Does it review fixture configuration in conftest.py?

Yes, it analyzes fixtures for appropriate scoping (function, class, module, or session) and ensures yield fixtures have proper cleanup blocks.

Does this skill support asynchronous Python tests?

Yes, it specifically reviews async test patterns, ensuring correct usage of AsyncMock and ensuring all coroutines are properly awaited.

Can it help reduce test code duplication?

Absolutely. The skill identifies repetitive test logic and recommends using @pytest.mark.parametrize to streamline your test suite.

How does it improve the accuracy of mocks?

It verifies that the patch() function targets the correct location where the dependency is used rather than where it is defined, and ensures call tracking assertions are robust.

Pytest Code Review

Name: Pytest Code Review
Author: existential-birds

byexistential-birds

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Security & Testing

Audits Python test suites to ensure robust async patterns, efficient fixture usage, and accurate mocking implementation.

About

Pytest Code Review is a specialized capability for Claude Code designed to elevate the quality of Python testing workflows. It provides deep analysis of test files to identify common pitfalls in asynchronous testing, optimizes fixture scoping and cleanup in conftest.py, and ensures that mocking is applied correctly at the point of use. By enforcing DRY patterns through parametrization and verifying test isolation, this skill helps developers maintain high-performance, reliable, and maintainable test suites for complex Python applications.

Key Features

DRY pattern enforcement through @pytest.mark.parametrize recommendations
14 GitHub stars
Precise mocking audits for correct patch locations and call tracking
Comprehensive async testing validation for AsyncMock and await patterns
Automated checks for test isolation and shared mutable state issues
Fixture optimization including scope management and yield cleanup verification

Use Cases

Refactoring legacy Python test suites to use modern async/await patterns
Reviewing pull requests to ensure test isolation and proper fixture scoping
Reducing test code duplication by implementing pytest parametrization

About

Key Features

DRY pattern enforcement through @pytest.mark.parametrize recommendations
14 GitHub stars
Precise mocking audits for correct patch locations and call tracking
Comprehensive async testing validation for AsyncMock and await patterns
Automated checks for test isolation and shared mutable state issues
Fixture optimization including scope management and yield cleanup verification

Use Cases

Refactoring legacy Python test suites to use modern async/await patterns
Reviewing pull requests to ensure test isolation and proper fixture scoping
Reducing test code duplication by implementing pytest parametrization