Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
Quickly install testing-python AI skill to your development environment via command line
Source: jlowin/fastmcp.
Every test should be atomic, self-contained, and test single functionality. A test that tests multiple things is harder to debug and maintain.
Each test should verify a single behavior. The test name should tell you what's broken when it fails. Multiple assertions are fine when they all verify the same behavior.
Don't parameterize unrelated behaviors. If the test logic differs, write separate tests.
Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing. Source: jlowin/fastmcp.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/jlowin/fastmcp --skill testing-pythonWrite and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing. Source: jlowin/fastmcp.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/jlowin/fastmcp --skill testing-python Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/jlowin/fastmcp