A powerful utility designed to parse SKILL.md files and generate actionable, human-friendly usage guides for any AI agent skill.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skill-usage-analyzer
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-usage-analyzer 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 Usage Analyzer?
The Skill Usage Analyzer is a specialized tool developed for the Openclaw Skills ecosystem to solve the problem of documentation fatigue. Instead of manually sifting through long Markdown files, this skill intelligently parses the metadata and content of a SKILL.md file to produce structured summaries, configuration tables, and practical code snippets.
By leveraging automated semantic analysis, it identifies core functionalities, hidden configuration options, and common pitfalls. This ensures that developers and users can rapidly understand and deploy new capabilities without losing time on technical deep-dives, effectively acting as a bridge between complex technical specifications and immediate execution.
Skill Usage Analyzer Use Cases
- Rapidly onboarding new Openclaw Skills into your local environment by generating quick-start guides.
- Comparing multiple skills to decide which tool is best suited for a specific automation task.
- Auditing a workspace to identify missing documentation or uninstalled dependencies across a skill library.
- Discovering creative combinations and dependency graphs between different AI agent tools.
How Skill Usage Analyzer Works
- Metadata Parsing: The tool reads the frontmatter and headers of the target SKILL.md file to identify identity and requirements.
- Structural Extraction: It identifies code blocks, lists, and tables to separate installation steps from usage examples.
- Semantic Analysis: The analyzer interprets function descriptions to categorize the skill's purpose and primary use cases.
- Report Generation: Data is compiled into a chosen format (Text, Markdown, or JSON) using a standardized template for consistency.
Skill Usage Analyzer Setup
To start analyzing your Openclaw Skills, ensure you have Python 3 installed and use the following commands:
# Analyze a specific skill file
python3 scripts/analyze_skill.py /path/to/skill/SKILL.md
# Analyze all installed skills in your workspace
python3 scripts/analyze_all.py
Skill Usage Analyzer Data Schema & Taxonomy
The analyzer organizes data into a structured hierarchy to ensure scannability:
| Section | Data Points Extracted |
|---|---|
| Basic Info | Name, description, and applicable scenarios. |
| Core Functions | Numbered list of primary capabilities with brief explanations. |
| Examples | Concrete CLI commands and code snippets for immediate use. |
| Configuration | Storage paths, environment variables, and default values. |
| Risk Assessment | Common issues, latency warnings, and network dependencies. |
Skill Usage Analyzer Advanced Features
- Multi-format output support allowing exports to Markdown or raw JSON for integration with other automation pipelines.
- Automated dependency graphing to visualize how various Openclaw Skills interact using Mermaid JS.
- Intelligent skill recommendation engine that suggests tool combinations based on a natural language task description.
- Batch processing capabilities to generate a comprehensive local index of all available skills.
SKILL.md
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