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 a unified plugin for Claude Code that eliminates repetitive stack explanation by encoding persistent knowledge of production patterns. It includes 111 reusable skills for RAG, FastAPI, React 19, testing, security, and database design that load on-demand with zero overhead. The plugin features 37 specialized agents that route tasks to the right expert persona, and 211 hooks for pre-commit checks, git protection, and quality gates. Setup is guided by a personalized onboarding wizard that scans your codebase, detects your tech stack, recommends relevant skills, and configures MCP servers. Development teams use OrchestKit to standardize patterns, enforce conventions automatically, and ship code with confidence.
1. **Install OrchestKit**: Run `pip install orchestkit` in your Python environment or use the provided CLI tool. 2. **Select Project Type**: Choose from FastAPI, React 19, or LangGraph based on your needs. For backend services, use FastAPI; for frontend, React 19; for complex workflows, LangGraph. 3. **Configure Features**: Specify required features like authentication, database integration, or specific security measures. Use the `--features` flag to include multiple features at once. 4. **Generate Project**: Execute the OrchestKit command with your specifications. Example: `orchestkit generate --type fastapi --features jwt,postgres,openapi`. Review the generated files and structure. 5. **Customize and Extend**: Modify the generated files to match your specific requirements. Use the included testing framework to validate your setup before deployment. **Tips for Better Results:** - Always review the `.env.example` file and configure your environment variables before running the project - Use the `--output` flag to specify a custom directory for your project - For React 19 projects, ensure you have Node.js 18+ installed - Leverage the included hooks for CI/CD integration and automated testing
Implement full-stack features with parallel multi-agent coordination using /ork:implement
Establish team coding standards through automatic hooks that block bad commits and enforce quality gates
Onboard new developers with personalized setup wizard that configures skills for your specific tech stack
Review pull requests with specialized agents (backend-architect, frontend-dev, security-auditor) in parallel
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.
Use OrchestKit to scaffold a [PROJECT_TYPE] project (FastAPI/React 19/LangGraph) with production-ready patterns for [SPECIFIC_FEATURES]. Include [SECURITY_MEASURES] and [TESTING_FRAMEWORK]. Generate the project structure, key files, and initial configuration. Document the setup process in a README.md file.
### Project Scaffolding with OrchestKit
**Project Type:** FastAPI microservice for user authentication
**Features:** JWT authentication, rate limiting, OpenAPI docs, PostgreSQL integration
**Security Measures:** Environment variables, CORS middleware, input validation
**Testing Framework:** pytest with coverage reports
---
#### Generated Project Structure:
```
auth-service/
├── .env.example
├── .gitignore
├── README.md
├── app/
│ ├── __init__.py
│ ├── main.py
│ ├── config.py
│ ├── models/
│ │ ├── __init__.py
│ │ └── user.py
│ ├── routes/
│ │ ├── __init__.py
│ │ ├── auth.py
│ │ └── users.py
│ ├── services/
│ │ ├── __init__.py
│ │ ├── auth_service.py
│ │ └── user_service.py
│ ├── utils/
│ │ ├── __init__.py
│ │ ├── security.py
│ │ └── validators.py
│ └── database/
│ ├── __init__.py
│ └── session.py
├── tests/
│ ├── __init__.py
│ ├── test_auth.py
│ └── test_users.py
├── requirements.txt
└── docker-compose.yml
```
#### Key Files Generated:
**app/main.py**
```python
from fastapi import FastAPI
from app.routes import auth, users
from app.config import settings
from app.database.session import engine, Base
Base.metadata.create_all(bind=engine)
app = FastAPI(title="Auth Service", version="0.1.0")
app.include_router(auth.router, prefix="/auth", tags=["auth"])
app.include_router(users.router, prefix="/users", tags=["users"])
```
**app/config.py**
```python
from pydantic_settings import BaseSettings
class Settings(BaseSettings):
database_url: str = "postgresql://user:password@localhost:5432/auth_db"
jwt_secret: str = "your-secret-key"
jwt_algorithm: str = "HS256"
access_token_expire_minutes: int = 30
settings = Settings()
```
**README.md**
```markdown
# Auth Service
A FastAPI microservice for user authentication.
## Setup
1. Copy `.env.example` to `.env` and configure environment variables
2. Run `docker-compose up -d` to start PostgreSQL
3. Install dependencies: `pip install -r requirements.txt`
4. Start the service: `uvicorn app.main:app --reload`
## Testing
Run tests with: `pytest --cov=app tests/`
## API Documentation
Access OpenAPI docs at: http://localhost:8000/docs
```
---
**Next Steps:**
1. Configure your `.env` file with actual database credentials
2. Run database migrations: `alembic revision --autogenerate -m "initial"`
3. Start the service and test the `/auth/register` and `/auth/login` endpoints
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