pytest-code-review
Claude Code plugin for code review skills and verification workflows. Python, Go, React, FastAPI, BubbleTea, and AI frameworks (Pydantic AI, LangGraph, Vercel AI SDK).
15 stars3 forksUpdated Jan 24, 2026
npx skills add https://github.com/existential-birds/beagle --skill pytest-code-reviewSKILL.md
Pytest Code Review
Quick Reference
| Issue Type | Reference |
|---|---|
| async def test_*, AsyncMock, await patterns | references/async-testing.md |
| conftest.py, factory fixtures, scope, cleanup | references/fixtures.md |
| @pytest.mark.parametrize, DRY patterns | references/parametrize.md |
| AsyncMock tracking, patch patterns, when to mock | references/mocking.md |
Review Checklist
- Test functions are
async def test_*for async code under test - AsyncMock used for async dependencies, not Mock
- All async mocks and coroutines are awaited
- Fixtures in conftest.py for shared setup
- Fixture scope appropriate (function, class, module, session)
- Yield fixtures have proper cleanup in finally block
- @pytest.mark.parametrize for similar test cases
- No duplicated test logic across multiple test functions
- Mocks track calls properly (assert_called_once_with)
- patch() targets correct location (where used, not defined)
- No mocking of internals that should be tested
- Test isolation (no shared mutable state between tests)
When to Load References
- Reviewing async test functions → async-testing.md
- Reviewing fixtures or conftest.py → fixtures.md
- Reviewing similar test cases → parametrize.md
- Reviewing mocks and patches → mocking.md
Review Questions
- Are all async functions tested with async def test_*?
- Are fixtures properly scoped with appropriate cleanup?
- Can similar test cases be parametrized to reduce duplication?
- Are mocks tracking calls and used at the right locations?
Repository Stats
Stars15
Forks3
LicenseMIT License