python

Identify Python codebase gaps in typing, formatting, testing, and secure coding.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/kittne/codex-skills-by-codex --skill python-kittne
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python
Source: https://github.com/kittne/codex-skills-by-codex/tree/main/python
Command: npx skills add https://github.com/kittne/codex-skills-by-codex --skill python-kittne

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill codifies Python best practices to ensure code quality, maintainability, and robust testing across projects by enforcing modern language features, typing discipline, and reliable tooling.

Core Features & Use Cases

  • Enforce Python 3.10+ with full type hinting, strict static analysis, and robust testing practices.
  • Standardize formatting and linting (Black + Ruff with 120-char lines, double quotes, sorted imports) and structured logging.
  • Provide a ground truth for secure coding, dependency hygiene, and test-driven development to accelerate safe refactors and new feature work.

Quick Start

Configure your project to adopt Python best-practices by aligning tooling and CI with the guidelines outlined above.

Frequently Asked Questions about python

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

FAQPage Schema
How do I enforce strict type checking and modern Python standards in my codebase?

To enforce strict type checking in Python, apply Python 3.10+ compatibility rules and run static analysis with mypy or pyright. This identifies typing gaps to ensure reliable, maintainable software across your projects.

What is the best way to standardize Python formatting and linting with Black and Ruff?

Standardizing Python formatting with Black and Ruff involves enforcing 120-character lines, double quotes, and sorted imports. This codifies best practices to ensure code quality and maintainability across your project.

How do I set up formal testing practices and dependency hygiene in a Python CI pipeline?

Setting up formal testing in a Python CI pipeline requires enforcing test-driven development with pytest and checking dependency hygiene. This provides a ground truth for secure coding to accelerate safe refactors.

Does this Python best practices skill work for small scripts as well as large services?

Yes, these Python best practices apply to projects ranging from small scripts to large services. The guidelines scale across CI pipelines, code reviews, and release engineering to maintain robust software.