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Self Improving To Expertpack

by @brianhearn

Convert Self-Improving Agent learnings into a structured ExpertPack. Migrates the .learnings/ directory (LEARNINGS.md, ERRORS.md, FEATURE_REQUESTS.md) and an...

Versionv1.0.1
Downloads737
Stars⭐ 1
TERMINAL
clawhub install self-improving-to-expertpack

πŸ“– About This Skill


name: self-improving-to-expertpack description: "Convert Self-Improving Agent learnings into a structured ExpertPack. Migrates the .learnings/ directory (LEARNINGS.md, ERRORS.md, FEATURE_REQUESTS.md) and any promoted content from workspace files into ExpertPack's portable format with multi-layer retrieval, context tiers, and EK measurement. Output is Obsidian-compatible β€” includes YAML frontmatter on all content files and can be opened as an Obsidian vault. Use when: upgrading from Self-Improving Agent to ExpertPack, backing up agent learnings, exporting accumulated knowledge, or migrating to a new platform. Triggers on: 'self-improving to expertpack', 'convert self-improving', 'export learnings', 'migrate self-improving', 'learnings to expertpack', 'convert learnings to pack'." metadata: openclaw: homepage: https://expertpack.ai requires: bins: - python3

Self-Improving Agent β†’ ExpertPack

Converts a Self-Improving Agent skill's .learnings/ directory (3.8K ClawHub installs) into a properly structured ExpertPack.

Supported sources:

  • LEARNINGS.md β€” corrections, knowledge gaps, best practices, simplify-and-harden patterns
  • ERRORS.md β€” command failures, exceptions, integration issues
  • FEATURE_REQUESTS.md β€” user-requested capabilities and implementation notes
  • Promoted content β€” entries already promoted to CLAUDE.md, AGENTS.md, SOUL.md, TOOLS.md (detected and cross-referenced)
  • Usage

    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/ β€” best practices, conventions, behavioral patterns, promoted rules - facts/ β€” knowledge gaps filled, project-specific facts - operational/ β€” error resolutions, tool gotchas, integration fixes - summaries/ β€” pattern analyses, recurring issue summaries - relationships/ β€” 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 β€” 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 β€’ ClawHub expertpack skill

    See also: Self-Improving Agent skill on ClawHub.

    πŸ’‘ Examples

    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.