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Found 37 Skills
Write or refresh Python test coverage. Use when Codex needs to add coverage, replace stale tests, prefer executable doctest examples in public docstrings, or lock down Python behavior in repos that use `uv`, `pytest`, `nox`, and `mise`.
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices. Use for Python projects, APIs, data processing, or automation scripts.
Test-driven development workflow enforcement for Python and React projects. Use when the user requests TDD, test-first development, or red-green-refactor methodology. Enforces strict cycle: write ONE failing test -> implement minimum code to pass -> refactor while green -> repeat. Applies to both backend (pytest) and frontend (Testing Library). Changes agent behavior to write tests before code. Does NOT provide testing patterns (use pytest-patterns or react-testing-patterns for how to write tests).
Comprehensive pytest testing skill for Python projects. Write efficient, maintainable tests with fixtures, parametrization, markers, mocking, and assertions. Use when: (1) Writing new tests for Python code, (2) Setting up pytest in a project, (3) Creating fixtures for test dependencies, (4) Parametrizing tests for multiple inputs, (5) Mocking/patching with monkeypatch, (6) Debugging test failures, (7) Organizing test suites with markers, (8) Any Python testing task.
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers). For Prowler-specific API/SDK testing conventions, also use prowler-test-api or prowler-test-sdk.
Generate pytest test cases for Python functions and classes
Analyze and optimize pytest suites to improve speed, identify flaky tests, and increase coverage. Use to maintain high-quality, fast-running test pipelines.
pytest - Python's most powerful testing framework with fixtures, parametrization, plugins, and framework integration for FastAPI, Django, Flask
This skill should be used when writing tests, fixing bugs, adding features, or modifying the gateway layer. Use when you need guidance on testing architecture, working with fakes, implementing ABC gateway interfaces, or understanding the defense-in-depth testing strategy. Essential for maintaining test quality and understanding where different types of tests belong.
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.
Use when writing, fixing, editing, or refactoring Python tests. Enforces Clean Code principles—fast tests, boundary coverage, one assert per test.
Provides comprehensive guidance for pytest testing framework including test writing, fixtures, parametrization, mocking, and plugins. Use when the user asks about pytest, needs to write Python tests, use pytest fixtures, or configure pytest for Python projects.