Skills matching the name, description or GitHub author.
Build Python APIs with FastAPI, Pydantic v2, and SQLAlchemy 2.0 async. Covers project structure, JWT auth, validation, and database integration with uv package manager. Prevents 7 documented errors. Use when:...
Comprehensive backend development skill for building scalable backend systems using NodeJS, Express, Go, Python, Postgres, GraphQL, REST APIs. Includes API scaffolding, database optimization, security implement...
Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python app...
Server-specific best practices for FastAPI, Celery, and Pydantic. Extends python-skills with framework-specific patterns.
FastAPI with Supabase and SQLAlchemy/SQLModel
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke for async SQLAlchemy, JWT authentication, WebSockets, OpenAPI documentation.
Python JSON parsing best practices covering performance optimization (orjson/msgspec), handling large files (streaming/JSONL), security (injection prevention), and advanced querying (JSONPath/JMESPath). Use whe...
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization,...
Use when building FastAPI applications, implementing async endpoints, setting up Pydantic schemas, working with SQLAlchemy, or writing pytest tests for Python backend services.
Comprehensive backend development skill for building scalable backend systems using Python (FastAPI), Postgres, Redis, and more. Includes API design, database optimization, security implementation, and performa...
Converts JSON data snippets into Python Pydantic data models.
Async/await patterns for FastAPI and SQLAlchemy. Use when working with async code, database sessions, concurrent operations, or debugging async issues in Python.
Data validation and settings management using Python type annotations with Pydantic v2
Use when designing RESTful API endpoints in FastAPI or Python projects. Triggers for: creating GET/POST/PUT/DELETE endpoints, request validation with Pydantic, response formatting with JSON schemas, status code...
Use when creating FastAPI backend applications - route handlers, dependencies, CORS config, or Pydantic models. NOT when frontend logic, non-Python backends, or unrelated server-side code. Triggers: "FastAPI",...
Modern API development patterns for building high-performance, scalable web services. Expert in async/await patterns, REST/GraphQL APIs, middleware, error handling, rate limiting, OpenAPI documentation, testing...
Automatically generate and execute Python test scripts from OpenAPI specifications and GraphQL schemas with enhanced features
Python FastAPI development with uv package manager, modular project structure, SQLAlchemy ORM, and production-ready patterns.
FastAPI web framework patterns. Triggers on: fastapi, api endpoint, dependency injection, pydantic model, openapi, swagger, starlette, async api, rest api, uvicorn.
FastAPI 2026 advanced patterns including lifespan, dependencies, middleware, and Pydantic settings. Use when configuring FastAPI lifespan events, creating dependency injection, building Starlette middleware, or...
Strawberry GraphQL library for Python with FastAPI integration, type-safe resolvers, DataLoader patterns, and subscriptions. Use when building GraphQL APIs with Python, implementing real-time features, or creat...
Build high-performance FastAPI applications with async routes, validation, dependency injection, security, and automatic API documentation. Use when developing modern Python APIs with async support, automatic O...
Use when designing APIs, Architecture, Security, or Scalability for Node, Python, Go, or Java backend systems.
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.