Create fast, modern Python APIs using FastAPI with async/await support, automatic API documentation, type validation using Pydantic, dependency injection, JWT authentication, and SQLAlchemy ORM integration.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfastapi-developmentExecute the skills CLI command in your project's root directory to begin installation:
Fetches fastapi-development from aj-geddes/useful-ai-prompts and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate fastapi-development. Access via /fastapi-development in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create fast, modern Python APIs using FastAPI with async/await support, automatic API documentation, type validation using Pydantic, dependency injection, JWT authentication, and SQLAlchemy ORM integration.
Minimal working example:
# main.py
from fastapi import FastAPI, HTTPException, status
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
import logging
# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Create FastAPI instance
app = FastAPI(
title="API Service",
description="A modern FastAPI application",
version="1.0.0",
docs_url="/api/docs",
openapi_url="/api/openapi.json"
)
# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=["http://localhost:3000"],
allow_credentials=True,
allow_methods=["*"],
// ... (see reference guides for full implementation)
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| FastAPI Application Setup | FastAPI Application Setup |
| Pydantic Models for Validation | Pydantic Models for Validation |
| Async Database Models and Queries | Async Database Models and Queries |
| Security and JWT Authentication | Security and JWT Authentication |
| Service Layer for Business Logic | Service Layer for Business Logic |
| API Routes with Async Endpoints | API Routes with Async Endpoints |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Keeps context tight: fastapi-development is the kind of skill you can hand to a new teammate without a long onboarding doc.
fastapi-development reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend fastapi-development for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for fastapi-development matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for fastapi-development matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
fastapi-development has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
fastapi-development fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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