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Pytest code review

Skill existential-birds/beagle/plugins/beagle-python/skills/pytest-code-review

Agent Skills marketplace: framework-aware skills for code review, documentation, test-plan generation, AI-writing detection, architectural analysis, and git workflows — for Python, Go, Rust, Elixir, React, Remix, and iOS/Swift. Works with Claude Code, Codex, and any agent that supports Agent Skills.

Install
npx -y skills add existential-birds/beagle --skill pytest-code-review

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What its author says it does

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Reviews pytest test code for async patterns, fixtures, parametrize, and mocking. Use when reviewing test_*.py files, checking async test functions, fixture usage, or mock patterns.

SKILL.md

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Pytest Code Review

Quick Reference

Issue TypeReference
async def test_*, AsyncMock, await patternsreferences/async-testing.md
conftest.py, factory fixtures, scope, cleanupreferences/fixtures.md
@pytest.mark.parametrize, DRY patternsreferences/parametrize.md
AsyncMock tracking, patch patterns, when to mockreferences/mocking.md

Review gates

Work in order. Do not assert pytest-specific problems until each applicable gate passes.

  1. Scoped filesPass when: You list every test_*.py and any conftest.py you will cite; no findings for files outside that list.
  2. Async vs syncPass when: Per scoped file, you note whether it uses async def test_* / await; if yes, open references/async-testing.md before criticizing async usage.
  3. FixturesPass when: If shared setup matters, you name the conftest.py path(s) or state none; for yield fixtures, confirm cleanup exists before claiming resource leaks.
  4. patch / mocksPass when: For any patch or mock critique, you give the import path where the symbol is used (call site), or mark N/A; open references/mocking.md when mocking is central to the review.
  5. FindingsPass when: Each finding includes a file path and line(s) or test node id, not a generic rule restatement.

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

  1. Are all async functions tested with async def test_*?
  2. Are fixtures properly scoped with appropriate cleanup?
  3. Can similar test cases be parametrized to reduce duplication?
  4. Are mocks tracking calls and used at the right locations?

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