Replace divergent per-skill curation with one daily isolated collection review that can consolidate, rewrite, create, and drop writable skills atomically.
Autonomous auto mode remains automatic. Adds bounded review, transactional recovery, durable cadence, shared locking, and reuse-first /learn behavior.
Co-authored-by: Ayaan Zaidi <hi@obviy.us>
* feat(skills): repair used skills in turn
* fix(skills): bind repair to used skill receipt
* fix(skills): preserve explicit repair review
Co-authored-by: Ayaan Zaidi <hi@obviy.us>
Teach the semantic reviewer to improve skills the agent actually used, keep review input provider-bound, and preserve bounded deterministic retries.
Co-authored-by: Ayaan Zaidi <hi@obviy.us>
Self-learning reviewer edits existing skills via targeted patches: it quotes the exact live text (or appends a section) and the service composes the full body inside the receipt-pinned read that hash-binds the proposal — untouched content survives by construction, and patches auto-apply through the scanner-gated pipeline. Full-body rewrites and oversized-skill edits stay pending for the operator. The review prompt shifts to active capture within the existing evidence gates, and shallow same-sender turns accumulate per session (provider-identity scoped, zero-iteration and duplicate-run contracts honored, aborted provenance carried, bounded state) so quick corrections get reviewed with their own transcripts. Replaces closed#119856.
Deletes the deterministic regex capture path that templated raw chat text into skill proposals (junk like a proposal whose whole procedure was one slugified user message). All autonomous learning now flows through the isolated experience reviewer: it sees a bounded workspace skill list, prefers revising pending proposals or updating the governing skill over creating new ones, and treats durable user corrections as first-class evidence. Update proposals are reviewer-only (explicit opt-in) and never auto-apply, since the reviewer drafts them without the live skill body. Removes the producerless pending-suggestion session machinery. Regression test proves the junk path is gone; real-Telegram E2E verdict in the PR body.
Skill Workshop lifecycle actions now run without an additional Gateway approval by default, while explicit `approvalPolicy: "pending"` keeps the operator approval gate.
Prepared head SHA: 06e907797e
Co-authored-by: Shakker <165377636+shakkernerd@users.noreply.github.com>
Reviewed-by: @shakkernerd
Ayaan Zaidi