Tags: mco-org/mco
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Bump version to 0.8.0, update README with v0.8 features (#76) New in v0.8.0: - Chain mode (--chain) for sequential multi-agent analysis - Per-provider perspectives (--perspectives-json) - Consensus badges ([N/M agree] / [confirmed by N/M]) - Session retry with error classification and exponential backoff - Session result retrieval (session result <name> <id>) - Critical nowait data loss fix Co-authored-by: admin <admin@SH-TuShaokun.local>
feat: cross-session memory bridge (Phase 1-4) (#60) * feat: add single-slot run hooks for MCO lifecycle events * feat: add --memory/--space CLI flags and hook wiring in run_review * feat: add bridge skeleton with finding_hash and PersistedFinding type * feat: add evermemos MCP client wrapper with optional dependency * feat: implement bridge core with pre_run/post_run and finding merge semantics * test: add integration tests for hook wiring and real bridge path * test: verify memory misconfiguration error messages are actionable * fix: use uvx evermemos-mcp (PyPI) instead of npx npm placeholder * fix: reject colon in --space (slug only), add uvx-missing test * feat: add passive confirmation logic for finding lifecycle * feat: add forget cleaner for rejected findings * feat: add task type auto-classification from prompt and findings * feat: add tech stack detection from project file markers * feat: add request_status polling for write confirmation * feat: add agent reliability scoring with cross-validation tracking * feat: add cold-start weight mixing for agent reliability * feat: add finding confidence calculation with three-factor weighting * feat: wire passive confirm and forget into post_run hook * feat: integrate confidence, classification, and stack detection into bridge hooks Wire Phase 2-4 modules into the bridge pre_run and post_run hooks: - Stack detection and agent weight retrieval in pre_run - Confidence calculation before finding persistence in post_run - Task classification and agent score persistence in post_run - Status polling for critical/high severity findings in post_run - Confidence grade labels in injected prompt for known-open findings * feat: add tech stack aggregate scoring for cold-start priors Add update_stack_aggregate() to scoring.py that reads existing scores from a stack-level evermemos space, merges with new per-repo scores, and writes back. Wire into core.py _post_run_impl() after repo-specific agent scores. This enables cold-start priors for new repos sharing the same tech stack. * feat: add mco findings subcommand for listing and confirming findings * feat: add mco memory subcommand for agent-stats, priors, and status * test: add end-to-end integration test for full Phase 1-4 pipeline * fix: resolve 5 correctness issues from code review 1. Canonical latest view: deduplicate findings/scores by key across all read paths (core, findings_cli, memory_cli) 2. Accurate run_count: count [MCO-RUN-MARKER] entries in context space instead of finding entry count 3. Category-aware _load_agent_rates: filter by task_category or average across categories when no filter specified 4. memory_id injection: extract id from fetch_history outer item, not from serialized content JSON 5. Per-finding changed_files: each finding checks files changed since its own last_seen_commit, not a union across all commits Add 17 targeted tests covering all 5 fixes. * fix: wire category parameter through show_priors to _load_agent_rates show_priors() accepted a category argument but never forwarded it to _load_agent_rates(), making the category filter decorative. Now all three _load_agent_rates() calls (repo, stack, global) receive the category so users get category-filtered priors as intended. * docs: add cross-session memory section to README, bump to v0.4.0 Add opt-in --memory feature documentation with usage examples, subcommands, and architecture overview. Keep it concise at the bottom of the README. Bump version to 0.4.0 for the memory bridge feature release. * fix: replace pytest.approx with unittest assertions for CI compatibility CI runs python3 -m unittest discover without pytest installed. Convert test_cold_start.py and test_confidence.py to use unittest.TestCase with assertAlmostEqual/assertEqual. --------- Co-authored-by: admin <admin@SH-TuShaokun.local>
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