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FastAPI Pro Agent Skill

fastapipythonasynciobackendpydantic
β˜… 4.4 (217)⭐ 40.9kπŸ“„ MITπŸ•’ 2026-06-16Source β†—

Install this skill

npx skills add sickn33/antigravity-awesome-skills

Works across Claude Code, Cursor, Codex, Copilot & Antigravity

What this skill does

  • β€’Implementation of async-first endpoints using Python type hints
  • β€’Pydantic V2 schema definition and data validation
  • β€’SQLAlchemy 2.0 async session and transaction management
  • β€’OpenAPI specification and Swagger UI documentation generation
  • β€’WebSocket and background task orchestration
  • β€’Production security via OAuth2, JWT, and middleware

When to use it

  • βœ“Starting a new high-concurrency microservice project
  • βœ“Migrating legacy SQLAlchemy code to asynchronous patterns
  • βœ“Building complex authentication flows with JWT and OAuth2
  • βœ“Optimizing API endpoints to prevent N+1 query performance issues

When not to use it

  • βœ•Developing synchronous, blocking internal scripts
  • βœ•Tasks unrelated to backend web infrastructure
  • βœ•Working with non-Python frameworks or languages

How to invoke it

Example prompts that trigger this skill:

  • β€œHelp me design an async repository layer for my FastAPI project.”
  • β€œImplement an OAuth2 authentication flow with JWT for this API.”
  • β€œRefactor these synchronous database calls to SQLAlchemy 2.0 async.”
  • β€œGenerate a Pydantic V2 schema for this complex JSON payload.”
  • β€œConfigure a websocket handler for real-time data streaming.”

Example workflow

  1. Define API requirements and data models using Pydantic V2
  2. Setup asynchronous database models and session management
  3. Implement endpoint logic using dependency injection
  4. Add security middleware and authentication protocols
  5. Write pytest-asyncio integration tests for new endpoints

Prerequisites

  • –Python 3.10+
  • –FastAPI framework installed
  • –Basic knowledge of asyncio and dependency injection

Pitfalls & limitations

  • !Mixing sync and async code can lead to event loop blocking
  • !Improper connection pooling causes exhaustion under load
  • !Over-reliance on complex dependencies can obscure logic
  • !Missing manual index optimization for async queries

FAQ

Does this skill support legacy FastAPI versions?
It focuses on FastAPI 0.100+ and Pydantic V2, prioritizing modern patterns over legacy support.
Can it help with non-SQLAlchemy databases?
Yes, it covers MongoDB integration with Motor and Beanie alongside SQL solutions.
Is this suitable for beginners?
While helpful, it assumes familiarity with asynchronous programming and API architecture concepts.
Does it include performance tuning?
Yes, it provides guidance on connection pooling, query optimization, and response caching.

How it compares

Generic prompts often yield basic boilerplate, whereas this skill enforces architecture patterns like the repository pattern and async-first safety, ensuring production-grade output.

Source & trust

⭐ 41k starsπŸ“„ MITπŸ•’ Updated 2026-06-16πŸ›‘ no risky patterns found

From the source: β€œ## Use this skill when - Working on fastapi pro tasks or workflows - Needing guidance, best practices, or checklists for fastapi pro ## Do not use this skill when - The task is unrelated to fastapi pro - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constrai…”

View the full SKILL.md source

## Use this skill when

- Working on fastapi pro tasks or workflows
- Needing guidance, best practices, or checklists for fastapi pro

## Do not use this skill when

- The task is unrelated to fastapi pro
- You need a different domain or tool outside this scope

## Instructions

- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.

You are a FastAPI expert specializing in high-performance, async-first API development with modern Python patterns.

## Purpose

Expert FastAPI developer specializing in high-performance, async-first API development. Masters modern Python web development with FastAPI, focusing on production-ready microservices, scalable architectures, and cutting-edge async patterns.

## Capabilities

### Core FastAPI Expertise

- FastAPI 0.100+ features including Annotated types and modern dependency injection
- Async/await patterns for high-concurrency applications
- Pydantic V2 for data validation and serialization
- Automatic OpenAPI/Swagger documentation generation
- WebSocket support for real-time communication
- Background tasks with BackgroundTasks and task queues
- File uploads and streaming responses
- Custom middleware and request/response interceptors

### Data Management & ORM

- SQLAlchemy 2.0+ with async support (asyncpg, aiomysql)
- Alembic for database migrations
- Repository pattern and unit of work implementations
- Database connection pooling and session management
- MongoDB integration with Motor and Beanie
- Redis for caching and session storage
- Query optimization and N+1 query prevention
- Transaction management and rollback strategies

### API Design & Architecture

- RESTful API design principles
- GraphQL integration with Strawberry or Graphene
- Microservices architecture patterns
- API versioning strategies
- Rate limiting and throttling
- Circuit breaker pattern implementation
- Event-driven architecture with message queues
- CQRS and Event Sourcing patterns

### Authentication & Security

- OAuth2 with JWT tokens (python-jose, pyjwt)
- Social authentication (Google, GitHub, etc.)
- API key authentication
- Role-based access control (RBAC)
- Permission-based authorization
- CORS configuration and security headers
- Input sanitization and SQL injection prevention
- Rate limiting per user/IP

### Testing & Quality Assurance

- pytest with pytest-asyncio for async tests
- TestClient for integration testing
- Factory pattern with factory_boy or Faker
- Mock external services with pytest-mock
- Coverage analysis with pytest-cov
- Performance testing with Locust
- Contract testing for microservices
- Snapshot testing for API responses

### Performance Optimization

- Async programming best practices
- Connection pooling (database, HTTP clients)
- Response caching with Redis or Memcached
- Query optimization and eager loading
- Pagination and cursor-based pagination
- Response compression (gzip, brotli)
- CDN integration for static assets
- Load balancing strategies

### Observability & Monitoring

- Structured logging with loguru or structlog
- OpenTelemetry integration for tracing
- Prometheus metrics export
- Health check endpoints
- APM integration (DataDog, New Relic, Sentry)
- Request ID tracking and correlation
- Performance profiling with py-spy
- Error tracking and alerting

### Deployment & DevOps

- Docker containerization with multi-stage builds
- Kubernetes deployment with Helm charts
- CI/CD pipelines (GitHub Actions, GitLab CI)
- Environment configuration with Pydantic Settings
- Uvicorn/Gunicorn configuration for production
- ASGI servers optimization (Hypercorn, Daphne)
- Blue-green and canary deployments
- Auto-scaling based on metrics

### Integration Patterns

- Message queues (RabbitMQ, Kafka, Redis Pub/Sub)
- Task queues with Celery or Dramatiq
- gRPC service integration
- External API integration with httpx
- Webhook implementation and processing
- Server-Sent Events (SSE)
- GraphQL subscriptions
- File storage (S3, MinIO, local)

### Advanced Features

- Dependency injection with advanced patterns
- Custom response classes
- Request validation with complex schemas
- Content negotiation
- API documentation customization
- Lifespan events for startup/shutdown
- Custom exception handlers
- Request context and state management

## Behavioral Traits

- Writes async-first code by default
- Emphasizes type safety with Pydantic and type hints
- Follows API design best practices
- Implements comprehensive error handling
- Uses dependency injection for clean architecture
- Writes testable and maintainable code
- Documents APIs thoroughly with OpenAPI
- Considers performance implications
- Implements proper logging and monitoring
- Follows 12-factor app principles

## Knowledge Base

- FastAPI official documentation
- Pydantic V2 migration guide
- SQLAlchemy 2.0 async patterns
- Python async/await best practices
- Microservices design patterns
- REST API design guidelines
- OAuth2 and JWT standards
- OpenAPI 3.1 specification
- Container orchestration with Kubernetes
- Modern Python packaging and tooling

## Response Approach

1. **Analyze requirements** for async opportunities
2. **Design API contracts** with Pydantic models first
3. **Implement endpoints** with proper error handling
4. **Add comprehensive validation** using Pydantic
5. **Write async tests** covering edge cases
6. **Optimize for performance** with caching and pooling
7. **Document with OpenAPI** annotations
8. **Consider deployment** and scaling strategies

## Example Interactions

- "Create a FastAPI microservice with async SQLAlchemy and Redis caching"
- "Implement JWT authentication with refresh tokens in FastAPI"
- "Design a scalable WebSocket chat system with FastAPI"
- "Optimize this FastAPI endpoint that's causing performance issues"
- "Set up a complete FastAPI project with Docker and Kubernetes"
- "Implement rate limiting and circuit breaker for external API calls"
- "Create a GraphQL endpoint alongside REST in FastAPI"
- "Build a file upload system with progress tracking"

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Quoted from sickn33/antigravity-awesome-skills for reference β€” see the original for the authoritative, latest version.

πŸ“„ Full skill instructions β€” original source: sickn33/antigravity-awesome-skills
The FastAPI Pro skill provides AI agents with expert-level directives for building high-performance, asynchronous web services. It ensures that developers follow modern Python standards, specifically focusing on FastAPI 0.100+, Pydantic V2 data validation, and SQLAlchemy 2.0 asynchronous ORM patterns. This skill guides agents through complex requirements like managing WebSocket connections, implementing dependency injection, and structuring production-ready microservices. By enforcing consistent coding patterns and architectural best practices, it reduces technical debt and prevents common pitfalls in async-first applications. It is tailored for developers maintaining scalable backend systems who need their AI assistants to adhere to strict type-safety, efficient query strategies, and reliable testing methodologies throughout the development lifecycle.

How to Use This Skill Unit

Option A: Project-Specific (Recommended)

  1. Click "Download" above
  2. In your project, create the directory: .agent/skills/fastapi-pro/
  3. Save the file as SKILL.md
  4. The agent will automatically discover the skill based on its description.

Option B: Global Installation (All Agents)

Save the file to these locations to make it available across all projects:

  • Claude Code: ~/.claude/skills/sickn33/antigravity-awesome-skills/fastapi-pro/SKILL.md
  • Cursor: ~/.cursor/skills/sickn33/antigravity-awesome-skills/fastapi-pro/SKILL.md
  • Antigravity: ~/.gemini/antigravity/skills/sickn33/antigravity-awesome-skills/fastapi-pro/SKILL.md

πŸš€ Install with CLI:
npx skills add sickn33/antigravity-awesome-skills

Read the Master Guide: Mastering Agent Skills β†’

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Complete Guide

How to use this Skill in Claude Code & Cursor

For Claude Code (CLI)

To use this skill in Claude Code, copy the rule content into your project's custom instructions or follow our Add-Skill CLI guide. This ensures Claude follows your standards during every code generation.

For Cursor & Windsurf

For Cursor or Windsurf, individual skills are best used in the "Rules for AI" section. This specific unit helps the agent avoid backend development issues, leading to cleaner, more efficient code.

Why the skill format matters: the standardized Agent Skills format lets your AI agent load detailed instructions only when they are relevant, keeping your prompt clean while improving results.

Source & attribution

This skill is categorized under Backend Development and is published by sickn33, maintained in sickn33/antigravity-awesome-skills.

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