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Found 150 Skills
Guide Test-Driven Development workflow (Red-Green-Refactor) for new features, bug fixes, and refactoring. Identifies test improvement opportunities and applies pytest best practices. Use when writing tests, implementing features, or following TDD methodology. **PROACTIVE ACTIVATION**: Auto-invoke when implementing features or fixing bugs in projects with test infrastructure (pytest files, tests/ directory). **DETECTION**: Check for tests/ directory, pytest.ini, pyproject.toml with pytest config, or test files. **USE CASES**: Writing production code, fixing bugs, adding features, legacy code characterization.
Test-driven development workflow enforcement for Python and React projects. Use when the user requests TDD, test-first development, or red-green-refactor methodology. Enforces strict cycle: write ONE failing test -> implement minimum code to pass -> refactor while green -> repeat. Applies to both backend (pytest) and frontend (Testing Library). Changes agent behavior to write tests before code. Does NOT provide testing patterns (use pytest-patterns or react-testing-patterns for how to write tests).
Grey Haven's comprehensive testing strategy - Vitest unit/integration/e2e for TypeScript, pytest markers for Python, >80% coverage requirement, fixture patterns, and Doppler for test environments. Use when writing tests, setting up test infrastructure, running tests, debugging test failures, improving coverage, configuring CI/CD, or when user mentions 'test', 'testing', 'pytest', 'vitest', 'coverage', 'TDD', 'test-driven development', 'unit test', 'integration test', 'e2e', 'end-to-end', 'test fixtures', 'mocking', 'test setup', 'CI testing'.
testcontainers-python specialist. Covers all container modules (PostgreSQL, MySQL, MongoDB, Redis, Kafka, RabbitMQ, MinIO, Elasticsearch, LocalStack), GenericContainer, wait strategies, Docker Compose, networks, pytest fixtures, and CI/CD integration. USE WHEN: user mentions "testcontainers", "docker in tests", "real database in tests", "test with real postgres/redis/kafka", asks about container fixtures or Docker-based testing. DO NOT USE FOR: Spring Boot testcontainers (Java) - use `spring-boot-integration`; Mocking HTTP - use `fastapi-testing`; Pure pytest patterns - use `pytest`
Diagnose and fix failing pytest tests in the pplx-sdk project, following existing test patterns and conventions.
Generate pytest test cases for Python functions and classes
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.
Sets up async tests with proper fixtures and mocks using pytest-asyncio patterns. Use when testing async functions, creating async fixtures, mocking async services, or handling async context managers. Covers @pytest_asyncio.fixture, AsyncMock with side_effect, async generator fixtures (yield), and testing async context managers. Works with Python async/await patterns, pytest-asyncio, and unittest.mock.AsyncMock.
Review generated or changed test code against universal testing rules before it ships. Best used reactively after an agent writes, edits, generates, or refactors tests, before presenting, committing, or merging them. Use for pytest (test_*.py, *_test.py), PHPUnit/Pest (*Test.php), Jest/Vitest (*.test.ts, *.spec.js), Go (*_test.go), files under tests/, __tests__/, or spec/, and review requests like 'write tests for X', 'add tests', 'test this', 'review these tests', or PR diffs containing tests. Can also guide test writing when explicitly invoked before the work. This skill is the quality gate that prevents AI-generated test bloat.
Sets up Python development environment using UV for fast dependency management. Configures virtual environment, dependencies, testing (pytest), linting/formatting (ruff), and type checking (mypy). ALWAYS use UV - NEVER use pip directly. Use when starting work on Python projects, after cloning Python repositories, setting up CI/CD for Python, or troubleshooting Python environment issues.
Work with the Inpoxia repository's local tools and workflows for CLI usage, GraphMail library changes, and quality checks. Use when tasks involve running or updating `inpoxia` commands, modifying files under `src/inpoxia/**`, validating behavior with `pytest`, or enforcing style/type checks with `ruff` and `pyright`.
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.