Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
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Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Shared quality standards and metrics for testing across all plugins in the Claude Night Market ecosystem.
| Level | Coverage | Use Case |
|---|---|---|
| Minimum | 60% | Legacy code |
| Standard | 80% | Normal development |
| High | 90% | Critical systems |
| detailed | 95%+ | Safety-critical |
For implementation patterns and examples:
This skill provides foundational standards referenced by:
pensive:test-review - Uses coverage thresholds and quality metricsparseltongue:python-testing - Uses anti-patterns and best practicessanctum:test-* - Uses quality checklist and content assertion levels for test validationimbue:proof-of-work - Uses content assertion levels to enforce Iron Law on execution markdownReference in your skill's frontmatter:
dependencies: [leyline:testing-quality-standards]
Verification: Run pytest -v to verify tests pass.
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
pytest --cov and threshold enforced in pyproject.tomltest_*.py or *_test.py
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Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.
The English summary is being prepared. Showing the original description.
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
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Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.
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Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
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Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
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Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
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