Skills ontology-to-expertpack

Name: ontology-to-expertpack
Author: openclaw

Convert an Ontology skill knowledge graph into a structured ExpertPack. Use when migrating from the Ontology skill's entity/relation graph (memory/ontology/graph.jsonl) to ExpertPack's richer format with multi-layer retrieval, EK measurement, and portable deployment. Output is Obsidian-compatible — includes YAML frontmatter on all content files and can be opened as an Obsidian vault. Triggers on: 'ontology to expertpack', 'convert ontology', 'export ontology', 'migrate ontology', 'ontology graph to pack', 'upgrade ontology'. Requires the Ontology skill's graph.jsonl and optionally schema.yaml.

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 "$T/skills/brianhearn/ontology-to-expertpack" ~/.claude/skills/openclaw-skills-ontology-to-expertpack && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

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

manifest: skills/brianhearn/ontology-to-expertpack/SKILL.md

Ontology to ExpertPack Converter

Converts an OpenClaw Ontology skill's append-only knowledge graph into a fully compliant ExpertPack with multi-layer retrieval support.

How to Use

Run the converter script:

python3 {skill_dir}/scripts/convert.py \
  --graph memory/ontology/graph.jsonl \
  --output ~/expertpacks/my-knowledge-pack

Optional flags:

```
--schema memory/ontology/schema.yaml
```
— uses type definitions and relation rules
```
--name "My Knowledge Pack"
```
— custom pack name (defaults to "Ontology Export")

--type auto|person|product|process|composite

— override auto-detected pack type

What It Produces

A complete ExpertPack at the output directory:

```
manifest.yaml
```
— pack identity, type, context tiers, EK metadata placeholder
```
overview.md
```
— summary of graph contents, entity/relation counts, navigation guide
Content organized by mapped category (relationships/, workflows/, facts/, concepts/, operational/, governance/)
```
_index.md
```
in each content directory
```
relations.yaml
```
— typed entity relation graph (schema 2.3 compliant)
```
glossary.md
```
— entity types and terms
Lead summaries and
```
##
```
section headers for optimal chunking

Filenames use kebab-case. Content files kept under 3KB.

Post-Conversion Steps

```
cd
```
into the generated ExpertPack directory
Verify content files are 400–800 tokens each (Schema 2.5 — no external chunker needed for correctly-sized files)
Run EK evaluator to measure esoteric knowledge ratio
Review and refine
```
manifest.yaml
```
context tiers
Commit to git and share via expertpack.ai or ClawHub

See expertpack.ai and the

expertpack

ClawHub skill for full pack maintenance workflows.

Keep the output pack git-friendly and ready for iterative deepening.