Metaskill

3 Core Components

1. Deep Self-Correction (deep-correct.sh) — 3-level breakdown on errors:
2. Surface: What specifically failed
3. Principle: The underlying rule/constraint violated

4. Habit: Concrete behavioral change to prevent recurrence

5. Transfer Learning (transfer-check.sh) — Before a task, search past learnings for analogous patterns. Maps domains (e.g., "auth" → "security") to prevent siloed learning.

6. Proactive Pattern Recognition (success-capture.sh) — Log what worked and why, building a repository of successful patterns.

Usage

# When an error occurs
bash skills/metaskill/scripts/deep-correct.sh "description of the error"

# Before starting a complex task
bash skills/metaskill/scripts/transfer-check.sh "description of the new task"

# After successful execution
bash skills/metaskill/scripts/success-capture.sh "what worked" "why it worked"

# Monthly health eval
bash skills/metaskill/scripts/eval.sh --save

Configuration (LLM Provider)

Metaskill uses two provider tiers — fast (extraction) and deep (transfer/eval). Edit config.yaml to match your setup:

# config.yaml
providers:
  fast: anthropic   # change to: openai | ollama | gemini
  deep: anthropic

Ollama example (fully local, no API key):

providers:
  fast: ollama
  deep: ollama
models:
  ollama:
    fast: llama3.2
    deep: llama3.1:70b

If no provider is available, metaskill falls back to manual/heuristic mode (still works, but less precise extraction).

Integration with Self-Improving-Agent

Writes to skills/self-improving-agent/.learnings/ if present, otherwise falls back to its own .learnings/ directory. No extra setup needed.

AGENTS.md Wiring (Mandatory)

Add to pre-task checklist: 1. Run transfer-check.sh before any major task 2. Run deep-correct.sh immediately after any error (not just LEARNINGS.md append) 3. Run success-capture.sh after complex task completes successfully