pytest-code-review
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.
Best use case
pytest-code-review is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using pytest-code-review should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pytest-code-review/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pytest-code-review Compares
| Feature / Agent | pytest-code-review | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Pytest Code Review ## Quick Reference | Issue Type | Reference | |------------|-----------| | async def test_*, AsyncMock, await patterns | [references/async-testing.md](references/async-testing.md) | | conftest.py, factory fixtures, scope, cleanup | [references/fixtures.md](references/fixtures.md) | | @pytest.mark.parametrize, DRY patterns | [references/parametrize.md](references/parametrize.md) | | AsyncMock tracking, patch patterns, when to mock | [references/mocking.md](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 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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