doc-generator
Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.
Best use case
doc-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.
Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "doc-generator" skill to help with this workflow task. Context: Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/doc-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How doc-generator Compares
| Feature / Agent | doc-generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate markdown documentation from Python codebases by analyzing source files, extracting docstrings, type hints, and code structure. Use when the user asks to document Python code, create API docs, or generate README files from source code.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Python Documentation Generator Generate comprehensive markdown documentation from Python source code. ## When to Use This Skill - User asks to "document this code" or "generate docs" - Creating API documentation from Python modules - Generating README files with usage examples - Extracting docstrings and type signatures into readable format - User mentions "documentation", "docstrings", or "API reference" ## Input Accept either: - Single Python file path - Directory path (recursively process .py files) - List of specific files ## Output Format Generate standard markdown with: ```markdown # Module Name Brief description from module docstring. ## Classes ### ClassName Description from class docstring. **Methods:** - `method_name(param: type) -> return_type`: Brief description ## Functions ### function_name(param: type) -> return_type Description from docstring. **Parameters:** - `param` (type): Description **Returns:** - type: Description ## Usage Examples ```python # Extract from docstring examples or generate basic usage ``` ``` ## Analysis Approach 1. **Parse Python files** using AST or inspection 2. **Extract key elements:** - Module-level docstrings - Class definitions and docstrings - Function/method signatures with type hints - Docstring content (support Google, NumPy, Sphinx formats) 3. **Organize hierarchically** (modules -> classes -> methods -> functions) 4. **Generate clean markdown** with consistent formatting ## Quality Guidelines - Preserve original docstring formatting when meaningful - Include type hints prominently in signatures - Group related items (all classes together, all functions together) - Add table of contents for large modules - Skip private members (leading underscore) unless explicitly requested - Handle missing docstrings gracefully (note "No description provided") ## Python Tools Prefer standard library: - `ast` module for parsing - `inspect` module for runtime introspection - `pathlib` for file handling No external dependencies required for basic documentation generation. ## Error Handling - Skip files with syntax errors (log warning) - Handle missing type hints gracefully - Warn if no docstrings found but continue processing - Validate file paths exist before processing
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