tdd-python

Python Test-Driven Development expertise with pytest, strict red-green-refactor methodology, domain-first modeling (DDD), principled DRY discipline, FastAPI testing patterns, and Pydantic model testing. Use when implementing Python features with TDD, writing pytest tests, testing FastAPI endpoints, developing with test-first approach, modeling domain concepts, refactoring duplication, or when user mentions 'Python TDD', 'pytest', 'FastAPI testing', 'red-green-refactor', 'Python unit tests', 'test-driven Python', 'domain modeling', 'value object', 'ubiquitous language', 'DRY', or 'Python test coverage'.

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仓库: greyhaven-ai/claude-code-config
最近来源活动: 2026年4月18日 01:43
检测到的 SKILL.md 语言: 英语
星标: 30
Forks: 5

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SKILL.md

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name: tdd-python
description: Python Test-Driven Development expertise with pytest, strict red-green-refactor methodology, domain-first modeling (DDD), principled DRY discipline, FastAPI testing patterns, and Pydantic model testing. Use when implementing Python features with TDD, writing pytest tests, testing FastAPI endpoints, developing with test-first approach, modeling domain concepts, refactoring duplication, or when user mentions 'Python TDD', 'pytest', 'FastAPI testing', 'red-green-refactor', 'Python unit tests', 'test-driven Python', 'domain modeling', 'value object', 'ubiquitous language', 'DRY', or 'Python test coverage'.
skills: ["code-style","api-design-standards","test-generation"]
allowed-tools: ["Read","Write","MultiEdit","Bash","Grep","Glob","TodoWrite"]

# TDD Python Skill Python Test-Driven Development following strict red-green-refactor cycle with pytest — sharpened by **DDD at Red** (model the domain first) and **DRY at Refactor** (deduplicate same-concept repetition only). ## Description Systematic Python implementation using TDD methodology. Tests are written first and drive design; domain vocabulary drives the tests; duplication is removed only when the *same concept* repeats, not when syntax coincidentally looks alike. ## Discipline Layering - **Before Red — Model the Domain**: Name the entity, value object, or aggregate in the business's language. Decide entity vs. value object. Reject primitive obsession — wrap `str`/`int` in `EmailAddress`, `Money`, `NewType`, or `pydantic.BaseModel` when they carry rules. Keep domain logic out of FastAPI routes. - **Red**: Write a failing test. Name it in domain terms (`test_rejects_refund_when_amount_exceeds_daily_limit`) — never mechanical (`test_returns_false`). - **Green**: Minimal code to pass. No speculative abstractions. - **Refactor — DRY with discipline**: Deduplicate only when the *same domain concept* appears ≥3 times with the same meaning. Three similar lines beats a premature abstraction. Promote recurring primitives to value objects. When uncertain, inline. ## What's Included - **Examples**: Python TDD cycles, FastAPI TDD, Pydantic model TDD, value-object modeling - **Reference**: pytest patterns, Python testing best practices, branded-type idioms (`NewType`, `frozen=True`) - **Templates**: pytest templates, TDD workflows ## Use When - Implementing Python features with TDD - Modeling domain concepts (entities, value objects, aggregates) - FastAPI endpoint development (keeping domain rules out of routes) - Pydantic model development - Refactoring duplication after a green test ## Related Agents - `tdd-python-implementer` **Skill Version**: 1.1

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code-quality-analysis

Multi-mode code quality analysis covering security reviews (OWASP Top 10), clarity refactoring (readability rules), synthesis analysis (cross-file issues), and DDD/DRY lenses (flags mechanical naming, primitive obsession, domain rules leaking into infrastructure, and premature abstractions via the three-occurrences-same-concept rule). Supports team-mode parallel analysis when invoked from quality-pipeline. Use when reviewing code for security vulnerabilities, improving code readability, conducting quality audits, pre-deployment checks, or when user mentions 'code quality', 'code review', 'security review', 'refactoring', 'code smell', 'OWASP', 'code clarity', 'primitive obsession', 'value object', 'ubiquitous language', 'DRY', 'premature abstraction', or 'quality audit'.

2026-04-19

performance-optimization

Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'.

2026-04-19

api-design-standards

Design RESTful APIs following Grey Haven standards - FastAPI routes, Pydantic schemas, HTTP status codes, pagination, filtering, error responses, OpenAPI docs, and multi-tenant patterns. Use when creating API endpoints, designing REST resources, implementing server functions, configuring FastAPI, writing Pydantic schemas, setting up error handling, implementing pagination, or when user mentions 'API', 'endpoint', 'REST', 'FastAPI', 'Pydantic', 'server function', 'OpenAPI', 'pagination', 'validation', 'error handling', 'rate limiting', 'CORS', or 'authentication'.

2026-04-19

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