self-improving-to-expertpack

# Self-Improving Agent → ExpertPack Converts a **Self-Improving Agent** skill's `.learnings/` directory (3.8K ClawHub installs) into a properly structured **ExpertPack**. **Supported sources:** - **LEARNINGS.md** — corrections, knowledge gaps, best practices, simplify-and-harden patterns - **ERRORS.md** — command failures, exceptions, integration issues - **FEATURE_REQUESTS.md** — user-requested capabilities and implementation notes - **Promoted content** — entries already promoted to CLAUDE.md, AGENTS.md, SOUL.md, TOOLS.md (detected and cross-referenced) ## Usage ```bash cd /root/.openclaw/workspace/ExpertPack/skills/self-improving-to-expertpack python3 scripts/convert.py \ --workspace /path/to/your/workspace \ --output ~/expertpacks/my-learnings-pack \ [--name "My Agent's Learnings"] \ [--type auto|person|agent|process] ``` Override `.learnings/` location with `--learnings /path/to/.learnings`. ## What It Produces A complete ExpertPack conforming to schema 2.3: - `manifest.yaml` (with context tiers, EK stub) - `overview.md` summarizing conversion (entry counts, categories, priority breakdown) - Structured directories mapped from learning types: - `mind/` — best practices, conventions, behavioral patterns, promoted rules - `facts/` — knowledge gaps filled, project-specific facts - `operational/` — error resolutions, tool gotchas, integration fixes - `summaries/` — pattern analyses, recurring issue summaries - `relationships/` — cross-references between related entries - `_index.md` files, lead summaries, `glossary.md` (if terms/tags found) - `relations.yaml` (from See Also links and shared tags) - Clean deduplication preferring promoted > resolved > pending entries **Secrets are automatically stripped** (sk-*, ghp_*, tokens, passwords). Warnings emitted for any found. ## Post-Conversion Steps 1. `cd ~/expertpacks/my-learnings-pack` 2. Verify content files are 400–800 tokens each (Schema 2.5 — retrieval-ready by design) 3. Measure EK ratio: `python3 /path/to/expertpack/tools/eval-ek.py .` 4. Review `overview.md` and `manifest.yaml` 5. Commit to git and publish to ClawHub **Learn more:** https://expertpack.ai • ClawHub [expertpack skill](https://clawhub.com/skills/expertpack) **See also:** Self-Improving Agent skill on ClawHub.