generate-docstrings
Create docstrings for functions and classes. Use when documenting code APIs.
Best use case
generate-docstrings is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Create docstrings for functions and classes. Use when documenting code APIs.
Teams using generate-docstrings should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/generate-docstrings/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How generate-docstrings Compares
| Feature / Agent | generate-docstrings | 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?
Create docstrings for functions and classes. Use when documenting code APIs.
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
# Generate Docstrings
Write comprehensive docstrings for functions and classes following standard formats (Google, NumPy, reStructuredText).
## When to Use
- Adding documentation to undocumented functions
- Improving code documentation completeness
- Ensuring consistent docstring format
- Supporting API documentation generation
## Quick Reference
```python
# Google-style docstring format
def matrix_multiply(a: ExTensor, b: ExTensor) -> ExTensor:
"""Multiply two matrices using optimized Mojo kernels.
Args:
a: First matrix (shape: m x n)
b: Second matrix (shape: n x k)
Returns:
Product matrix (shape: m x k)
Raises:
ValueError: If matrix dimensions don't align for multiplication
Example:
```mojo
>> a = ExTensor([[1, 2], [3, 4]], DType.float32)
>>> b = ExTensor([[1, 0], [0, 1]], DType.float32)
>>> c = matrix_multiply(a, b)
```
"""
...
```
## Workflow
1. **Analyze function**: Understand purpose, parameters, return value
2. **Choose format**: Select docstring style (Google is recommended)
3. **Write summary**: Clear one-line description
4. **Document parameters**: Type, description, constraints
5. **Document return**: Type and description of return value
6. **Add examples**: Practical usage examples
## Output Format
Docstring structure:
- One-line summary
- Extended description (if needed)
- Args section (parameter documentation)
- Returns section (return value documentation)
- Raises section (exceptions)
- Examples section (usage examples)
## References
- See `generate-api-docs` skill for API documentation generation
- See Google Python Style Guide for docstring conventions
- See PEP 257 for Python docstring conventionsRelated Skills
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