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.