Skill Quality Assurance

Automatically analyze and score OpenClaw skill documentation quality. Identifies critical issues and provides actionable fixes.

Overview

This skill runs a multi-dimensional quality analysis on any OpenClaw skill's SKILL.md file, scoring it across:

• Clarity — Structure, headings, sentence length
• Completeness — Required fields, install/usage sections
• Actionability — Step-by-step guides, commands
• Discoverability — Keywords, description, categories
• Examples — Code examples, before/after, use cases

Usage

Analyze a single skill

Analyze the skill at: C:\path\to\skills\my-skill

Analyze all skills in a directory

Run: node engine.js C:\path\to\skills

Interpretation

Scoring Dimensions

1. Clarity (20%)

Checks for: headings hierarchy, sentence length, filler words, markdown formatting

2. Completeness (20%)

Checks for: name, description, keywords, install section, usage section

3. Actionability (25%)

Checks for: numbered steps, runnable commands, configuration guides

4. Discoverability (15%)

Checks for: keywords (5+), description length (50+ chars), category/tags

5. Examples (20%)

Checks for: code blocks (3+), before/after cases, use case descriptions

Quality Thresholds

For ClawHub publication:

• Overall score ≥ 7.0 required
• No dimension below 5.0
• Must have keywords field
• Must have description ≥ 50 chars

Auto-Fix

The companion script fix_skill_md.cjs automatically fixes:

• Missing description field
• Missing keywords field
• Missing Install section
• Missing Usage section

node fix_skill_md.cjs

Example Output

# Skill Quality Report

Analyzed: 34 skills

## Overall Rankings
 1. ✅ skylv-browser-automation-agent   9.4/10
 2. ✅ skylv-openclaw-evomap-connector   9.3/10

Average score: 8.1/10
Grade A (7+): 29
Grade B (5-6): 5
Grade C (<5): 0

MIT License © SKY-lv