Pytest Test Architect

The problem

Writing tests often results in brittle suites that break during refactors because they target implementation details instead of behavior. Developers frequently miss critical edge cases and fail to verify that the system state remains intact after an error is raised.

What it does

• Generates a comprehensive test matrix covering the happy path, boundary conditions, error paths, and side effects.
• Builds production-grade pytest suites using the Arrange-Act-Assert (AAA) pattern and clean fixture architecture.
• Implements robust mocking strategies limited to system boundaries like HTTP, clocks, and third-party SDKs.
• Enforces state-preservation assertions to ensure failed operations do not corrupt data.
• Delivers runnable test files along with a coverage report and a list of identified code smells.

Frameworks & tools

Python, pytest, freezegun, monkeypatch, tmp_path.

Why this beats prompting it yourself

Standard prompts usually produce shallow tests that only check the happy path. This skill enforces a disciplined architectural approach to testing, ensuring every public method is exercised against a four-category matrix and that fixtures are composed rather than duplicated.

Use cases

• Generating a complete test suite for a new Python module or class.
• Increasing test coverage for legacy code by identifying unhandled boundary conditions.
• Refactoring brittle mocks into stable, behavior-based assertions.
• Auditing existing codebases for "testability" and identifying hidden I/O or state issues.

Known limitations

Requires the environment to have necessary dependencies installed to verify the tests via execution. Prefers fakes over MagicMock for complex interfaces, which may require manual implementation of the fake if not provided.