When should I use backend-development?

backend-development is useful in the following scenarios: • 1. RESTful API Blueprinting: Designing standardized endpoint structures, response formats, and error handling protocols to ensure consistency across web services. • 2. Database Schema Engineering: Constructing optimized SQL schemas with advanced features like UUIDs, soft deletes, and efficient cursor-based pagination for high-scale data management. • 3. Security & Performance Optimization: Implementing JWT-based authentication middleware, Redis cache-aside patterns, and IP-based rate limiting to protect and accelerate backend services. • 4. System Observability & Monitoring: Setting up structured JSON logging, health check endpoints, and distributed tracing to maintain visibility in microservices environments.

When & Why to Use This Skill

This Claude skill provides a comprehensive framework for modern backend development, focusing on scalable API design, robust database architecture, and microservices patterns. It streamlines the creation of production-ready systems by offering standardized templates for RESTful conventions, JWT authentication, caching strategies, and observability best practices, ensuring high performance and maintainability.

Use Cases

1. RESTful API Blueprinting: Designing standardized endpoint structures, response formats, and error handling protocols to ensure consistency across web services.
2. Database Schema Engineering: Constructing optimized SQL schemas with advanced features like UUIDs, soft deletes, and efficient cursor-based pagination for high-scale data management.
3. Security & Performance Optimization: Implementing JWT-based authentication middleware, Redis cache-aside patterns, and IP-based rate limiting to protect and accelerate backend services.
4. System Observability & Monitoring: Setting up structured JSON logging, health check endpoints, and distributed tracing to maintain visibility in microservices environments.

name	backend-development
description	Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
source	wshobson/agents
license	MIT

name

backend-development

description

Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.

source

wshobson/agents

license

MIT

Backend Development

API Design

RESTful Conventions

GET    /users          # List users
POST   /users          # Create user
GET    /users/:id      # Get user
PUT    /users/:id      # Update user (full)
PATCH  /users/:id      # Update user (partial)
DELETE /users/:id      # Delete user

GET    /users/:id/posts  # List user's posts
POST   /users/:id/posts  # Create post for user

Response Format

{
  "data": { ... },
  "meta": {
    "page": 1,
    "per_page": 20,
    "total": 100
  }
}

Error Format

{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid input",
    "details": [
      { "field": "email", "message": "Invalid format" }
    ]
  }
}

Database Patterns

Schema Design

-- Use UUIDs for public IDs
CREATE TABLE users (
  id SERIAL PRIMARY KEY,
  public_id UUID DEFAULT gen_random_uuid() UNIQUE,
  email VARCHAR(255) UNIQUE NOT NULL,
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);

-- Soft deletes
ALTER TABLE users ADD COLUMN deleted_at TIMESTAMPTZ;

-- Indexes
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_users_created ON users(created_at DESC);

Query Patterns

-- Pagination with cursor
SELECT * FROM posts
WHERE created_at < $cursor
ORDER BY created_at DESC
LIMIT 20;

-- Efficient counting
SELECT reltuples::bigint AS estimate
FROM pg_class WHERE relname = 'users';

Authentication

JWT Pattern

interface TokenPayload {
  sub: string;      // User ID
  iat: number;      // Issued at
  exp: number;      // Expiration
  scope: string[];  // Permissions
}

function verifyToken(token: string): TokenPayload {
  return jwt.verify(token, SECRET) as TokenPayload;
}

Middleware

async function authenticate(req: Request, res: Response, next: Next) {
  const token = req.headers.authorization?.replace('Bearer ', '');
  if (!token) {
    return res.status(401).json({ error: 'Unauthorized' });
  }

  try {
    req.user = verifyToken(token);
    next();
  } catch {
    res.status(401).json({ error: 'Invalid token' });
  }
}

Caching Strategy

// Cache-aside pattern
async function getUser(id: string): Promise<User> {
  const cached = await redis.get(`user:${id}`);
  if (cached) return JSON.parse(cached);

  const user = await db.users.findById(id);
  await redis.setex(`user:${id}`, 3600, JSON.stringify(user));
  return user;
}

// Cache invalidation
async function updateUser(id: string, data: Partial<User>) {
  await db.users.update(id, data);
  await redis.del(`user:${id}`);
}

Rate Limiting

const limiter = rateLimit({
  windowMs: 60 * 1000,  // 1 minute
  max: 100,             // 100 requests per window
  keyGenerator: (req) => req.ip,
  handler: (req, res) => {
    res.status(429).json({ error: 'Too many requests' });
  }
});

Observability

Logging: Structured JSON logs with request IDs
Metrics: Request latency, error rates, queue depths
Tracing: Distributed tracing with correlation IDs
Health checks: /health and /ready endpoints