Pytest Code Review

The pytest-code-review skill enables AI agents to automatically analyze Python test files for quality, coverage, and adherence to best practices using the Beagle framework. It provides immediate feedback on test structure, naming conventions, and assertion logic to ensure robust backend testing suites.

When to use it

• Before merging pull requests that introduce new unit or integration tests.
• When refactoring existing test code to improve readability and maintainability.
• To validate that new features have corresponding test coverage before deployment.
• During code reviews to catch flaky tests or missing edge cases early in the development cycle.

Key capabilities

• Automated analysis of Python pytest files for structural integrity.
• Detection of common anti-patterns and naming convention violations.
• Evaluation of assertion logic quality within test functions.
• Integration with the Beagle AI agent ecosystem for backend workflows.

Example prompts

• "Run a code review on my new test_user_service.py file to check for best practices."
• "Analyze these failing tests and suggest improvements to the assertions."
• "Review the test coverage of my latest feature implementation using pytest standards."

Tips & gotchas

Ensure your project has pytest installed and configured correctly before invoking this skill. The agent focuses on code quality rather than execution results, so it may not flag runtime errors unless they are part of the static analysis context.