Can it help me avoid common testing mistakes?

Absolutely. It includes a dedicated section on anti-patterns, such as mutable fixture defaults and resource leakages, to ensure your tests are reliable.

What is the Pytest Pattern Enforcer?

It is a Claude Code skill that provides domain-specific guidance to ensure generated Python tests follow industry-standard pytest best practices and implementation patterns.

How does it improve test organization?

The skill enforces the Arrange-Act-Assert (AAA) structure and encourages the use of classes and scoped fixtures to keep test suites clean and modular.

Does this skill support asynchronous Python code?

Yes, it includes specific patterns for @pytest.mark.asyncio and AsyncMock to handle modern asynchronous application testing correctly.

Pytest Pattern Enforcer

Name: Pytest Pattern Enforcer
Author: ricardoroche

byricardoroche

Security & Testing

Enforces standardized pytest best practices including advanced fixtures, mocking strategies, and async test patterns.

About

Pytest Pattern Enforcer is a specialized skill for Claude Code designed to elevate the quality of Python test suites. It automatically guides Claude to implement the Arrange-Act-Assert (AAA) structure, utilize session-scoped fixtures, and apply sophisticated parametrization. By enforcing these patterns, the skill helps developers maintain readable, maintainable, and comprehensive test coverage while avoiding common pitfalls such as mutable fixtures and unorganized test logic. It is particularly useful for projects requiring complex mocking or asynchronous testing support.

Key Features

AAA (Arrange-Act-Assert) pattern enforcement
Advanced fixture management with scopes and cleanup
Anti-pattern detection and correction
0 GitHub stars
Async testing and AsyncMock implementation
Data-driven testing via robust parametrization

Use Cases

Mocking external APIs and database interactions for integration tests
Refactoring legacy test suites into organized, fixture-driven structures
Generating comprehensive unit tests for complex Python business logic

About

Key Features

AAA (Arrange-Act-Assert) pattern enforcement
Advanced fixture management with scopes and cleanup
Anti-pattern detection and correction
0 GitHub stars
Async testing and AsyncMock implementation
Data-driven testing via robust parametrization

Use Cases

Mocking external APIs and database interactions for integration tests
Refactoring legacy test suites into organized, fixture-driven structures
Generating comprehensive unit tests for complex Python business logic