Docstring Formatter FAQs

Question 1

How does it improve my documentation accuracy?

Accepted Answer

By programmatically analyzing function signatures, the skill ensures that every parameter and return type is accounted for. This reduces human error where documentation becomes out of sync with the actual code implementation.

Question 2

Can this skill handle specialized libraries like PyTorch?

Accepted Answer

Yes. It includes specialized templates for PyTorch nn.Modules, properties, and complex scientific functions. it correctly documents class attributes, forward methods, and even includes support for LaTeX mathematical formulas in the Notes section.

Question 3

What does the Docstring Formatter skill do?

Accepted Answer

This skill automates the standardization of Python documentation. It converts existing plain-text or Google-style comments into structured NumPy and Sphinx-style docstrings, automatically extracting parameters, types, and return values directly from your function signatures.

Question 4

Does it support the creation of executable examples?

Accepted Answer

Absolutely. The skill generates structured 'Examples' sections using the doctest format (>>>), making your documentation more helpful for end-users and allowing for automated testing of the documentation itself.

Question 5

When should I use this skill in my workflow?

Accepted Answer

You should use this skill during the code quality phase of development, specifically when preparing modules for API documentation, refactoring legacy code, or ensuring that a large codebase (~50+ functions) meets professional documentation standards like pydocstyle.

Docstring Formatter

Docstring Formatter

Key Features

Use Cases

Key Features

Use Cases