feat: Review Army — parallel specialist reviewers for /review (v0.14.3.0) (#692)
* feat: extend gstack-diff-scope with SCOPE_MIGRATIONS, SCOPE_API, SCOPE_AUTH
Three new scope signals for Review Army specialist activation:
- SCOPE_MIGRATIONS: db/migrate/, prisma/migrations/, alembic/, *.sql
- SCOPE_API: *controller*, *route*, *endpoint*, *.graphql, openapi.*
- SCOPE_AUTH: *auth*, *session*, *jwt*, *oauth*, *permission*, *role*
* feat: add 7 specialist checklist files for Review Army
- testing.md (always-on): coverage gaps, flaky patterns, security enforcement
- maintainability.md (always-on): dead code, DRY, stale comments
- security.md (conditional): OWASP deep analysis, auth bypass, injection
- performance.md (conditional): N+1 queries, bundle impact, complexity
- data-migration.md (conditional): reversibility, lock duration, backfill
- api-contract.md (conditional): breaking changes, versioning, error format
- red-team.md (conditional): adversarial analysis, cross-cutting concerns
All use standard header with JSON output schema and NO FINDINGS fallback.
* feat: Review Army resolver — parallel specialist dispatch + merge
New resolver in review-army.ts generates template prose for:
- Stack detection and specialist selection
- Parallel Agent tool dispatch with learning-informed prompts
- JSON finding collection, fingerprint dedup, consensus highlighting
- PR quality score computation
- Red Team conditional dispatch
Registered as REVIEW_ARMY in resolvers/index.ts.
* refactor: restructure /review template for Review Army
- Replace Steps 4-4.75 with CRITICAL pass + {{REVIEW_ARMY}}
- Remove {{DESIGN_REVIEW_LITE}} and {{TEST_COVERAGE_AUDIT_REVIEW}}
(subsumed into Design and Testing specialists respectively)
- Extract specialist-covered categories from checklist.md
- Keep CRITICAL + uncovered INFORMATIONAL in main agent pass
* test: Review Army — 14 diff-scope tests + 7 E2E tests
- test/diff-scope.test.ts: 14 tests for all 9 scope signals
- test/skill-e2e-review-army.test.ts: 7 E2E tests
Gate: migration safety, N+1 detection, delivery audit,
quality score, JSON findings
Periodic: red team, consensus
- Updated gen-skill-docs tests for new review structure
- Added touchfile entries and tier classifications
* docs: update SELF_LEARNING_V0.md with Release 2 status + Release 2.5
Mark Release 2 (Review Army) as in-progress. Add Release 2.5 for
deferred expansions (E1 adaptive gating, E3 test stubs, E5 cross-review
dedup, E7 specialist tracking).
* chore: bump version and changelog (v0.14.3.0)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
feat: GStack Learns — per-project self-learning infrastructure (v0.13.4.0) (#622)
* feat: learnings + confidence resolvers — cross-skill memory infrastructure
Three new resolvers for the self-learning system:
- LEARNINGS_SEARCH: tells skills to load prior learnings before analysis
- LEARNINGS_LOG: tells skills to capture discoveries after completing work
- CONFIDENCE_CALIBRATION: adds 1-10 confidence scoring to all review findings
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: learnings bin scripts — append-only JSONL read/write
gstack-learnings-log: validates JSON, auto-injects timestamp, appends to
~/.gstack/projects/$SLUG/learnings.jsonl. Append-only (no mutation).
gstack-learnings-search: reads/filters/dedupes learnings with confidence
decay (observed/inferred lose 1pt/30d), cross-project discovery, and
"latest winner" resolution per key+type.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: learnings count in preamble output
Every skill now prints "LEARNINGS: N entries loaded" during preamble,
making the compounding loop visible to the user.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: integrate learnings + confidence into 9 skill templates
Add {{LEARNINGS_SEARCH}}, {{LEARNINGS_LOG}}, and {{CONFIDENCE_CALIBRATION}}
placeholders to review, ship, plan-eng-review, plan-ceo-review, office-hours,
investigate, retro, and cso templates. Regenerated all SKILL.md files.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat: /learn skill — manage project learnings
New skill for reviewing, searching, pruning, and exporting what gstack
has learned across sessions. Commands: /learn, /learn search, /learn prune,
/learn export, /learn stats, /learn add.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* docs: self-learning roadmap — 5-release design doc
Covers: R1 GStack Learns (v0.14), R2 Review Army (v0.15), R3 Smart Ceremony
(v0.16), R4 /autoship (v0.17), R5 Studio (v0.18). Inspired by Compound
Engineering, adapted to GStack's architecture.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* test: learnings bin script unit tests — 13 tests, free
Tests gstack-learnings-log (valid/invalid JSON, timestamp injection,
append-only) and gstack-learnings-search (dedup, type/query/limit filters,
confidence decay, user-stated no-decay, malformed JSONL skip).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore: bump version and changelog (v0.13.4.0)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* test: learnings resolver + bin script edge case tests — 21 new tests, free
Adds gen-skill-docs coverage for LEARNINGS_SEARCH, LEARNINGS_LOG, and
CONFIDENCE_CALIBRATION resolvers. Adds bin script edge cases: timestamp
preservation, special characters, files array, sort order, type grouping,
combined filtering, missing fields, confidence floor at 0.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: sync package.json version with VERSION file (0.13.4.0)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore: gitignore .factory/ — generated output, not source
Same pattern as .claude/skills/ and .agents/. These SKILL.md files are
generated from .tmpl templates by gen:skill-docs --host factory.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* test: /learn E2E — seed 3 learnings, verify agent surfaces them
Seeds N+1 query pattern, stale cache pitfall, and rubocop preference
into learnings.jsonl, then runs /learn and checks that at least 2/3
appear in the agent's output. Gate tier, ~$0.25/run.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>