Pytest

What it does

This skill enables AI agents to execute pytest commands directly within their environment, allowing them to run test suites and verify code correctness. It streamlines the testing workflow by removing the need for manual command-line invocation during development cycles.

When to use it

• Automatically validate logic changes before committing code to a repository.
• Run regression tests after an AI agent generates or modifies a function.
• Verify that new dependencies do not break existing test cases.
• Execute full test suites as part of a continuous integration simulation.

Key capabilities

• Runs pytest commands natively in the agent's shell context.
• Executes specific test files or individual test functions.
• Reports pass/fail status and output logs directly to the conversation.

Example prompts

• "Run all tests in the tests/ directory and summarize any failures."
• "Execute the unit tests for the new user authentication module I just wrote."
• "Run pytest with verbose output to see detailed error messages for the failing case."

Tips & gotchas

Ensure your project has a valid pytest.ini or pyproject.toml configuration file, as the agent relies on standard project structures to locate tests. If tests fail due to missing environment variables, provide those details in the prompt context before re-running.