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12e1bc424d
Ports continuous-learning observer signal, storage, remote normalization, and v1 deprecation fixes onto current main.
132 lines
4.4 KiB
Markdown
132 lines
4.4 KiB
Markdown
---
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name: continuous-learning
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description: "[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1; route continuous learning, session learning, and pattern extraction requests to continuous-learning-v2."
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origin: ECC
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---
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# Continuous Learning Skill - DEPRECATED
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> **DEPRECATED 2026-04-28.** Use `continuous-learning-v2` instead. v2 is a strict superset: stop-hook observation becomes PreToolUse/PostToolUse observation, full skills become atomic instincts with confidence scoring, and global-only storage becomes project-scoped plus global promotion.
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>
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> This file is kept for archival reference and backward compatibility with existing installs.
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---
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## Original v1 Documentation (archival)
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Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills.
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## When to Activate
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- Setting up automatic pattern extraction from Claude Code sessions
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- Configuring the Stop hook for session evaluation
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- Reviewing or curating learned skills in `~/.claude/skills/learned/`
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- Adjusting extraction thresholds or pattern categories
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- Comparing v1 (this) vs v2 (instinct-based) approaches
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## Status
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This v1 skill is still supported, but `continuous-learning-v2` is the preferred path for new installs. Keep v1 when you explicitly want the simpler Stop-hook extraction flow or need compatibility with older learned-skill workflows.
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## How It Works
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This skill runs as a **Stop hook** at the end of each session:
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1. **Session Evaluation**: Checks if session has enough messages (default: 10+)
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2. **Pattern Detection**: Identifies extractable patterns from the session
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3. **Skill Extraction**: Saves useful patterns to `~/.claude/skills/learned/`
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## Configuration
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Edit `config.json` to customize:
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```json
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{
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"min_session_length": 10,
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"extraction_threshold": "medium",
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"auto_approve": false,
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"learned_skills_path": "~/.claude/skills/learned/",
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"patterns_to_detect": [
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"error_resolution",
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"user_corrections",
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"workarounds",
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"debugging_techniques",
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"project_specific"
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],
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"ignore_patterns": [
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"simple_typos",
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"one_time_fixes",
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"external_api_issues"
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]
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}
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```
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## Pattern Types
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| Pattern | Description |
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|---------|-------------|
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| `error_resolution` | How specific errors were resolved |
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| `user_corrections` | Patterns from user corrections |
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| `workarounds` | Solutions to framework/library quirks |
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| `debugging_techniques` | Effective debugging approaches |
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| `project_specific` | Project-specific conventions |
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## Hook Setup
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Add to your `~/.claude/settings.json`:
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```json
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{
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"hooks": {
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"Stop": [{
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"matcher": "*",
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"hooks": [{
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"type": "command",
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"command": "~/.claude/skills/continuous-learning/evaluate-session.sh"
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}]
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}]
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}
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}
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```
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## Why Stop Hook?
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- **Lightweight**: Runs once at session end
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- **Non-blocking**: Doesn't add latency to every message
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- **Complete context**: Has access to full session transcript
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## Related
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- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) - Section on continuous learning
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- `/learn` command - Manual pattern extraction mid-session
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---
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## Comparison Notes (Research: Jan 2025)
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### vs Homunculus
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Homunculus v2 takes a more sophisticated approach:
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| Feature | Our Approach | Homunculus v2 |
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|---------|--------------|---------------|
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| Observation | Stop hook (end of session) | PreToolUse/PostToolUse hooks (100% reliable) |
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| Analysis | Main context | Background agent (Haiku) |
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| Granularity | Full skills | Atomic "instincts" |
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| Confidence | None | 0.3-0.9 weighted |
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| Evolution | Direct to skill | Instincts → cluster → skill/command/agent |
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| Sharing | None | Export/import instincts |
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**Key insight from homunculus:**
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> "v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time. v2 uses hooks for observation (100% reliable) and instincts as the atomic unit of learned behavior."
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### Potential v2 Enhancements
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1. **Instinct-based learning** - Smaller, atomic behaviors with confidence scoring
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2. **Background observer** - Haiku agent analyzing in parallel
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3. **Confidence decay** - Instincts lose confidence if contradicted
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4. **Domain tagging** - code-style, testing, git, debugging, etc.
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5. **Evolution path** - Cluster related instincts into skills/commands
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See: `docs/continuous-learning-v2-spec.md` for full spec.
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