Skills self-improving-to-expertpack

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 — 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'.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/brianhearn/self-improving-to-expertpack" ~/.claude/skills/clawdbot-skills-self-improving-to-expertpack && rm -rf "$T"

manifest: skills/brianhearn/self-improving-to-expertpack/SKILL.md

source content

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

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

```
cd ~/expertpacks/my-learnings-pack
```
Verify content files are 400–800 tokens each (Schema 2.5 — retrieval-ready by design)

Measure EK ratio:

python3 /path/to/expertpack/tools/eval-ek.py .

Review
```
overview.md
```
and
```
manifest.yaml
```
Commit to git and publish to ClawHub

Learn more: https://expertpack.ai • ClawHub expertpack skill

See also: Self-Improving Agent skill on ClawHub.