pool, so a timeout now returns
None and the caller delivers one fallback verdict.
- console/server.py _validate_regex_pattern (regex ReDoS probe)
Also:
- Double the default judge LLM timeouts for slower local models:
judge.timeout 60->120s and judge.output_guard_llm_timeout 30->60s
(settings registry, JudgeConfig dataclass, --judge-timeout CLI default,
class docstring, docs). Correct a stale doc that described the per-turn
timeout as a total budget across turns.
- Raise the regex probe bound 0.5->3.0s so a legitimately complex pattern
isn't false-flagged as catastrophic backtracking.
- CI: run pytest with -v instead of -q so a hang names the offending test
instead of riding the job timeout.
- Tests: cover deadline.py and the regex validator; move test_judge.py off
fixed sleeps onto the existing _wait_for helper.
Hardened service + slice + node-identity drop-in template + a README for
running a turnstone-server outside Docker that joins the compose cluster —
the production-shaped counterpart to the one-liner in docs/docker.md. Secrets
stay in config.toml; per-host identity + cluster URLs go in the drop-in. The
README notes the cross-host mTLS caveat (turnstonelabs/lacme#22).
A turnstone-server running outside the compose network ("bare-metal", e.g. a
local-GPU box) couldn't fully join: it can't resolve the in-cluster console
(console:8090) to enroll its mTLS cert, and SearxNG was unreachable for
web_search. Only Postgres was published.
Publish the console's plain-HTTP ACME endpoint (:8090) and SearxNG (:8081)
alongside Postgres, all bound via one knob TURNSTONE_HOST_IP (default 127.0.0.1
-- nothing new on the LAN; set it to the host's LAN IP for a node on another
machine). Postgres keeps honoring the legacy POSTGRES_BIND as a fallback, so
existing .env files don't break.
The node's TLS client now honors TURNSTONE_CONSOLE_URL so a bare-metal node can
point at the published ACME endpoint instead of the unreachable in-cluster name
(empty = in-cluster service discovery, unchanged).
Docs (docker.md, tls.md), the run.sh-generated .env, and the bootstrap wizard
updated to match. The advertised host is the cert's primary SAN and the console
collector dials it back, so mTLS hostname verification holds both ways.
The server (:8080) and console (:8090) both set a cookie named
`turnstone_auth`. Cookies ignore port (RFC 6265), so on a shared host
(localhost dev, the Electron build, single-box installs) logging into one
surface overwrote the other's cookie and 401'd the first session.
Give each surface its own cookie name -- `turnstone_auth_server` /
`turnstone_auth_console` -- threaded as a required `cookie_name` argument
through the cookie builders, `check_request`, `AuthMiddleware`, and the six
shared auth handlers (login/logout/setup/whoami/refresh/oidc_callback). Each
app passes its own constant; the parameter is required (no default) so a
forgotten caller fails loudly instead of silently reverting to the legacy name.
Names key on role, not node: the cluster shares one JWT identity and the
console->node proxy re-mints a bearer token (dropping Set-Cookie), so
per-instance names would break identity portability and aren't used.
Hard cutover: the legacy `turnstone_auth` cookie is no longer read and
self-expires within its 24h TTL (one forced re-login). JWT audience was
already enforced, so the shared cookie was a session clobber, not an auth
bypass.
The coordinator memory scope was keyed by the session's ws_id, so every
new coordinator session started with an empty namespace and its rows
were orphaned on close — coordinator memory never actually persisted.
Re-key the scope to the coordinator's creator user_id: one durable
orchestration namespace per user, shared by all of that user's
coordinator sessions (concurrent ones included; upsert-by-name is the
collision rule).
The child-containment threat model is unchanged: the gate is session
KIND — children are always interactive and share the parent's user_id,
so _validate_scope rejects them before scope resolution, and the REST
memories API still rejects the coordinator scope outright. The implicit
visibility lane now also fails closed on an empty scope_id to match the
explicit search/list lanes (the storage helpers treat a falsy scope_id
as 'no scope_id filter', which would have read every user's rows).
Anonymous coordinators are no longer constructible: ChatSession refuses
kind=COORDINATOR with an empty user_id at the constructor — the single
choke point covering create, rehydration of legacy rows (surfaced by
the open handler as a 503 with remediation text), and any future host —
and the console no longer masks an empty uid as a phantom 'system'
principal when minting coordinator JWTs, per CoordinatorTokenManager's
documented 'sub = the real creator user_id' contract.
Migration 061 carries existing coordinator rows across: rows whose
owning workstream is gone or ownerless are deleted (unreachable under
user keying), same-name collisions within a user keep the newest
updated row (memory_id tiebreak), and survivors re-key to the owner's
user_id.
Copilot review on #661: empty base_url let the SDK fall back to
https://api.anthropic.com, sending compat-shaped requests to the
commercial API. The lane is local-only by definition, and the /v1-strip
edge case already established fail-loudly-over-silent-prod-retarget;
apply the same principle to the empty case. create_client raises an
actionable ValueError; the admin Detect path surfaces it as a clean
error string via probe_model_endpoint's existing handler.
Add provider id "anthropic-compatible": the existing AnthropicProvider
pointed at Anthropic-compatible local servers (vLLM /v1/messages),
mirroring the openai/openai-compatible split. Registry-only — configured
via the admin Models tab or [models.*] toml, not exposed on the bare
--provider flag, so the CLI/server prod-URL defaults are unreachable for
the lane and real-Anthropic behavior is untouched.
Lane behavior (live-verified against vLLM 0.22.1rc1 + DeepSeek-V4-Flash):
- Capability defaults replace the Claude static table: token_param
max_tokens, thinking_mode none, web_search/tool_search/vision off,
reasoning replay on. vLLM rejects Anthropic server-side tool types
(tools require input_schema) and ignores the thinking request param,
so neither is sent; thinking blocks still stream back and round-trip
through the native lane verbatim.
- Reasoning toggles via server_compat extra_body chat_template_kwargs
(first-class vLLM request field; request-level keys beat server
defaults). _build_thinking_and_kwargs forwards non-internal
extra_params as SDK extra_body; thinking_budget_tokens stays internal.
- No temperature force: thinking_mode none skips the Claude-only
temperature=1.0 requirement.
Admin UI: provider option + URL placeholder (base_url without /v1 — the
SDK appends /v1/messages); the server-compat section shows only the
extra-body field for the lane. thinking_mode round-trips through the
form dropdown for every provider except anthropic-compatible, where it
stays in the raw capabilities JSON — the edit-load lift and save restore
use the same predicate so stored overrides are never silently dropped.
Docs: architecture.md gains the lane subsection incl. verified quirks
(thinking param dropped by vLLM; stop_sequences cut inside thinking and
report end_turn; usage has no cache fields; images need a multimodal
model; mid-conversation system turns are per-model opt-in).
Negative-tested: removing the _INTERNAL_EXTRA_PARAMS exclusion fails
test_internal_keys_not_leaked; the live test drives a streamed turn with
the chat_template_kwargs toggle and asserts no reasoning deltas.
* docs: 1.6.0 changelog — roll up the 1.5→1.6 line for stable
Replaces [Unreleased] with the 1.6.0 section: 320 main-only commits
since the stable/1.5 divergence grouped into theme bullets (license,
trajectory/migration-060, web search, rerank/memory, approvals/judge,
L-shell, shelf, SSE, providers, cluster ops, security). Breaking
changes aggregated up top; migration-060 backup callout reshaped from
discussion #631 for the stable audience.
* docs: add the stable/1.6 track to the changelog preamble
* docs: retire the stable/1.4 track — current + one prior policy
Changelog preamble down to three tracks with the policy stated;
1.4 retirement noted in the 1.6.0 Removed section (final release
v1.4.0; tags/artifacts remain, BUSL-1.1 as shipped). releasing.md
track table, policy bullet, and examples brought up to the 1.6.0
promote cycle — the doc was still describing the 1.4-stable era.
Field incident: the coordinator LLM hand-copied a child ws_id and
collapsed its aaa run to a, producing a 30-char id. inspect said "not
found", wait called it "denied", neither offered recovery, and the model
concluded the child was dead and dropped the lane — silent report
degradation while the child kept working.
- validate model-supplied ws_id args at the tool boundary
(send/close/cancel/delete/inspect/wait): full 32-hex ids pass through
at unchanged storage cost; a child's exact legacy id still resolves;
anything else fails fast with a did-you-mean (capped Levenshtein <=3
over the coord's own children) plus a child roster. Near-misses never
auto-resolve; display names are not addresses (mutable, non-unique) —
a name ref errors with a pointer at the right id
- wait_for_workstream: rename per-entry state "denied" -> "not_found"
with an honest sentinel; malformed refs error before any waiting
(invalid_ws_ids); a well-formed id that is foreign, missing, or
hard-deleted mid-wait aborts the wait on the tick that observes it
instead of burning the timeout (mode=all was unsatisfiable) or riding
along to complete=True (silent lane loss); mode=all completes only
when every id is real-terminal; entries carry the child display name
- one not-found payload across all verbs: foreign and nonexistent stay
byte-identical (no existence oracle), hints reference only the coord's
own children, echoed refs clipped in error strings; invalid_ws_ids and
not_found share one per-ref shape with the roster hoisted top-level
- inspect ownership now requires user_id parity via _row_in_own_subtree,
matching the wait/mutating gates (#506) — closes the forged-parent
cross-tenant read
- session exec serializes the structured recovery payload (results +
did_you_mean + children) on unresolvable-id wait errors instead of
collapsing to the bare error string
- tool JSON descriptions + coordinator docs updated to the new contract;
incident regression test pins the captured aaa-collapse ids
* chore: relicense BUSL-1.1 -> Apache 2.0 for 1.6.0
Flips every license artifact in the tree; 1.5.x and earlier remain
BUSL-1.1 per their release-time LICENSE files. Contributor consent
record: #548 (rationale: #546).
- LICENSE: canonical Apache 2.0 text
- NOTICE: new; copyright line + pointer to THIRD-PARTY-NOTICES
- pyproject.toml: SPDX expression + explicit license-files trio
- Dockerfile: COPY the license trio (hatchling needs them at build)
- THIRD-PARTY-NOTICES: BUSL line reworded; bundled-version drift
fixed (KaTeX 0.17.0, Mermaid 11.15.0, hls.js 1.6.16)
- README badge + License section, CONTRIBUTING inbound-license line,
TS SDK package(+lock), example pyproject
- docs/pgbouncer.md: drop stray ':' introduced in #353
* docs: add CONTRIBUTORS.md
* chore: drop LICENSE leading blank line
The apache.org LICENSE-2.0.txt begins with a newline; the SPDX
canonical text and GitHub license templates do not. Use the
conventional form — detection is whitespace-normalized either way.
Review follow-up: the ON CONFLICT rationale lived verbatim in three
places (protocol docstring + both backend comments). Keep the prose in
the protocol — the contract's home — and point the backends at it.
Also recommend cancel_on_approval=true in docs for deployments where
the judge shares one local inference backend with the session model.
A whole-stack restart races every node against the console for the CA
fetch (compose re-enforces depends_on ordering only on `up`): losers
logged one warning and served plain HTTP for their lifetime, while
winners served mTLS that the plain-HTTP container healthcheck could
never probe — leaving "healthy" plaintext nodes and "unhealthy"
working ones.
- TLSClient.init() grows attempts/base_delay retry (server passes 6
attempts, ~31 s backoff) absorbing the boot race; per-attempt CA-fetch
failures log warning + debug traceback instead of error tracebacks.
- healthcheck.py falls back to HTTPS when the plain probe fails,
presenting the node's own cert as the client cert with the cluster CA
pinned; dials localhost because the internal CA issues DNS SANs only.
Default plain-HTTP deployments are unchanged.
- The server writes boot PEMs under a fixed root (TURNSTONE_TLS_PEM_DIR,
default <tmpdir>/turnstone-tls) so the probe can find them; boot
clears stale dirs and refuses a symlinked/foreign-owned root; renewal
rewrites the PEM dir so the probe's client cert never outlives the
served cert.
- /health reports tls: "active"|"fallback" (absent when TLS is
disabled) so a silently downgraded node is observable.
The Anthropic SDK provider was the lone first-class provider gated behind
an optional extra, while OpenAI ships in core and Google rides the
OpenAI-compatible path. Fold anthropic, psycopg (postgres), croniter
(console), and lacme (tls) into the base dependency set so a default
`pip install turnstone` yields a complete single- or multi-node
deployment; only the Discord/Slack channel gateways stay optional.
- pyproject: four extras → base deps; `all` is now discord+slack; drop the
redundant croniter from the `test` extra; regenerate uv.lock.
- ci: the postgres test job installs `.[test]` (psycopg is base now).
- providers: `_ensure_anthropic` becomes a thin SDK accessor for
`create_client`; drop the now-redundant eager import-guard calls from
the streaming/completion hot path (anthropic is always present).
- bootstrap: import anthropic directly.
- tests/docs: drop the anthropic importorskips and stale extra-install hints.
The reranker_alias -> model-definition path (added when reranking became a model
role) made the older global endpoint settings redundant. Resolve reranking
solely through the Reranker role and remove the parallel global config.
- Removed settings tools.rerank_url / rerank_model / rerank_api_key, their
config.py getters (+ $TURNSTONE_RERANK_URL / $TURNSTONE_RERANK_MODEL and the
module caches), and the fallback branch in resolve_rerank_client_from. The
resolver now returns a client only when a Reranker model (capability
supports_rerank, base_url = its /rerank endpoint) is selected, else None.
- Kept as global knobs: reranker_alias (the selector), rerank_web_search,
rerank_bm25, rerank_bm25_threshold, and rerank_instruction -- a task-level
query knob (Qwen3-style), not endpoint identity.
- The Settings tab is registry-driven, so the three fields disappear with their
SettingDefs. Updated the Reranker role help, example config, and docs/tools.md.
BREAKING: a reranker configured via [tools] rerank_url (config.toml / env /
Settings tab) no longer works -- add the reranker in the admin Models tab and
pick it under Models -> Roles -> Reranker. No migration: reranking is days old
and disabled by default, so any orphaned tools.rerank_* config rows are inert.
Tests: the resolver covers no-store / no-alias / non-rerank-alias -> None and the
model-definition happy path; the obsolete global-fallback tests are removed.
Phase 2 of BM25 reranking (follows #627). Makes the rerank_bm25_threshold floor
usable across reranker models and adds tooling to pick it.
- normalize_scores (rerank.py): map a rerank batch into a 0-1 relevance
probability -- sigmoid when any score falls outside [0,1] (logit endpoints
like bge/TEI), identity otherwise (Cohere/Jina/Qwen already 0-1). Applied in
the _bm25_reranker closure AND calibration so the threshold means the same on
every endpoint. Monotonic, so ranking order is unchanged.
- rerank_calibrate.py + `turnstone-admin rerank-calibrate [--apply]`: probe the
endpoint with labelled relevant/irrelevant groups, normalise, and recommend a
recall-biased floor -- or report "no clean separation" (a mis-served/weak
reranker). A warmup loop absorbs a cold endpoint's first-request compile so
calibration doesn't time out. Validated live against Qwen3-Reranker 0.6B and
4B: the calibrated floor differs sharply per model (~0.95 vs ~0.33 for the
same task) -- exactly why per-endpoint calibration exists.
- rerank_config.py: extract resolve_rerank_client_from(config_store, registry);
the alias/url precedence now lives in one place, shared by ChatSession (which
delegates) and the CLI.
- tools.rerank_instruction (config + setting + client): wrap the query as
<Instruct>:/<Query>: for instruction-aware rerankers (Qwen3) on endpoints that
don't apply the model's own chat template. Docs note the critical vLLM serving
detail: Qwen3-Reranker needs --chat-template or its scores are near-random and
reranking hurts retrieval.
Negative-tested: normalize sigmoid/identity branches, closure-normalises-before-
floor, calibration separation/recall-bias/warmup-absorbs-cold-start, the CLI
apply/no-apply/no-separation paths, and instruction query-wrapping through the
real httpx boundary.
Reuse the shipped Cohere/Jina rerank client as an optional post-process on
the BM25 surfaces (tool search, skill search, memory composition) via one
seam: BM25Index gains an injected reranker + a two-stage search (BM25 recall
top-50 -> rerank -> top-k). No new storage.
Gated on a configured endpoint plus tools.rerank_bm25 (default on, matching
rerank_web_search). tools.rerank_bm25_threshold (default 0.0 = off) is a
relevance FLOOR for proactive memory surfacing: BM25 always returns something,
so without a floor every-turn memory injection spends tokens on the top-k of
whatever lexically matched; the reranker score is what makes a meaningful
"inject nothing" gate possible.
Two reranker modes (BM25Index rerank_filters):
- REORDER (reactive tool/skill search): the reranker must never drop results
-> fall back to BM25 order on empty, backfill omitted pool items, so a
misbehaving endpoint can't silently lose tools.
- FILTER (memory, rerank_filters = threshold > 0): a clean empty/short result
is honoured (inject nothing) -- a deliberate divergence from
web_search._rerank_results.
Parse/endpoint failure is a discrete branch from the floor: an empty result
for non-empty input means an unparseable response (a conforming reranker
scores every doc), so the closure raises RerankError and BM25Index falls back
to BM25 order in BOTH modes -- the floor only acts on valid scores.
Also: cap the rerank client timeout at 15s (the per-turn memory path can't
afford tools.timeout's 120s default); move the Reranker alias to rerank.py
(shared, no import cycle); document the endpoint egress in the rerank_bm25
help, the admin Reranker-role description, and docs/tools.md; add
scripts/bench_bm25_rerank.py (manual, needs a live endpoint) to measure
precision@k/MRR lift and recommend a threshold default.
Negative-tested: reorder fallback-on-empty and omitted-item backfill,
filter-mode honor-empty, singleton-still-floored, the parse-fail RerankError
raise, the >= floor boundary, and pool-position-to-doc-index mapping -- each
guard reverted to confirm its test fails, then restored.
Reranking is delegated to an external Cohere/Jina-compatible /rerank endpoint
(self-hosted vLLM/TEI/llama.cpp, or hosted Cohere/Jina/Voyage); Turnstone runs
no reranker model itself. Disabled until an endpoint is configured.
- core/rerank.py: CohereJinaRerankClient (tolerant of results-wrapped and
bare-list responses) + resolver.
- web_search: rerank the SearxNG result pool by query relevance before top-k,
with a native-order fallback on error; answers/infoboxes untouched.
- Reranker as a model definition: add a model with the supports_rerank
capability and pick it under Models -> Roles -> Reranker
(tools.reranker_alias); takes precedence over the tools.rerank_url settings.
Settings: tools.rerank_url/model/api_key, tools.rerank_web_search,
tools.reranker_alias. Docs: docs/tools.md, turnstone.example.toml.
(web_fetch reranking was evaluated and dropped: for single-document chunk
selection it did not reliably beat head-truncation. Reranking is reserved for
multi-item ranking.)
`man` and `math` duplicated capabilities already reachable through
`bash`; `plan_agent` is better expressed as a `task_agent` running a
planning skill, and carried a large amount of special-case machinery
(plan-review gate, refinement loop, per-kind model routing). Removing
all three shrinks the tool surface and cuts per-call token cost.
Also removed, as dead-once-the-tools-are-gone:
- the `math` sandbox executor (`turnstone.core.sandbox`) and its
`[sandbox]` extra; the eval analyst now runs bash-only
- the read-only `AGENT_TOOLS` sub-agent tool set and the `agent`
tool-metadata key (`task_agent`/`TASK_AGENT_TOOLS` retained)
- the plan-review protocol end to end: the `on_plan_review` UI hook,
`resolve_plan`, `POST /v1/api/plan` + `POST /v1/api/route/plan`,
the `plan_review`/`plan_resolved` SSE events, and their Python SDK /
TypeScript SDK / OpenAPI / frontend / Discord+Slack bindings
- the `model.plan_alias` / `model.plan_effort` settings and the
registry `plan_model` / `plan_effort` routing fields
TOOLS 31->28, TASK_AGENT_TOOLS 13->11; COORDINATOR_TOOLS unchanged.
BREAKING CHANGE: removes the `man`, `math`, `plan_agent` tools, the
plan-review SSE/HTTP/SDK surface, and the plan_* model-routing settings
from the experimental 1.6 line.
Rename the web_search tool's `topic` parameter to `category` and expand the
enum to general/news/it/science, mapped to SearxNG `categories=`. The model can
now target the right corpus per query (e.g. `it` for code, `science` for
papers) — useful when generic engines rate-limit. The Tavily-era `finance`
topic (no SearxNG equivalent) is dropped. Threaded consistently through
_prepare_web_search / _exec_web_search / both search clients.
BREAKING: the web_search `topic` argument is now `category`.
Drop the Tavily and DuckDuckGo (ddgs) web_search backends for a single
self-hosted SearxNG service bundled into the docker-compose stacks.
Core:
- New SearXNGClient + _format_searxng; rewrite resolve_web_search_client to
(backend, searxng_url, searxng_engines, ...). MCP backend + oauth_user guard
unchanged. _resolve_search_client follows storage -> toml -> env -> default
precedence (explicit "" disables, via ConfigStore.stored_keys()).
- Drop the Tavily-era topic=finance (no SearxNG category); topic is now
general/news.
Settings/config:
- Remove tools.tavily_api_key, get_tavily_key, $TAVILY_API_KEY, [api].tavily_key.
- Add tools.searxng_url (default http://searxng:8080) + tools.searxng_engines,
with get_searxng_url/get_searxng_engines.
Compose + bundled config:
- Internal-only searxng service (no published API port, :ro config, /healthz
healthcheck, persistent searxng-cache volume) in both stacks; bundle
turnstone/deploy/searxng/settings.yml (JSON output on, limiter off).
- Caddy serves the SearxNG web UI on :8444 (dev: localhost-only; prod: opt-in).
- bootstrap extractor + wheel packaging updated.
Deps: drop the ddg extra + ddgs mypy override (regenerates uv.lock, removing the
lxml/h2/brotli transitives).
Docs: tools/docker/architecture/openshell + diagrams + config example + CHANGELOG;
docs/docker.md carries the AGPL-3.0 §13 operator note.
BREAKING: tools.web_search_backend no longer accepts "tavily"/"ddg";
tools.tavily_api_key and the ddg extra are removed. Run the bundled SearxNG (ships
in the compose stacks) or set TURNSTONE_SEARXNG_URL to an external instance.
Closes#545
`docker compose up` from a clone builds one image and brings up the whole stack
— PostgreSQL, console, Caddy, channel, and 10 server nodes — sharing one
Postgres so the console discovers every node. The dashboard is reachable only
through Caddy (HTTP/2 avoids the browser's 6-connection cap on the dashboard's
SSE streams); the console's plain-HTTP port is no longer published. Postgres
binds 127.0.0.1 so a bare-metal turnstone-server can join the cluster — the
bare-metal overlay is folded in and removed. Insecure dev defaults keep it
zero-config; the bundled production stack mirrors the shape but pulls ghcr
images and requires real secrets.
Move the Caddyfile under turnstone/deploy so it ships in the wheel; update docs,
QUICKSTART, and .env.example to match.
The floor blocks only explicit heuristic deny/critical verdicts — it is
not a general "never lower the heuristic" rule. The heuristic default for
an unmatched tool is `review`, and letting a confident LLM `approve`
upgrade a `review` is the feature's purpose. Matches the implementation
and addresses PR review feedback.
Opt-in judge.smart_approvals (default off): when the intent-validation
LLM judge returns a high-confidence "approve" verdict, the tool batch is
approved automatically with no operator prompt. review/deny recommendations,
low confidence, judge errors (llm_fallback), and a deterministic heuristic
deny/critical finding all still require a human. Requires judge.enabled.
- Batch-atomic: a parallel tool batch auto-approves only if every call
qualifies; one non-qualifying call holds the whole batch for a human.
- Gate: tier==llm + recommendation==approve + confidence >=
judge.confidence_threshold (default raised 0.7 -> 0.95), with a floor
that never clears an explicit heuristic deny/critical verdict.
- approve_tools waits for the async LLM verdicts, finalises the audit
trail (AutoApproveReason.smart_approval), and re-emits verdicts after
the card so the live chip updates; the auto-approved row renders the
LLM verdict rather than the cautious heuristic carry-over.
- judge: always deliver exactly one verdict per call (fallback on error);
reject non-finite confidence so NaN can't clear the bar.
- Drop verdicts from a superseded judge generation so a reused call_id
from a prior turn's still-running daemon can't satisfy the gate's wait.
Config plumbed through the server/console/CLI builders and the live
_judge_cfg; admin Judge tab renders the toggle. Docs + example config
updated. ~35 tests covering the gate matrix, batch-atomicity, the
heuristic floor, audit stamping, the streaming re-emit, NaN/duplicate-id
defenses, and the cross-turn generation guard.
Enabling mTLS broke the cluster in three layered ways:
- Service certs were keyed on socket.gethostname() (the container ID) and
never carried the advertised service name as a SAN, so every collector and
routing-proxy handshake failed the hostname check. build_cert_hostnames()
now puts the advertised host first: it becomes the cert's primary domain
(hence a SAN) and a stable store key that survives container recreation.
- lacme's RenewalManager renews everything in the store; with the store shared
cluster-wide, every node renewed every other node's (and every dead
container's) cert — an N×M renewal storm. _SingleDomainStore scopes each
node's sweep to its own cert, and the console adds a periodic GC for the
certs of long-departed nodes.
- uvicorn loads its cert once at boot and never reloads, so renewed certs
never reached the listener and the served cert expired mid-process.
swap_context_cert() hot-swaps renewed material into the live SSL context
(server listener and console client context) via load_cert_chain.
Observability and browser access:
- The collector logged connection/TLS failures at DEBUG, so a persistent
mTLS-verify failure was invisible. It now logs the first failure per node
(reachable->unreachable) at WARNING and stays at DEBUG on retries.
- The console serves plain HTTP (it is the ACME bootstrap endpoint) and no
longer rewrites its advertised URL to https://. Browser->console TLS is
terminated by a reverse proxy: the cluster profile gains a caddy service
(browser h2/HTTPS -> caddy -> console h1.1/HTTP) plus browser-TLS docs.
Tests: tests/test_tls_san_renewal.py, tests/test_collector_reachability.py.
Surface the output-guard LLM judge on the inline finding chip and merge it
with the regex heuristic instead of one stage winning outright.
Merge rule (issue #560, "show, annotated"):
- risk_level = max(heuristic, llm); flags = union. The judge can escalate
but never lower a heuristic positive — it evaluates adversarial tool
output, so defeating it must not erase a deterministic regex finding.
Credentials stay heuristic-only and are always redacted.
- The judge's own verdict rides along as a dissent-aware annotation
(judge_risk / confidence / reasoning / judge_model) on the chip in both
the interactive and coordinator UIs, live and on reconnect. One shared
merge_guard_display_payload drives both paths so they cannot drift.
- The model is shown the merged risk + flags but never the judge's "benign"
verdict — a fooled judge must not talk the model out of caution.
Fixes a reconnect bug: a judge that ran but failed wrote a risk="none" row
that won the replay dedup and hid the heuristic finding (it showed live but
vanished on refresh). Failed judges now persist under tier="llm_error",
excluded from the display merge; the max-merge also floors the displayed
risk at the heuristic level so the chip never vanishes.
Also adds a regression test confirming the LLM judge runs on every tool
output, not just heuristic-flagged ones.
Tests: merge unit tests, storage-backed replay regression, live/replay
wire-shape parity, SDK-event drift guard. ruff + mypy clean.
Collapse the three hand-synced "raw storage -> render shape" projections
into one server-side projection. The projection previously lived in a
test-only `_build_history` (SSE-era reference impl), a client-side JS
normaliser (`history_normalize.js`, the transitional bridge), and coord's
inline `init()` handling -- drifting silently with no parity test.
Add `project_history_messages` to `history_decoration.py` and run it as the
final step of the `make_history_handler` pipeline (load_messages -> decorate
-> extract_reasoning -> project), so `GET /history` emits the canonical
render shape directly: flat tool_calls (with verdict / output_assessment),
top-level source / reminders / attachments, collapsed multipart content,
derived denied / is_error / pending, reasoning, and advisories. Interactive
`replayHistory` now consumes the payload verbatim.
Close two gaps the JS bridge deferred:
- list-content <tool_output> advisory extraction (decorate handles only
string content; the projection extracts list-carrier advisories, then
joins remaining text parts to the string the renderers require);
- orphan->pending marks ONLY the last orphan tool-call turn, so a
mid-conversation cancelled tool still renders instead of vanishing.
Delete `history_normalize.js` (+ its <script> tag and node test) and the
test-only `_build_history` (+ orphaned imports); retarget its direct tests
onto the projection helpers. Update the WorkstreamHistoryResponse
description and the Web UI Resilience architecture note to the projected
shape.
Coord's `init()` still reads the raw side-channels; migrating it to the
projected shape is the next commit, browser-verified separately.
Refs #549.
notify was interactive-only — a coord with a natural "fan-out complete"
or "batch failed" beat could only post by spawning a child for the
single message, which is a lot of ceremony. Routing is session-kind-
agnostic in _prepare_notify / _exec_notify; this is a metadata flip
that adds the coord flag (plus the explicit interactive flag the loader
needs once coordinator is set) and updates the dual-kind whitelists,
coord tool-set assertions, and skill-author docs accordingly. Adds
two coord-session tests pinning the prepare dispatch contract
(needs_approval=False matches notify.json auto_approve) and the exec
→ channel-gateway path.
Four /review findings collapsed to one code chokepoint + two
documentation fixes:
1. find's `kind` arg now validated against ``SkillKind`` (matching
create / update's existing pattern at session.py:8298 / :8512).
Closes two failure modes that shared the same root:
- typos (`kind="interactivee"`) silently produced
`kinds=["interactivee", "any"]` filtering to literal-`any` rows
only and masquerading as a narrowed catalog — now returns an
explicit "kind must be one of: ..." error;
- the documented enum value `kind="any"` degenerated to
`kinds=["any", "any"]` which narrowed to literal-`any` rows
instead of returning "every kind" — now collapses to ``None``
so the documented semantic holds.
2. docs/coordinator-skills.md "two-surface model" section rewritten
to reflect the post-flatten reality: kind is metadata, not an
enforcement boundary. The line-67 tools-table row updated from
the long-dead `list_skills` to `skills (action=find)` with the
opt-in kind-filter framing.
3. Three stale "interactive-only" comments in session.py
(:5514, :7857, :8210) that directly contradicted the
`_prepare_skills_load` docstring ("Both kinds can load") — drop
the qualifier so future grep-and-encode hazards don't reintroduce
the rejection.
Tests:
- test_find_kind_invalid_errors — typo case (replaces the silent
degenerate to literal-any-only)
- test_find_kind_any_means_no_filter — documented enum value matches
documented semantic (collapses to None at prepare)
- test_find_kind_narrow_passes_through — valid narrowing values
reach exec as expected
Deferred to release notes (no code change, intentional policy shift):
- skills(action='get') / load can now read full content + scan_report +
allowed_tools on cross-kind rows from any session. Operators with
pre-existing kind=coordinator skills authored under the prior
implicit visibility contract should audit those bodies for
sensitive content (allowed_tools allowlists, embedded credentials,
internal hostnames in examples) before upgrade.
Three Copilot threads from PR #526:
1. ``_exec_spawn_workstream`` success path emitted
``{"child_ws_id": null}`` when the upstream response unexpectedly
omitted ``ws_id`` (200-shape with no error field, no id field).
Adds the missing guard — mirrors ``_exec_spawn_batch`` which
already surfaces ``"spawn returned no ws_id"`` as a denied row.
The LLM now sees a tool error and can retry instead of chasing
a null id through follow-up tools.
2. ``docs/coordinator-skills.md`` UI render note said "keep the
ws_id as the click-through key" in a paragraph that had just
introduced ``child_ws_id`` — readable as "the ws_id value" but
confusable as a field-name claim. Clarifies that the value
class is the same regardless of which key carried it.
3. ``docs/bulk-endpoints.md`` ``spawn_batch`` example shows
``child_ws_id`` (coord-tool output shape). The doc title and
the "model tool" column label already disambiguate it from HTTP
API responses, but a reader landing at the example section
directly could miss the framing. Adds one explicit sentence.
Coordinator LLMs on large fan-outs recency-bias on seeing `ws_id`
in a `spawn_workstream` / `spawn_batch` return -- calling
`spawn_workstream(ws_id=...)` again instead of progressing to
`wait_for_workstream(ws_ids=[...])`. On 10+ child fan-outs this
cascades into self-inflicted re-spawn loops.
Rename to `child_ws_id` (already an existing project term -- see
`tasks` tool, `child_event_bus.py`) defuses the recency bias.
Scope is the LLM-facing JSON only -- the server HTTP API at the
spawn endpoint still returns `ws_id`, and the internal reads of
that HTTP response are unchanged.
Also updates the two tool descriptions, the operator-facing skill
doc, and the bulk-endpoints example so docs don't undo the rename.
Patrick Buckley