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stack-python

Enforce Python quality gates with Ruff, mypy, and pytest.

Updated Feb 11, 2026
Search Tags:#testing#development#pytest#python#quality gates#mypy#ruff
One-click install
npx skills add https://github.com/juniorfontenele/ai-guidelines --skill stack-python
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stack-python
Source: https://github.com/juniorfontenele/ai-guidelines/tree/main/.agents/skills/stack-python
Command: npx skills add https://github.com/juniorfontenele/ai-guidelines --skill stack-python

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured approach to Python development, ensuring code quality, maintainability, and adherence to best practices.

Core Features & Use Cases

  • Quality Gates: Integrates Ruff for linting/formatting and mypy for type checking.
  • Testing: Establishes patterns for using pytest for unit and integration tests.
  • Project Structure: Recommends an idiomatic Python project layout.
  • Use Case: When starting a new Python project or refactoring an existing one, use this Skill to set up robust quality checks and testing frameworks from the outset.

Quick Start

Configure Ruff and mypy for your Python project by running ruff check . and mypy ..

Frequently Asked Questions about stack-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What are the best practices for setting up Python quality gates with Ruff and mypy?▼

Python quality gates combine Ruff for linting and formatting with mypy for strict type checking. Running `ruff check .` and `mypy .` enforces code quality and maintainability across your project by catching errors early.

How do I structure a Python project for pytest testing and type hints?▼

Structure Python projects using an idiomatic layout that separates source and tests, requires type hints throughout, and uses pytest for unit and integration tests. Pydantic handles data validation while async improves performance where appropriate.

Does this Python development approach require Pydantic and async patterns?▼

Yes, this Python development approach requires adherence to type hints and Pydantic for validation. It also mandates using async where appropriate, ensuring robust, maintainable code patterns are followed consistently across the project.

What's the best way to enforce Python development patterns when refactoring?▼

Enforce Python development patterns by integrating Ruff, mypy, and pytest from the outset. This combination provides idiomatic patterns, strict type checking, and comprehensive testing guidelines that maintain code quality during refactoring.

When should I use mypy and Ruff configuration in my Python project?▼

Use mypy and Ruff configuration when implementing Python features, starting new projects, or refactoring existing ones. These quality gates enforce development patterns, ensure type hint adherence, and maintain code quality standards.

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