code-docs-generator

What This Skill Does

The Code Documentation Generator is a powerful OpenClaw AI agent skill designed to bridge the gap between complex source code and accessible, high-quality documentation. It automatically crawls your repositories to extract API specifications, SDK method definitions, and structural hierarchies. By parsing JSDoc, TypeDoc, OpenAPI/Swagger schemas, and language-specific docstrings, it creates human-readable documentation that stays in sync with your codebase. Whether you are managing a monolithic application or microservices, this skill eliminates the manual drudgery of writing technical guides, allowing development teams to focus on shipping features rather than maintaining wikis.

Installation

To integrate this tool into your workflow, run the following command within your OpenClaw terminal: clawhub install openclaw/skills/skills/sa9saq/code-docs-generator Once installed, ensure the agent has the necessary file system permissions to scan your local project directories or remote repository endpoints.

Use Cases

• API Documentation: Quickly generate OpenAPI 3.0 specs to share with frontend developers or external API consumers.
• Onboarding Acceleration: Auto-generate 'Getting Started' guides and tutorials for new developers joining a legacy project.
• Open Source Maintenance: Maintain professional-grade READMEs and documentation sites without manual formatting effort.
• Compliance & Auditing: Ensure that code definitions align with formal API contracts, automatically highlighting discrepancies during the documentation generation phase.

Example Prompts

1. "Analyze the repository at https://github.com/example/api and generate an OpenAPI 3.0 YAML file for all endpoints."
2. "Scan the current directory's TypeScript files and create a TypeDoc-style markdown summary for all public functions."
3. "Generate a comprehensive README.md for this Python project, including installation steps, usage examples, and a description of core modules based on current docstrings."

Tips & Limitations

• Contextual Accuracy: The quality of output is directly correlated to the quality of your inline code comments. Ensure your functions and classes are documented with standard annotations (JSDoc, Python Docstrings).
• Large Projects: For massive monolithic repositories, consider limiting the scan to specific directories to prevent token timeouts or hallucinations.
• Review Required: Always review generated documentation before publication, especially regarding security notes or private internal endpoints that should not be exposed in public API references.
• CI/CD Integration: For best results, trigger this skill as part of your CI pipeline to ensure documentation updates whenever the master branch is updated.