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Found 130 Skills
Automated test generation, review, and execution for pytest-based projects. Auto-activates on keywords test, coverage, pytest, unittest, integration test, e2e, performance, benchmark, security testing. Routes to specialized testing workflows based on user intent.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
Modern Python tooling best practices using uv, ruff, ty, and pytest. Mandates the Trail of Bits Python coding standards for project setup, dependency management, linting, type checking, and testing. Based on patterns from trailofbits/cookiecutter-python.
Develop Python applications using modern patterns, uv, functional-first design, and production-first practices. Use this whenever working with .py files, pyproject.toml, uv commands, pip/pip3, poetry, virtualenv/venv, inline script metadata, or Python tooling like pytest, mypy, ruff, asyncio, itertools, functools, or dataclasses. If the task involves running Python, managing Python dependencies, creating environments, or building Python packages, load this skill and prefer uv-oriented workflows.
Write comprehensive backend tests including unit tests, integration tests, and API tests. Use when testing REST APIs, database operations, authentication flows, or business logic. Handles Jest, Pytest, Mocha, testing strategies, mocking, and test coverage.
Comprehensive test automation specialist covering unit, integration, and E2E testing strategies. Expert in Jest, Vitest, Playwright, Cypress, pytest, and modern testing frameworks. Guides test pyramid design, coverage optimization, flaky test detection, and CI/CD integration. Activate on 'test strategy', 'unit tests', 'integration tests', 'E2E testing', 'test coverage', 'flaky tests', 'mocking', 'test fixtures', 'TDD', 'BDD', 'test automation'. NOT for manual QA processes, load/performance testing (use performance-engineer), or security testing (use security-auditor).
FastAPI framework mechanics and advanced patterns. Use when configuring middleware, creating dependency injection chains, implementing WebSocket endpoints, customizing OpenAPI documentation, setting up CORS, building authentication dependencies (JWT validation, role-based access), implementing background tasks, or managing application lifespan (startup/shutdown). Does NOT cover basic endpoint CRUD or repository/service patterns (use python-backend-expert) or testing (use pytest-patterns).
自动生成全面的测试套件，包括单元测试、集成测试和E2E测试，支持Jest、Vitest、pytest、xUnit等。
Integrate Open-Meteo Weather Forecast, Air Quality, and Geocoding APIs: query design, variable selection, timezone/timeformat/units, multi-location batching, and robust error handling. Keywords: Open-Meteo, /v1/forecast, /v1/air-quality, geocoding-api, hourly, daily, current, timezone=auto, timeformat=unixtime, models, WMO weather_code, CAMS, GeoNames, httpx, FastAPI, pytest.
FastAPI integration testing specialist. Covers synchronous TestClient, async httpx AsyncClient, dependency injection overrides, auth testing (JWT, OAuth2, API keys), WebSocket testing, file uploads, background tasks, middleware testing, and HTTP mocking with respx, responses, and pytest-httpserver. USE WHEN: user mentions "FastAPI test", "TestClient", "httpx async test", "dependency override test", "respx mock", asks about testing FastAPI endpoints, authentication in tests, or HTTP client mocking. DO NOT USE FOR: Django - use `pytest-django`; pytest internals - use `pytest`; Container infrastructure - use `testcontainers-python`
Set up performance benchmarks and CodSpeed harness for a project. Use this skill whenever the user wants to create benchmarks, add performance tests, set up CodSpeed, configure codspeed.yml, integrate a benchmarking framework (criterion, divan, pytest-benchmark, vitest bench, go test -bench, google benchmark), or when the user says 'add benchmarks', 'set up perf tests', 'create a benchmark', 'benchmark this', or wants to measure performance of their code for the first time. Also trigger when the optimize skill needs benchmarks that don't exist yet.
Python backend implementation patterns for FastAPI applications with SQLAlchemy 2.0, Pydantic v2, and async patterns. Use during the implementation phase when creating or modifying FastAPI endpoints, Pydantic models, SQLAlchemy models, service layers, or repository classes. Covers async session management, dependency injection via Depends(), layered error handling, and Alembic migrations. Does NOT cover testing (use pytest-patterns), deployment (use deployment-pipeline), or FastAPI framework mechanics like middleware and WebSockets (use fastapi-patterns).