菜单
Applies TDD: failing test first, smallest passing change, refactor under test protection. Use when adding behaviour, fixing defects, or refactoring with executable expectations.
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基于 SOC 职业分类
Governs AI models through inventory, purpose, risk tier, approval, monitoring, drift, kill-switch and retirement. Use when introducing, changing or operating models in production or agent workflows.
Applies an Asimov-inspired hierarchy of AI safety laws when material AI or instruction risk is present. Use when harm, unlawful requests, authority conflicts, or safety trade-offs need an explicit law hierarchy. Also known as apply_laws_of_AI.
Use when implementing input validation, output filtering, tool restrictions, policy enforcement, secure coding controls, destructive-tool guardrails, approval gates, or safe agent behaviour.
Use when starting a session or deciding which local skill applies; acts as the meta-skill for discovering and loading the smallest relevant skill.
Use when measuring coding-agent quality, RAG evaluation, regression risk, latency, cost, reliability, safety, or production performance for agent systems.
Designs ontology-driven knowledge graphs for explainable KG-RAG. Use when modelling semantic graphs, ontologies, or graph schemas for retrieval.
| name | tdd-practice |
| description | Applies TDD: failing test first, smallest passing change, refactor under test protection. Use when adding behaviour, fixing defects, or refactoring with executable expectations. |
Use this skill when adding behaviour, fixing a defect, refactoring risky code, creating library functions, implementing business rules, or improving code where expected behaviour can be specified with executable tests.
Drive implementation from executable expectations. Produce code that is correct, minimal, refactorable and protected by targeted tests.
For Python projects, pytest recommends isolated development environments, package installation in editable mode for development, and conventional discovery using test_*.py or *_test.py. New projects should prefer a src/ layout with --import-mode=importlib to avoid surprising import-path behaviour. When a repository uses pyproject.toml, keep pytest configuration there or in a dedicated pytest config file and prefer strict options such as strict_config and strict_markers where compatible with the pinned pytest version.
Do not use python setup.py test or pytest-runner; pytest documents that setuptools test integration is deprecated and can bypass modern packaging/security mechanisms.
Source: pytest — Good Integration Practices.
code-review-and-quality — review after tests passreflection-and-verification — repair loop when checks failbdd-practice — acceptance scenarios for external behaviour