metaskill

# Metaskill ## 3 Core Components 1. **Deep Self-Correction (`deep-correct.sh`)** — 3-level breakdown on errors: - **Surface**: What specifically failed - **Principle**: The underlying rule/constraint violated - **Habit**: Concrete behavioral change to prevent recurrence 2. **Transfer Learning (`transfer-check.sh`)** — Before a task, search past learnings for analogous patterns. Maps domains (e.g., "auth" → "security") to prevent siloed learning. 3. **Proactive Pattern Recognition (`success-capture.sh`)** — Log what worked and why, building a repository of successful patterns. ## Usage ```bash # 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: ```yaml # config.yaml providers: fast: anthropic # change to: openai | ollama | gemini deep: anthropic ``` | Provider | Env Var | Notes | |---|---|---| | `anthropic` | `ANTHROPIC_API_KEY` | Default | | `openai` | `OPENAI_API_KEY` | | | `ollama` | *(none needed)* | Local, free | | `gemini` | `GOOGLE_API_KEY` | | **Ollama example** (fully local, no API key): ```yaml 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