Agent skill

FastAPI Scaffolding

Generate and maintain the FastAPI backend structure for the RAG chatbot with proper project organization.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/fastapi-scaffolding

SKILL.md

FastAPI Scaffolding

Instructions

  1. Create or update the backend folder structure with these directories:

    • app/
      • main.py (entry point with health endpoint)
      • routers/ (for API endpoints)
      • services/ (for business logic)
      • schemas/ (for Pydantic models)
      • deps/ (for dependency injection)
  2. Generate main.py with:

    • FastAPI app initialization
    • Health check endpoint at GET /health
    • CORS middleware configuration
    • Include routers setup
  3. Create a chat router placeholder in routers/chat.py

    • Include basic route registration
    • Setup for POST /chat endpoint
  4. Ensure proper Uvicorn configuration in requirements.txt and startup command

    • Include uvicorn, fastapi in dependencies
    • Provide proper startup command: uvicorn app.main:app --host 0.0.0.0 --port 7860
  5. Follow deterministic, clean Python code standards

    • Use proper type hints
    • Follow PEP 8 style guidelines
    • Include proper error handling

Examples

Input: "Create FastAPI backend structure" Output: Creates the complete directory structure with main.py containing:

python
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from app.routers import chat

app = FastAPI(title="Physical AI & Humanoid Robotics RAG API")

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Configure appropriately for production
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.get("/health")
async def health_check():
    return {"status": "healthy"}

app.include_router(chat.router, prefix="/api/v1")

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