learn

# /learn — Extract Patterns into Instincts Analyze recent work (observations, git history, solutions) and extract reusable "instincts" — small learned behaviors with confidence scoring. ## When to Use - After completing a feature or fixing a bug - At the end of a coding session - When you want to capture a pattern you noticed - Periodically to keep the project's knowledge current ## Execution Flow ### Step 1: Gather Evidence Run these in parallel to collect data: 1. **Git history** — `git log --oneline -20` for recent commits 2. **Recent diffs** — `git diff HEAD~5..HEAD --stat` for what changed 3. **Observations** — Read `.atv/observations.jsonl` for tool use patterns from hooks 4. **Existing instincts** — Read `.atv/instincts/project.yaml` (create if missing) 5. **Solutions** — Read `docs/solutions/` for documented patterns ### Step 2: Analyze Patterns Look for recurring patterns across the evidence: **Code style patterns:** - Error handling conventions (wrapping, custom types, sentinel errors) - Naming conventions (variable, function, file naming) - Import organization preferences - Comment style and documentation patterns **Workflow patterns:** - Test-first vs test-after behavior - Commit granularity preferences - Branch naming conventions - Review practices **Architecture patterns:** - Package/module organization - Dependency injection style - Interface usage patterns - Configuration management approach **Tool usage patterns** (from observations.jsonl): - Frequently used shell commands - Common file editing sequences - Preferred build/test commands ### Step 3: Create or Update Instincts For each new pattern discovered, create an instinct entry. For patterns that match existing instincts, increase confidence and observation count. **Instinct format** (YAML in `.atv/instincts/project.yaml`): ```yaml instincts: - id: kebab-case-unique-id trigger: "when [specific situation]" behavior: "do [specific action]" confidence: 0.5 domain: code-style|testing|architecture|error-handling|workflow|tooling observations: 1 first_seen: YYYY-MM-DD last_seen: YYYY-MM-DD evidence: - "commit abc123: wrapped all errors with fmt.Errorf" - "observed 3 times in observations.jsonl" ``` **Confidence rules:** - New instinct starts at 0.5 - Each additional observation: +0.1 (capped at 0.95) - Contradictory evidence: -0.15 - No observations for 30 days: -0.1 - Minimum: 0.1 (below this, remove the instinct) **Important constraints:** - Maximum 50 active instincts per project - Each instinct must be atomic — one trigger, one behavior - Triggers must be specific (not "when writing code") - Behaviors must be actionable (not "write good code") - Evidence must cite specific commits or observations ### Step 4: Write Results 1. Write updated `.atv/instincts/project.yaml` 2. Ensure `.atv/instincts/` directory exists ### Step 5: Report Show a summary: ``` Learning complete! New instincts: + always-wrap-errors (0.5) — wrap errors with fmt.Errorf using %w + table-driven-tests (0.5) — use table-driven test pattern for Go tests Updated instincts: ↑ prefer-early-returns (0.6 → 0.7) — 1 new observation ↑ run-tests-before-commit (0.7 → 0.8) — 2 new observations Ready to evolve (confidence > 0.8): ★ run-tests-before-commit — consider /evolve to generate a skill Total: X instincts (Y new, Z updated) Instinct file: .atv/instincts/project.yaml ``` ## Notes - Instincts are project-scoped and committed to the repo — the whole team benefits - Run `/instincts` to see all learned patterns - Run `/evolve` when instincts reach high confidence to generate full skills - The observer hooks in `.github/hooks/copilot-hooks.json` automatically capture tool use data