fastapi

What it does

This skill enables AI agents to build and deploy high-performance web APIs using Python's FastAPI framework. It handles automatic OpenAPI schema generation, dependency injection, and asynchronous request handling out of the box.

When to use it

• You need to create a REST or GraphQL API for an AI agent to interact with external services.
• Your application requires high concurrency and async support for I/O-bound tasks like database queries or HTTP calls.
• You want automatic interactive API documentation (Swagger UI) generated from your code definitions.
• You are building microservices that need type safety via Pydantic models for request/response validation.

Key capabilities

• Automatic OpenAPI schema generation and interactive docs
• Async support for high-performance I/O operations
• Built-in dependency injection system
• Request/Response validation using Pydantic
• Middleware integration for logging, CORS, and security
• Path operation decorators for defining endpoints

Example prompts

• "Create a FastAPI endpoint that accepts a user ID and returns their profile data from a mock database."
• "Generate a Python script with FastAPI to handle file uploads and return a processed image URL."
• "Set up a FastAPI server with CORS enabled and Swagger UI documentation for public access."

Tips & gotchas

Ensure you have Python 3.8+ installed, as FastAPI relies on modern async features. Always validate input data using Pydantic models to prevent injection attacks or malformed requests.