fastapi-development▌
aj-geddes/useful-ai-prompts · updated Apr 23, 2026
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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.
FastAPI Development
Table of Contents
Overview
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.
When to Use
- Building high-performance Python REST APIs
- Creating async API endpoints
- Implementing automatic OpenAPI/Swagger documentation
- Leveraging Python type hints for validation
- Building microservices with async support
- Integrating Pydantic for data validation
Quick Start
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)
Reference Guides
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 |
Best Practices
✅ DO
- Use async/await for I/O operations
- Leverage Pydantic for validation
- Use dependency injection for services
- Implement proper error handling with HTTPException
- Use type hints for automatic OpenAPI documentation
- Create service layers for business logic
- Implement authentication on protected routes
- Use environment variables for configuration
- Return appropriate HTTP status codes
- Document endpoints with docstrings and tags
❌ DON'T
- Use synchronous database operations
- Trust user input without validation
- Store secrets in code
- Ignore type hints
- Return database models in responses
- Implement authentication in route handlers
- Use mutable default arguments
- Forget to validate query parameters
- Expose stack traces in production
How to use fastapi-development on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add fastapi-development
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches fastapi-development from GitHub repository aj-geddes/useful-ai-prompts and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate fastapi-development. Access the skill through slash commands (e.g., /fastapi-development) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ 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.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★31 reviews- ★★★★★Aditi Martin· Dec 28, 2024
Keeps context tight: fastapi-development is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ava Ghosh· Dec 24, 2024
fastapi-development reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aisha Abebe· Dec 12, 2024
I recommend fastapi-development for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ava Reddy· Nov 19, 2024
Registry listing for fastapi-development matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Advait Sharma· Nov 3, 2024
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yuki Johnson· Oct 22, 2024
Registry listing for fastapi-development matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ava Diallo· Oct 10, 2024
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Layla Li· Sep 17, 2024
fastapi-development has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yash Thakker· Sep 1, 2024
Useful defaults in fastapi-development — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Hassan Bansal· Sep 1, 2024
fastapi-development fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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