Agent-Skills.md

Agent Skills: Comprehensive Test Review

Use when reviewing test suites for coverage, isolation, mock usage, naming conventions, or completeness. Activates on "review test coverage", "audit test quality", or "check tests for completeness" requests. Performs thorough checklist-driven review covering test isolation, mock correctness, AAA pattern adherence, and naming standards.

UncategorizedID: Jamie-BitFlight/claude_skills/comprehensive-test-review

Repository

Jamie-BitFlight/claude_skills
Jamie-BitFlightLicense: MIT
6110

Install this agent skill to your local

pnpm dlx add-skill https://github.com/Jamie-BitFlight/claude_skills/tree/HEAD/plugins/python-engineering/skills/comprehensive-test-review

Skill Files

Browse the full folder contents for comprehensive-test-review.

Download Skill

Loading file tree…

plugins/python-engineering/skills/comprehensive-test-review/SKILL.md

Skill Metadata

Name
comprehensive-test-review
Description
Performs checklist-driven review of pytest test suites against coverage thresholds (80% line/branch minimum, 95% for critical paths), AAA pattern adherence, pytest-mock usage, test isolation, naming clarity, type hints, and flaky pattern detection. Use when auditing test quality before a release, reviewing coverage gaps, checking tests for completeness or best practices, or validating mocking standards. Accepts a test file or directory as input and outputs prioritized findings grouped by HIGH, MEDIUM, and LOW priority.

Comprehensive Test Review

Perform thorough test review for the specified test files or directories.

When to Use

  • Reviewing test coverage before a release
  • Auditing test quality after major refactoring
  • Checking tests for completeness and best practices
  • Identifying gaps in test suites

Testing Standards

Load and follow the standards in /python-engineering:standards-for-python-development when auditing against shared testing and quality rules. The checklist below summarizes this skill's focus; it does not replace those standards.

Coverage Requirements:

  • [ ] Minimum 80% line and branch coverage
  • [ ] Critical paths have 95%+ coverage
  • [ ] All public functions have at least one test
  • [ ] Edge cases are explicitly tested

Test Quality:

  • [ ] Tests follow AAA (Arrange-Act-Assert) pattern
  • [ ] Test names describe behavior, not implementation
  • [ ] Each test verifies one logical unit
  • [ ] Tests are isolated and independent

Mocking Standards:

  • [ ] Uses pytest-mock (MockerFixture), NOT unittest.mock
  • [ ] Mocks are scoped appropriately
  • [ ] No over-mocking of implementation details
  • [ ] External dependencies are properly stubbed

Type Safety:

  • [ ] All fixtures have complete type hints
  • [ ] Test functions have -> None return type
  • [ ] Using Python 3.11+ syntax (str | None, not Optional[str])

Additional Examination Points

Beyond the standard checklist:

  • Test Isolation: No shared state between tests
  • Mock Appropriateness: Mocking only external dependencies
  • Execution Time: Identifying slow tests for optimization
  • Flaky Patterns: Tests dependent on timing, order, or external state
  • Naming Clarity: Test names that explain intent and expected behavior

Analysis Process

  1. Gather test files in specified path
  2. Run coverage analysis with uv run pytest --cov
  3. Check each test against the standard checklist
  4. Identify gaps in coverage and quality
  5. Generate recommendations prioritized by impact

Output Format

Provide findings in this structure:

## Test Review Summary

### Coverage Analysis

- Overall: X%
- Critical modules: Y%
- Gaps identified: [list]

### Quality Issues

**HIGH Priority:**

- [Issue with location and fix]

**MEDIUM Priority:**

- [Issue with recommendation]

**LOW Priority:**

- [Minor improvements]

### Recommendations

1. [Prioritized action items]

Related Skills

  • python3-test-design: Use /python-engineering:python3-test-design for test architecture planning
  • python3-testing: Use python-engineering:python3-testing for test implementation patterns

Related Agent

For implementing test improvements, use the python-engineering:python-pytest-architect agent.