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Testing & QA
Unit tests, integration tests, E2E, QA, validation, and test automation
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- E2e TestVerify cargo-coupling CLI behavior end to end using disposable Rust fixtures.Votes: 0GitHub stars: 109
- AuditUse when the primary outcome is comparing documentation claims with implementation evidence, synchronizing docs from verified changes, or freshness review, including drift, missing coverage, stale claims, and post-change updates.Votes: 0GitHub stars: 67
- Evidence First DebuggingUse when debugging software, investigating incidents, diagnosing flaky tests, or analyzing performance regressions — enforces structured observation recording with evidence IDs, causality validation, and verification gates to prevent correlation-causation pollution. Use when an agent might otherwise summarize or speculate instead of reporting observed evidence.Votes: 0GitHub stars: 67
- Test Failure MindsetInvestigate pytest failures without treating tests or implementation as automatic authority. Use when diagnosing regressions, debugging test errors, or deciding whether to fix a test or code; trace the contract, product, fixture, and observation before choosing an evidence-backed correction.Votes: 0GitHub stars: 67
- SnakepolishUse when independently assessing how bounded Python code could accomplish the same behavior with less maintained code, more Pythonic design, newer language/stdlib capabilities, or well-maintained ecosystem libraries.Votes: 0GitHub stars: 67
- Python3 TypingAuto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 64...Votes: 0GitHub stars: 67
- Python3 TestingPytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based strategies.Votes: 0GitHub stars: 67
- Python3 Test DesignGuides pytest test architecture for Python 3.11+ using behavioral contracts, risk, and maintenance-adjusted value. Use when choosing unit/integration/property/e2e boundaries, fixture strategy, coverage measurement, or mutation testing. Preserves existing project gates but does not invent test-pyramid ratios, coverage percentages, mutation-score targets, or tests for implementation detail.Votes: 0GitHub stars: 67
- Python3 TddUse when a Python task explicitly requires test-driven development, tests-first implementation, or a red-green-refactor workflow.Votes: 0GitHub stars: 67
- Pre CommitConfigures and runs git hooks with prek (or the pre-commit it replaces — same `.pre-commit-config.yaml`). Use when adding or troubleshooting git hooks, writing a `prepare-commit-msg` or `commit-msg` stage hook, or authoring `.pre-commit-hooks.yaml` for hook distribution.Votes: 0GitHub stars: 67
- DebugUse when diagnosing a Python traceback, failing test, intermittent failure, integration defect, or other unexpected runtime behavior.Votes: 0GitHub stars: 67
- Create Feature TaskUse when creating a new feature development task — scaffolds a structured task file at .claude/tasks/{feature-name}.md with phased breakdown (Design, Implementation, Testing, Documentation), acceptance criteria, context preservation, and TaskCreate tracking. Activates on "create a feature task", "set up development tracking", "plan a feature implementation", or when preparing work for python-cli-architect or python-pytest-architect agents.Votes: 0GitHub stars: 67
- Evaluate And Tighten SkillsCompatibility router for semantic skill tightening. Delegate goal recovery, authority, semantic conservation, evaluation contracts, and instruction optimization to Skill Lapidary rather than duplicating that system in Plugin Creator.Votes: 0GitHub stars: 67
- Perl ValidateThis skill should be used when the user asks to "validate Perl script", "check Perl syntax", "verify Perl code", "/perl-validate", or mentions script validation, compile check, security review, or best practice compliance for Perl code.Votes: 0GitHub stars: 67
- Perl TestingThis skill should be used when the user asks to write Perl tests, test Perl code, use Test More, run prove, create test suite, mock Perl, or mentions Perl testing, TAP, Test Class, Test Deep, or test-driven development in Perl.Votes: 0GitHub stars: 67
- Fastmcp Python TestsWrite and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.Votes: 0GitHub stars: 67
- Verify DoneRigorous self-assessment checklist before marking any task as complete. Use when about to claim task completion, before final commit, when user asks "is it done?", or when transitioning from implementation to reporting. Prevents premature completion claims by requiring evidence for every assertion.Votes: 0GitHub stars: 67
- Validation ProtocolScientific validation protocol for verifying fixes work through observation, not assumption. Use when claiming a bug fix, code change, refactoring, or implementation is complete — enforces reproduce-broken-state then define-success-criteria then apply-fix then verify-outcome. Success means observing intended behavior, not absence of errors.Votes: 0GitHub stars: 67
- Test Failure MindsetUse when investigating failing tests or deciding whether to change the test or product. Validate test expectations against authoritative intent, trace product and test boundaries, and require evidence for the correction rather than automatic code fixes or test dismissal.Votes: 0GitHub stars: 67
- PlanningUse when Stage 1 Discovery is complete and design must begin — transforms the ARTIFACT:DISCOVERY into an actionable ARTIFACT:PLAN via RT-ICA prerequisite verification. Produces approach, components, success criteria, acceptance tests, and risks. Blocks on missing prerequisites before design proceeds.Votes: 0GitHub stars: 67
- Multi Perspective ReviewUse when a diff needs four parallel perspective reviewers (Security, Performance, Quality, Accessibility). Creates an ephemeral SAM plan, collects structured verdicts, synthesizes them into one deduplicated cross-referenced punch list, prints one summary line per perspective, and exits non-zero if any perspective returns REJECT. SKIP is a passing outcome.Votes: 0GitHub stars: 67
- Final VerificationCertifies that a feature achieves its original objectives via goal-backward verification (SAM Stage 7). Use when all tasks pass forensic review — starts from expected outcomes, works backwards to verify each was achieved, and returns CERTIFIED or NOT_CERTIFIED with specific gaps.Votes: 0GitHub stars: 67
- Complete ImplementationUse when all tasks for a feature are marked COMPLETE — runs holistic quality gates including code review, feature verification, integration check, documentation drift audit and update, and context refinement. Creates follow-up plans when issues are found.Votes: 0GitHub stars: 67
- Code Review PythonProvides Python-specific code review rules for the dh code-reviewer agent. Activates on pyproject.toml or *.py file detection — enforces uv, ruff, ty, pytest, type annotation, error handling, and Python 3.11+ idioms including pathlib, match statements, and modern union syntax.Votes: 0GitHub stars: 67