python-best-practices

Enforce PEP 8 compliance, type hints, and NumPy-style docstrings in Python code.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/elevanaltd/oa --skill python-best-practices-elevanaltd
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-best-practices
Source: https://github.com/elevanaltd/oa/tree/main/.claude/skills/python-best-practices
Command: npx skills add https://github.com/elevanaltd/oa --skill python-best-practices-elevanaltd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Inconsistent Python code style, lack of type hints, and poor documentation lead to hard-to-read, error-prone, and difficult-to-maintain codebases, increasing technical debt.

Core Features & Use Cases

  • PEP 8 Compliance: Enforces standard Python style guidelines for indentation, line length, naming conventions, and import organization, ensuring consistent code.
  • Mandatory Type Hints: Guides the use of modern type hint syntax for function signatures and complex variables, improving code clarity, error detection, and refactoring safety.
  • NumPy Style Docstrings: Promotes comprehensive documentation for all public functions and classes, enhancing readability, maintainability, and auto-documentation generation.
  • Use Case: When writing a new Python module, use this skill to ensure all functions are properly typed, docstrings follow NumPy style, and the code adheres to PEP 8 guidelines, leading to higher quality, more maintainable code.

Quick Start

Write a Python function process_data that takes a list of strings and an optional max_count, returning a dictionary of counts, ensuring it's fully typed and has a NumPy-style docstring.