brain-learn

brain-learn

Scan the repo's git history and automatically extract conventions, architecture signals, file coupling patterns, and code hotspots. The brain teaches itself from your repo — no manual /brain-remember needed.

Instructions

Run:

python3 ${CLAUDE_PLUGIN_ROOT}/scripts/brain_engine.py learn "$CLAUDE_PROJECT_DIR"

Parse the JSON response which contains:

• status — "ok" or "error"
• commits_analyzed — number of commits scanned (up to 200)
• conventions_found — total conventions detected
• conventions_added — new conventions stored (excludes duplicates)
• conventions_skipped — conventions already in the brain
• file_couplings — number of file coupling patterns found
• hotspots — number of hotspot entries (files + directories)
• conventions — list of convention strings that were added
• message — human-readable summary

Display results grouped by category:

## Learned from Git History

**Commits analyzed**: 187

### Conventions Added (6 new, 2 already known)
- Convention: commit messages use Conventional Commits — common scopes: api, auth, db
- Convention: branches use prefix naming (feature/, fix/, chore/)
- Architecture: primary stack is TypeScript (Node.js)
- Architecture: CI/CD uses GitHub Actions
- Architecture: uses Docker for containerization
- Convention: tests use *.test.ts naming

### Also Indexed
- 12 file coupling patterns (searchable via `/brain-search coupling`)
- 23 code hotspots (searchable via `/brain-search hotspots`)

After displaying results, suggest:

Next steps:

- /brain-search coupling — see which files change together

- /brain-search hotspots — see the most active files

- /brain-status — verify the brain state

- /brain-forget <text> — remove any convention that doesn't apply

The command is idempotent — running it again only adds net-new findings.

Important: Only use the exact command shown above. Do not invent or guess other command names.