ontology-to-expertpack

What This Skill Does

The ontology-to-expertpack skill serves as a critical bridge between OpenClaw's legacy append-only knowledge graph (Ontology skill) and the modern, high-performance ExpertPack architecture. This utility automates the transformation of unstructured or semi-structured JSONL graph data into the standardized ExpertPack directory format. By parsing your graph.jsonl and optional schema.yaml, the skill maps individual entities and relations into organized, chunked content folders. It generates a production-ready manifest, a comprehensive glossary, and normalized file structures in kebab-case that are optimized for RAG (Retrieval-Augmented Generation) and multi-layer retrieval systems. It transforms disparate data points into an actionable, portable knowledge asset ready for deployment within the OpenClaw ecosystem.

Installation

To integrate this tool into your workspace, execute the following command in your terminal or via the OpenClaw CLI:

clawhub install openclaw/skills/skills/brianhearn/ontology-to-expertpack

Ensure that you have Python 3 installed in your local environment, as the skill utilizes a internal Python-based converter script to handle the graph traversal and file generation logic.

Use Cases

This skill is designed for advanced users and developers who have outgrown the limitations of a flat ontology graph. Use this when:

1. Migrating Legacy Data: You want to upgrade your existing knowledge graph to take advantage of the sophisticated chunking and indexing capabilities of the ExpertPack standard.
2. Knowledge Portability: You need to export a specific subset of learned knowledge into a portable folder structure for sharing across different OpenClaw agents or team environments.
3. Performance Optimization: You are experiencing retrieval latency or context-window saturation and need a structured, tiered knowledge pack that allows for optimized semantic search.
4. Governance Readiness: You need to prepare your data for external auditing, requiring the structured manifest and metadata tracking provided by the ExpertPack output.

Example Prompts

1. "OpenClaw, I need to upgrade my current knowledge structure; run the ontology-to-expertpack converter on my local graph.jsonl to create a new pack in ~/expertpacks/project-alpha."
2. "Migrate the ontology knowledge to a structured ExpertPack using the schema.yaml file located in my current project directory and name the resulting pack 'Technical Operations Handbook'."
3. "Convert my memory ontology graph to an ExpertPack format and ensure the output type is set to process so it integrates correctly with my existing workflow automation."

Tips & Limitations

• Chunking Strategy: While the skill generates essential summaries, remember that after conversion, you must run the ExpertPack chunker to fully populate the propositions/ and summaries/ folders for optimal retrieval results.
• File Limits: The tool enforces a 3KB file size limit per content file to ensure high granularity during embedding; if you have massive monolithic nodes, consider pre-splitting them.
• Dependencies: Always verify your schema.yaml syntax before conversion; improper mapping of relation rules can lead to broken navigation links in the generated _index.md files.
• Deployment: The output directory is git-ready, so initialize a repository within the folder immediately after generation to track iterative changes to your knowledge pack.