A universal quality assessment framework designed to audit, score, and optimize SKILL.md files for any AI agent environment.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skill-quality-check
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install skill-quality-check using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Skill Quality Check?
Skill Quality Check is a comprehensive framework designed to audit the performance and structure of AI agent skills. By focusing on five key dimensions, it helps developers refine their Openclaw Skills to ensure they trigger correctly and consume minimal context tokens. The framework emphasizes the three-layer loading principle, which separates concise triggers from detailed execution logic and heavy documentation. By using this tool, developers can ensure their skills are professional, technical, and highly actionable for modern AI coding agents.
Skill Quality Check Use Cases
- Auditing new Openclaw Skills before adding them to your local environment to ensure they meet quality standards.
- Refining skill descriptions to prevent mis-triggers in high-density agent environments.
- Optimizing token usage for long-running AI sessions by identifying bloated SKILL.md files.
- Benchmarking skill quality before submission to shared repositories like ClawHub or SkillHub.
How Skill Quality Check Works
- Analyze the YAML frontmatter for strict adherence to required fields, eliminating unnecessary metadata.
- Evaluate the Level 1 description to confirm it functions as a high-accuracy trigger rather than a manual.
- Scan the SKILL.md body for effective role-setting and diverse, structured XML examples.
- Assess resource layering to ensure large datasets are properly moved to references or scripts folders.
- Calculate performance impact based on token costs and potential mis-trigger risks.
- Generate a quantified audit report with prioritized recommendations (P0 to P2) for immediate improvement.
Skill Quality Check Setup
The Skill Quality Check protocol can be applied to any local or remote file to improve your Openclaw Skills. You can inspect your skills using standard terminal tools:
# Fetch a remote SKILL.md for auditing
curl -s "https://raw.githubusercontent.com/<owner>/<repo>/main/skills/<skill>/SKILL.md"
# Inspect the YAML frontmatter compliance
grep -A 5 "^---" SKILL.md | head -10
# Count lines to estimate Level 2 token volume
wc -l SKILL.md
Skill Quality Check Data Schema & Taxonomy
The Skill Quality Check organizes its findings into a specific audit report format that categorizes the health of Openclaw Skills.
| Section | Metric | Focus |
|---|---|---|
| YAML Compliance | Field validation | Ensures only name and description are in frontmatter. |
| Description Quality | Trigger accuracy | Evaluates conciseness and keyword coverage (under 150 chars). |
| Body Quality | Progressive disclosure | Checks for role-setting, instructions, and XML examples. |
| Resource Layering | Directory usage | Validates use of scripts/ and references/ for heavy content. |
| Performance | Token efficiency | Benchmarks Level 1 and Level 2 volumes against optimal limits. |
Skill Quality Check Advanced Features
- Quantitative grading system (Excellent to Poor) providing an objective score for every skill audited.
- Three-layer loading validation to ensure AI agents only load heavy data when necessary.
- Mis-trigger risk analysis to identify overlapping keywords across multiple Openclaw Skills.
- Priority-based actionable feedback loops for fixing bloated or vague skill definitions.
SKILL.md
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