---

name: testing-quality-standards description: Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets. globs: "**/test_*.py" alwaysApply: false category: infrastructure tags:

• testing
• quality
• standards
• metrics dependencies: [] estimated_tokens: 400 provides: patterns:
  • coverage-thresholds
  • quality-metrics
  • anti-patterns
  • content-assertion-levels modules:
• modules/anti-patterns.md
• modules/best-practices.md
• modules/content-assertion-levels.md model_hint: standard

---

Testing Quality Standards

Shared quality standards and metrics for testing across all plugins in the Claude Night Market ecosystem.

When To Use

• Establishing test quality gates and coverage targets
• Validating test suite against quality standards

When NOT To Use

• Exploratory testing or spike work
• Projects with established quality gates that meet requirements

Coverage Thresholds

Level	Coverage	Use Case
Minimum	60%	Legacy code
Standard	80%	Normal development
High	90%	Critical systems
detailed	95%+	Safety-critical

Quality Metrics

Structure

• Clear test organization
• Meaningful test names
• Proper setup/teardown
• Isolated test cases

Coverage

• Critical paths covered
• Edge cases tested
• Error conditions handled
• Integration points verified

Maintainability

• DRY test code
• Reusable fixtures
• Clear assertions
• Minimal mocking

Reliability

• No flaky tests
• Deterministic execution
• No order dependencies
• Fast feedback loop

Detailed Topics

For implementation patterns and examples:

• Anti-Patterns - Common testing mistakes with before/after examples
• Best Practices - Core testing principles and exit criteria
• Content Assertion Levels - L1/L2/L3 taxonomy for testing LLM-interpreted markdown files

Integration with Plugin Testing

This skill provides foundational standards referenced by:

• pensive:test-review - Uses coverage thresholds and quality metrics
• parseltongue:python-testing - Uses anti-patterns and best practices
• sanctum:test-* - Uses quality checklist and content assertion levels for test validation
• imbue:proof-of-work - Uses content assertion levels to enforce Iron Law on execution markdown

Reference in your skill's frontmatter:

dependencies: [leyline:testing-quality-standards]

Verification: Run pytest -v to verify tests pass.

Troubleshooting

Common Issues

Tests not discovered Ensure test files match pattern test_*.py or *_test.py. Run pytest --collect-only to verify.

Import errors Check that the module being tested is in PYTHONPATH or install with pip install -e .

Async tests failing Install pytest-asyncio and decorate test functions with @pytest.mark.asyncio

Exit Criteria

• Coverage threshold met for the project tier: 60% minimum for legacy code, 80% for normal development, 90% for critical systems, 95%+ for safety-critical; measured with pytest --cov and threshold enforced in pyproject.toml
• All four quality metric checklists pass: Structure (clear organization, meaningful names, setup/teardown, isolation), Coverage (critical paths, edge cases, error conditions, integration points), Maintainability (DRY fixtures, clear assertions, minimal mocking), Reliability (no flaky tests, deterministic execution, no order dependencies)
• Test files match discovery pattern test_*.py or *_test.py confirmed by pytest --collect-only returning no errors
• No snapshot tests present on non-deterministic output (hash maps, timestamps, UUIDs); any found flagged as anti-patterns per modules/anti-patterns.md