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## What Problem This Solves Skill Workshop experience review ran as an isolated agent with a re-rendered 60k-character transcript, its own bootstrap, and a trimmed tool surface. Every review was a cold request: no prompt-cache reuse, a large re-serialized trajectory, and a reasoning/tool profile that differed from the foreground turn. Autonomous updates could target any workspace skill, size limits allowed 40 KB skills to grow unchecked (one deployed workspace hit a 21 KB `SKILL.md`), the collection reviewer had to re-list every skill in its plan and read them under a fixed 24k-character budget (a 16-skill workspace failed every pass with "Read every current skill before reconciling"), collection review only recorded successes so a failing pass retried on every Gateway restart, and `openclaw skills curator status` showed nothing about what the last reviews did. ## Why This Change Was Made - **Warm fork.** Experience review now continues the finished turn from the same in-memory session prefix (same session identity, bootstrap, skills prompt, tool schemas, `promptCacheKey`), appends one short review message, and runs with `sessionPersistence: "detached"` so nothing it writes reaches the foreground transcript or session record. Only `skill_workshop` executes; every other tool keeps its schema for cache parity and fails with a next-step message. The gate wraps the core tool list before Code Mode / Tool Search compaction, so catalog-hidden tools stay gated while `tool_call`/`exec` remain callable. `src/agents/embedded-agent-runner/run/attempt.skills-policy.test.ts` asserts identical system-prompt and tool digests between a foreground turn and its review, and that `tool_call` reaches `skill_workshop` but not `read` during review. Code Mode swarm globals (`phase`, `log`, `agents.run`) are the `sessions_spawn` capability and gate on the same allowlist, so a review cannot emit foreground lifecycle events or launch collectors. The review shares the foreground session, so it no longer retires that session's MCP runtime on run end; it reuses the warm runtime like any turn. Accepted tradeoff: the review inherits foreground tool construction (it creates the session MCP runtime only when the session has none, and spawns per-attempt LSP servers only when configured), because splitting tool construction from the foreground turn would break the cache-parity invariant this PR exists for. - **One apply owner, rechecked at the write boundary.** `src/skills/workshop/autonomous-apply.ts` decides apply-vs-pending for both the post-review loop and foreground repair: creates and updates to Workshop-authored skills apply; updates to user-authored skills stay pending with a recorded reason. `applySkillProposalTransition` rechecks path-based ownership under the commit lock for non-operator actors (agent, or no actor), so a claim released after the pre-check cannot let an agent write a user-authored skill; gateway and CLI operators still approve any pending proposal. The user-authored pending write runs under the same commit lock and rereads the row, so an operator apply that lands first is kept. The old `auto-apply.ts` path and name-based `listWorkshopAuthoredSkillNames` are deleted. - **Sparse collection plan and model-relative reads.** The collection reviewer returns only `write` and `drop` entries; unlisted skills stay untouched, so a 16-skill workspace no longer has to restate 16 keeps. The skill read budget is derived from the model's context window (35%) instead of a fixed 24k characters, with the 10,000-character skill cap still enforced per skill. No windowed read parameters: a skill is read whole or not at all. - **Weekly cadence.** Collection review runs once every 7 days instead of daily (`REVIEW_INTERVAL_MS`), matching how slowly a skill library actually changes; the attempt is recorded before the model starts, so a failed pass does not retry on every restart. - **Lean cap.** `AUTONOMOUS_SKILL_MAX_CHARS = 10,000` in `src/skills/workshop/collection-contracts.ts` is enforced by the tool and by collection reconcile; an oversized skill may only shrink. Tool description, experience prompt, and collection prompt were rewritten around procedures-not-records, one trigger per branch, and "NOTHING_TO_LEARN is the correct answer for most turns". - **Detached runs end quietly.** A detached run writes no transcript or session record and runs under the foreground session key, so `attempt-finalize` now skips agent_end side effects for it: plugins do not observe the review as a foreground turn, and a deep review cannot schedule a successor review of itself. - **Recorded outcomes.** Experience review records `applied | proposed | nothing | failed` with usage; one attempt per turn, drop on error. `openclaw skills curator status` prints the last collection and experience review outcome. ## User Impact - Default `auto` mode: experience review reuses the foreground prompt cache and skips message/other tool execution, so review cost is one bounded continuation instead of a cold re-render. - Autonomous edits touch only Workshop-authored skills; handwritten skills surface as pending proposals for operator approval. - Autonomous `SKILL.md` results stay ≤ 10,000 characters. - Collection review runs weekly and succeeds on larger skill libraries. A workspace with no recorded attempt reviews at the first daily check after Gateway start; an upgraded install keeps its recorded last attempt and reviews once it is older than 7 days. The 10,000-character cap applies to the next autonomous write; existing oversized skills are only ever shrunk. - `openclaw skills curator status` shows the last collection and experience review outcome, time, and tokens. - Docs: https://docs.openclaw.ai/tools/self-learning, https://docs.openclaw.ai/tools/skill-workshop Related: #123866, #128871 both patch skills above the reviewer read budget; this PR caps autonomous skill size and restricts oversized skills to shrink-only rewrites. ## Evidence - Live gateway (Linux, Telegram, `xai` provider) at `133ffe3`: manual experience review on a real foreground turn → `nothing` (usage: 0 uncached input, 13,902 cached, 36 output — the forked review hit the foreground prompt cache); manual collection review over the workspace → `succeeded`; the three oversized skills were rewritten under the cap (21,002 → 9,449; 11,882 → 7,735; 10,300 → 7,413 bytes, originals in `skill-workshop/collection-backups/`), the rest untouched, and the pre-PR "Read every current skill before reconciling" failure is gone. The next foreground turn's automatic experience review recorded `nothing` and `openclaw skills curator status` shows both outcomes. The apply recheck, MCP-runtime change (`26e821f`), and detached agent_end skip (`7e4a506`) landed after that run and are covered by the regression tests below. - `pnpm test src/skills/workshop src/agents/tools/skill-workshop-tool src/gateway/server-methods/skills` plus `src/agents/embedded-agent-runner/run/attempt.skills-policy.test.ts`, `src/agents/embedded-agent-runner/run/attempt.tool-search-catalog-abort.test.ts`, `src/cli/skills-cli.curator.test.ts`, `src/agents/harness/tool-surface-bridge.test.ts` — green. New regression tests (`service.test.ts` agent-vs-operator apply on a user-authored skill and operator apply kept over a stale pending snapshot; `experience-review.apply.test.ts` no `cleanupBundleMcpOnRunEnd`; `attempt-phase-lifecycle.test.ts` no agent_end for a detached run; `code-mode-swarm.test.ts` swarm globals refused under the review allowlist) fail on the pre-fix code. - Dependent sweep: 46 test files importing the touched modules — green. - `oxfmt`, `scripts/run-oxlint.mjs` on changed files, `git diff --check` — clean. - `pnpm tsgo && pnpm check:test-types` on Blacksmith Testbox — clean. - Local ClawSweeper review (`gpt-5.6-terra`, high): `133ffe3` raised two findings (ownership recheck removed from the apply boundary; review retiring the shared session's MCP runtime), fixed in `26e821f`; `26e821f` raised one (detached review re-entering agent-end scheduling), fixed in `7e4a506`; `7e4a506` raised three: pending write racing an operator apply and Code Mode swarm globals bypassing the execution gate, both fixed in `e4b4322`; "prove detached review does not start configured MCP or LSP runtimes" is skipped as the cache-parity tradeoff stated above (LSP tool schemas come from the LSP runtime; the MCP runtime is session-owned and already warm). Maintainer decision on `e4b4322`: accepted — a detached review reuses the session MCP runtime and re-spawns configured per-attempt LSP servers exactly like a foreground turn; it still cannot execute them. - Unrelated CI on `26e821f`/`7e4a506`: `check-lint-core-2` (`max-lines` in `src/gateway/server-methods/models-list-result.ts`, unused param in `models.test.ts`, both from #129332) and `checks-node-compact-small-8` (`doctor-auth.profile-health.test.ts`, Claude CLI auth from #129052) fail identically on `main` run 32857954734; `checks-node-compact-small-31` pins plugin SDK export counts (`4340` vs `4342`) that #129052 moved — this PR touches no `src/plugin-sdk` file. On `e4b4322` the failing set is the same twelve `checks-node-compact` shards that fail on `main` run 32857954734 (`large-5/12/13/14/15/18/22`, `small-8/14/20/21/26`) plus `small-31`; `check-lint-core-2` passes here. None are fixed here; #129357 carries the `main` fix. - LOC (raw numstat): production +712 / −664 (net +48; the four review-fix commits after the live run add +76 / −26); tests + docs +1269 / −1238 (net +31). |
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| src | ||
| doctor-contract-api.test.ts | ||
| doctor-contract-api.ts | ||
| harness.test.ts | ||
| harness.ts | ||
| index.test.ts | ||
| index.ts | ||
| openclaw.plugin.json | ||
| package.json | ||
| README.md | ||
| tsconfig.json | ||
GitHub Copilot agent runtime (OpenClaw plugin)
External OpenClaw plugin that registers a copilot agent harness backed by @github/copilot-sdk and the GitHub Copilot CLI.
Install
openclaw plugins install @openclaw/copilot
Restart the Gateway after installing or updating the plugin.
The harness claims the canonical subscription github-copilot provider plus
custom BYOK provider entries that the Copilot SDK can represent. Manifest-owned
native provider ids stay with their owning runtimes. The harness is opt-in only:
selection requires explicit agentRuntime.id: "copilot" on a model or provider
entry; auto never picks it. OpenClaw remains the default embedded runtime.
See GitHub Copilot agent runtime for configuration, the doctor contract, transcript mirroring, compaction, side questions, replay, and the supported-surface contract.
Package
- Plugin id:
copilot - Package:
@openclaw/copilot - Minimum OpenClaw host:
2026.5.28