External user filed 4/8 false positives on a /review run against a Django +
DRF + PostgreSQL repo (Sprint 2.5). Every FP class was the same shape:
"resolvable in <5 minutes by viewing the actual code or running a simple
grep" — fields that don't exist on the model, dict.get()-might-be-None on a
form that returns {}-initialized cleaned_data, standard ORM save behavior
called out as data loss.
Extends the Confidence Calibration resolver (consumed by review, cso,
plan-eng-review, ship) with a Pre-emit verification gate:
Every finding MUST quote the specific code line that motivates it
(file:line + verbatim text). If the reviewer cannot produce the quote,
the finding is unverified — its confidence is forced to 4-5 so the
existing "Suppress from main report" rule fires automatically. The
finding still goes to the appendix for calibration audit, but the user
does not see it in the critical-pass output.
Reuses the existing suppression mechanism — no new code path. The FP
classes the gate kills are enumerated in the resolver text so reviewers
see the named patterns.
Framework-meta nudge included for Django Meta, Rails associations,
SQLAlchemy relationships, TypeORM decorators, Sequelize init, Prisma
generated client — the reviewer must quote the meta-construct that
generates the symbol, not just grep for the literal name. Deeper
framework-aware ORM verification (model introspection, migration-history-
aware checks) is deliberately deferred to a future wave per T-Codex-2.
Atomic .tmpl-equivalent (resolver) edit + gen:skill-docs regen commit
per T-Codex-3.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* 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>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Garry Tan