Continuous Learning Skill
Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills.
How It Works
This skill runs as a Stop hook at the end of each session:
Session Evaluation: Checks if session has enough messages (default: 10+) Pattern Detection: Identifies extractable patterns from the session Skill Extraction: Saves useful patterns to ~/.claude/skills/learned/ Configuration
Edit config.json to customize:
{ "min_session_length": 10, "extraction_threshold": "medium", "auto_approve": false, "learned_skills_path": "~/.claude/skills/learned/", "patterns_to_detect": [ "error_resolution", "user_corrections", "workarounds", "debugging_techniques", "project_specific" ], "ignore_patterns": [ "simple_typos", "one_time_fixes", "external_api_issues" ] }
Pattern Types Pattern Description error_resolution How specific errors were resolved user_corrections Patterns from user corrections workarounds Solutions to framework/library quirks debugging_techniques Effective debugging approaches project_specific Project-specific conventions Hook Setup
Add to your ~/.claude/settings.json:
{ "hooks": { "Stop": [{ "matcher": "*", "hooks": [{ "type": "command", "command": "~/.claude/skills/continuous-learning/evaluate-session.sh" }] }] } }
Why Stop Hook? Lightweight: Runs once at session end Non-blocking: Doesn't add latency to every message Complete context: Has access to full session transcript Related The Longform Guide - Section on continuous learning /learn command - Manual pattern extraction mid-session Comparison Notes (Research: Jan 2025) vs Homunculus (github.com/humanplane/homunculus)
Homunculus v2 takes a more sophisticated approach:
Feature Our Approach Homunculus v2 Observation Stop hook (end of session) PreToolUse/PostToolUse hooks (100% reliable) Analysis Main context Background agent (Haiku) Granularity Full skills Atomic "instincts" Confidence None 0.3-0.9 weighted Evolution Direct to skill Instincts → cluster → skill/command/agent Sharing None Export/import instincts
Key insight from homunculus:
"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."
Potential v2 Enhancements Instinct-based learning - Smaller, atomic behaviors with confidence scoring Background observer - Haiku agent analyzing in parallel Confidence decay - Instincts lose confidence if contradicted Domain tagging - code-style, testing, git, debugging, etc. Evolution path - Cluster related instincts into skills/commands
See: /Users/affoon/Documents/tasks/12-continuous-learning-v2.md for full spec.