claudomator — task automation server https://git.terst.org/claudomator.git/atom?h=main 2026-05-02T08:00:17+00:00 2026-05-02T08:00:17+00:00 Claude noreply@anthropic.com 2026-05-02T08:00:17+00:00 urn:sha1:50f8fe8c1ff8b82e0bd399e5776e58bda3e57d1c Phase 4 of "local OSS models as agents" plan. Closes the epic. When an execution finishes and the agent did NOT write a "## Summary" heading in its stdout (so the existing extractSummary path returns empty), and the Pool has a local LLM configured, we now synthesize a 2-4 sentence summary from the assistant text content of the log tail. Behavior: - Primary path unchanged: if the agent wrote "## Summary", that wins byte-for-byte (TestPool_HandleRunResult_ExtractSummaryWins guards). - Fallback path: empty extractSummary + Pool.LLM != nil → synthesize. - All-empty path: when no LLM is configured, summary stays empty — identical to pre-Phase-4 behavior. Implementation: - Pool gains an LLM *llm.Client field, wired in serve.go and run.go alongside Classifier.LLM (same localClient used everywhere). - New synthesizeSummary in internal/executor/summary.go: * 6s timeout so a slow local model can't stall finalization * 16 KB tail cap on the stdout log * readAssistantTextTail seeks to the last 16 KB and skips the first (likely partial) line, parses each line as a stream-json event, joins assistant `text` blocks (skips system/result/etc). * Returns "" on any error so the caller's behavior never regresses. - handleRunResult: 3-tier summary resolution — exec.Summary set by runner → extractSummary → synthesizeSummary → empty. - minimalMockStore now records UpdateTaskSummary calls (additive; existing tests unaffected) so integration tests can assert. Tests (9 new): - synthesizeSummary nil client / empty path / missing file all return "" without HTTP calls. - empty assistant content short-circuits without LLM call. - success path returns trimmed body, with both assistant texts in the user prompt. - LLM 500 returns "" (caller handles same as no-summary). - readAssistantTextTail seeks past early content in a large file. - Pool integration: ## Summary present → LLM not called, agent text used. ## Summary absent + LLM set → LLM called, synthesized summary recorded against the right task ID. Plan: docs/plans/local-oss-runner.md. Epic complete. Post-epic deep cleanup queue captured in the same plan file for follow-up. https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J