pytest
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers).
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Pytest testing patterns for Python. Trigger: When writing or refactoring pytest tests (fixtures, mocking, parametrize, markers).
Use when implementing JWT authentication in FastAPI or Python projects. Triggers for: token generation, verification middleware, current user extraction, access token creation, token decoding, or role-based aut...
Comprehensive Python development expertise covering modern best practices, type hints, FastAPI web development, async/await, testing, and performance optimization. Use when working on Python projects requiring...
Neo4j driver best practices for Python. Use when working with Neo4j connections, Cypher queries, transactions, or GraphRAG implementations.
Guia para criar servidores MCP (Model Context Protocol) de alta qualidade que permitem que LLMs interajam com serviços externos através de ferramentas bem projetadas. Use ao construir servidores MCP para integr...
Build high-performance Python APIs with FastAPI. Covers async endpoints, dependency injection, Pydantic validation, OpenAPI auto-generation, OAuth2/JWT authentication, and database integration. Use when buildin...
自动进化型 CR 专家。通过 Python 脚本实现确切的项目管理与双存储日志归档。它不仅指出通用错误,更致力于通过分析存量代码来维护项目的"潜规则"一致性。
Create a plan and issues for implementation of a production-ready Python project with proper structure, tooling, and best practices.
Automate Python project Docker Hub deployments with optimized multi-stage builds, CI/CD pipelines, and security best practices. This skill should be used when users ask to containerize Python apps, build Docker...
Idiomatisches Python für Backend-Entwicklung mit Typ-Annotationen, Error Handling und Async.
Création et modification des outils smolagents Python de ce projet. Utilise ce skill pour tout ce qui touche à agent/tools/, agent/main.py, agent/gradio_app.py, et les modèles LiteLLM/Ollama/Z.ai.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.