continuous-learning

name	continuous-learning
description	Automatically extract reusable patterns from agent sessions and save them as learned skills for future use.

Continuous Learning

Evaluate agent sessions on completion to extract reusable patterns saved as learned skills.

When to Activate

• Setting up automatic pattern extraction from agent sessions
• Configuring a Stop hook for session evaluation
• Reviewing or curating learned skills
• Adjusting extraction thresholds or pattern categories

How It Works

This skill runs as a Stop hook at the end of each session:

1. Session Evaluation: Checks if session has enough messages (default: 10+)
2. Pattern Detection: Identifies extractable patterns from the session
3. Skill Extraction: Saves useful patterns to a learned skills directory

Configuration

Edit config.json to customize:

{
  "min_session_length": 10,
  "extraction_threshold": "medium",
  "auto_approve": false,
  "learned_skills_path": "~/.config/agent/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 a Stop hook to your agent settings:

{
  "hooks": {
    "Stop": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "<skills-path>/continuous-learning/evaluate-session.sh"
      }]
    }]
  }
}

Why Stop Hook?

• Lightweight: Runs once at session end
• Non-blocking: Adds no latency to individual messages
• Complete context: Has access to the full session transcript

v2 Comparison

The v2 instinct-based approach (see continuous-learning-v2) offers finer granularity:

Feature	v1 (this)	v2 (instinct-based)
Observation	Stop hook (session end)	PreToolUse/PostToolUse hooks
Granularity	Full skills	Atomic "instincts"
Confidence	None	0.3–0.9 weighted
Evolution	Direct to skill	Instincts → cluster → skill/command/agent