OrchestKit is an AI development toolkit for Claude Code, offering 159 skills, 34 agents, 20 commands, and 144 hooks. It provides production-ready patterns for FastAPI, React 19, LangGraph, security, and testing. Operations teams use it to streamline AI development and deployment, integrating with existing workflows and tools.
git clone https://github.com/yonatangross/orchestkit.gitOrchestKit is an AI development toolkit for Claude Code, offering 159 skills, 34 agents, 20 commands, and 144 hooks. It provides production-ready patterns for FastAPI, React 19, LangGraph, security, and testing. Operations teams use it to streamline AI development and deployment, integrating with existing workflows and tools.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/yonatangross/orchestkitCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Using OrchestKit, create a FastAPI backend for a [PRODUCT] application. The backend should include [FEATURES] and integrate with [EXISTING_SYSTEMS]. Ensure it follows security best practices and is ready for deployment.
Here's a FastAPI backend for a customer support ticketing system, created using OrchestKit:
```python
from fastapi import FastAPI, HTTPException, Depends
from pydantic import BaseModel
from typing import List, Optional
app = FastAPI()
# Models
class Ticket(BaseModel):
id: int
title: str
description: str
status: str = 'open'
priority: str = 'medium'
# In-memory database for demonstration
fake_db = {}
@app.post('/tickets/', response_model=Ticket)
def create_ticket(ticket: Ticket):
if ticket.id in fake_db:
raise HTTPException(status_code=400, detail='Ticket already exists')
fake_db[ticket.id] = ticket
return ticket
@app.get('/tickets/', response_model=List[Ticket])
def read_tickets(status: Optional[str] = None):
if status:
return [ticket for ticket in fake_db.values() if ticket.status == status]
return list(fake_db.values())
@app.put('/tickets/{ticket_id}', response_model=Ticket)
def update_ticket(ticket_id: int, ticket: Ticket):
if ticket_id not in fake_db:
raise HTTPException(status_code=404, detail='Ticket not found')
fake_db[ticket_id] = ticket
return ticket
@app.delete('/tickets/{ticket_id}')
def delete_ticket(ticket_id: int):
if ticket_id not in fake_db:
raise HTTPException(status_code=404, detail='Ticket not found')
del fake_db[ticket_id]
return {'message': 'Ticket deleted'}
# Security middleware
@app.middleware('http')
async def add_security_headers(request: Request, call_next):
response = await call_next(request)
response.headers['X-Frame-Options'] = 'DENY'
response.headers['X-Content-Type-Options'] = 'nosniff'
response.headers['X-XSS-Protection'] = '1; mode=block'
return response
```
This backend includes:
- CRUD operations for tickets
- Basic filtering by status
- Security headers middleware
- Pydantic models for data validation
The backend is ready for deployment and can be integrated with existing systems.Agents that listen, think and act for you.
AI assistant built for thoughtful, nuanced conversation
Automated Meeting Reports Transcripts Notes Video Coaching
Security patch notifications for servers
AI-powered compliance platform for 50+ laws
Agentic Offensive Security at Scale