An automated auditing tool that analyzes and scores the documentation quality of Openclaw Skills across five critical technical dimensions.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skylv-skill-validator
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install skylv-skill-validator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Skill Quality Assurance tool is a specialized utility designed to maintain high documentation standards for AI agent capabilities. By evaluating Openclaw Skills against a multi-dimensional rubric, it ensures that every skill is readable, functional, and discoverable. This tool is essential for developers who want to ensure their Openclaw Skills meet professional benchmarks and are ready for integration into complex AI workflows.
At its core, this skill identifies critical documentation gaps such as missing frontmatter, weak descriptions, or lack of actionable examples. By providing a clear grading system from A to F, it helps developers prioritize improvements and ensures that the Openclaw Skills they build provide maximum value to end-users and other agents.
To start analyzing your Openclaw Skills, ensure you have the engine and the optional fix script available in your CLI environment.
To analyze a directory of skills:
node engine.js /path/to/your/skills
To automatically fix common documentation issues in your Openclaw Skills:
node fix_skill_md.cjs
The analysis engine organizes data by evaluating the following metadata taxonomy within Openclaw Skills:
| Scoring Dimension | Weight | Evaluation Criteria |
|---|---|---|
| Clarity | 20% | Heading hierarchy, sentence length, and proper markdown formatting. |
| Completeness | 20% | Existence of mandatory fields like name, description, and usage. |
| Actionability | 25% | Presence of numbered steps and copy-pasteable bash commands. |
| Discoverability | 15% | Sufficient keyword density and a description of at least 50 characters. |
| Examples | 20% | Inclusion of at least 3 code blocks and clear before/after scenarios. |
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