Backend Patterns logo

Backend Patterns

OrganizationPopular
WorldFlowAI
backend-patterns

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Overview

PublisherWorldFlowAI
Repositoryeverything-claude-code
Skill namebackend-patterns
Stars
5.6K
Forks
841
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by WorldFlowAI on GitHub. Read the source before you install it.

Installation

Install the Backend Patterns AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/WorldFlowAI/everything-claude-code/tree/main/skills/backend-patterns
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/WorldFlowAI/everything-claude-code.git /tmp/everything-claude-code
mkdir -p .claude/skills
cp -r /tmp/everything-claude-code/skills/backend-patterns .claude/skills/backend-patterns
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Backend Patterns in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Backend Patterns on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Backend Patterns is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Backend Development Patterns

Backend architecture patterns and best practices for scalable server-side applications.

API Design Patterns

RESTful API Structure

typescript
// ✅ Resource-based URLs
GET    /api/markets                 # List resources
GET    /api/markets/:id             # Get single resource
POST   /api/markets                 # Create resource
PUT    /api/markets/:id             # Replace resource
PATCH  /api/markets/:id             # Update resource
DELETE /api/markets/:id             # Delete resource

// ✅ Query parameters for filtering, sorting, pagination
GET /api/markets?status=active&sort=volume&limit=20&offset=0

Repository Pattern

typescript
// Abstract data access logic
interface MarketRepository {
  findAll(filters?: MarketFilters): Promise<Market[]>
  findById(id: string): Promise<Market | null>
  create(data: CreateMarketDto): Promise<Market>
  update(id: string, data: UpdateMarketDto): Promise<Market>
  delete(id: string): Promise<void>
}

class SupabaseMarketRepository implements MarketRepository {
  async findAll(filters?: MarketFilters): Promise<Market[]> {
    let query = supabase.from('markets').select('*')

    if (filters?.status) {
      query = query.eq('status', filters.status)
    }

    if (filters?.limit) {
      query = query.limit(filters.limit)
    }

    const { data, error } = await query

    if (error) throw new Error(error.message)
    return data
  }

  // Other methods...
}

Service Layer Pattern

typescript
// Business logic separated from data access
class MarketService {
  constructor(private marketRepo: MarketRepository) {}

  async searchMarkets(query: string, limit: number = 10): Promise<Market[]> {
    // Business logic
    const embedding = await generateEmbedding(query)
    const results = await this.vectorSearch(embedding, limit)

    // Fetch full data
    const markets = await this.marketRepo.findByIds(results.map(r => r.id))

    // Sort by similarity
    return markets.sort((a, b) => {
      const scoreA = results.find(r => r.id === a.id)?.score || 0
      const scoreB = results.find(r => r.id === b.id)?.score || 0
      return scoreA - scoreB
    })
  }

  private async vectorSearch(embedding: number[], limit: number) {
    // Vector search implementation
  }
}

Middleware Pattern

typescript
// Request/response processing pipeline
export function withAuth(handler: NextApiHandler): NextApiHandler {
  return async (req, res) => {
    const token = req.headers.authorization?.replace('Bearer ', '')

    if (!token) {
      return res.status(401).json({ error: 'Unauthorized' })
    }

    try {
      const user = await verifyToken(token)
      req.user = user
      return handler(req, res)
    } catch (error) {
      return res.status(401).json({ error: 'Invalid token' })
    }
  }
}

// Usage
export default withAuth(async (req, res) => {
  // Handler has access to req.user
})

Database Patterns

Query Optimization

typescript
// ✅ GOOD: Select only needed columns
const { data } = await supabase
  .from('markets')
  .select('id, name, status, volume')
  .eq('status', 'active')
  .order('volume', { ascending: false })
  .limit(10)

// ❌ BAD: Select everything
const { data } = await supabase
  .from('markets')
  .select('*')

N+1 Query Prevention

typescript
// ❌ BAD: N+1 query problem
const markets = await getMarkets()
for (const market of markets) {
  market.creator = await getUser(market.creator_id)  // N queries
}

// ✅ GOOD: Batch fetch
const markets = await getMarkets()
const creatorIds = markets.map(m => m.creator_id)
const creators = await getUsers(creatorIds)  // 1 query
const creatorMap = new Map(creators.map(c => [c.id, c]))

markets.forEach(market => {
  market.creator = creatorMap.get(market.creator_id)
})

Transaction Pattern

typescript
async function createMarketWithPosition(
  marketData: CreateMarketDto,
  positionData: CreatePositionDto
) {
  // Use Supabase transaction
  const { data, error } = await supabase.rpc('create_market_with_position', {
    market_data: marketData,
    position_data: positionData
  })

  if (error) throw new Error('Transaction failed')
  return data
}

// SQL function in Supabase
CREATE OR REPLACE FUNCTION create_market_with_position(
  market_data jsonb,
  position_data jsonb
)
RETURNS jsonb
LANGUAGE plpgsql
AS $$
BEGIN
  -- Start transaction automatically
  INSERT INTO markets VALUES (market_data);
  INSERT INTO positions VALUES (position_data);
  RETURN jsonb_build_object('success', true);
EXCEPTION
  WHEN OTHERS THEN
    -- Rollback happens automatically
    RETURN jsonb_build_object('success', false, 'error', SQLERRM);
END;
$$;

Caching Strategies

Redis Caching Layer

typescript
class CachedMarketRepository implements MarketRepository {
  constructor(
    private baseRepo: MarketRepository,
    private redis: RedisClient
  ) {}

  async findById(id: string): Promise<Market | null> {
    // Check cache first
    const cached = await this.redis.get(`market:${id}`)

    if (cached) {
      return JSON.parse(cached)
    }

    // Cache miss - fetch from database
    const market = await this.baseRepo.findById(id)

    if (market) {
      // Cache for 5 minutes
      await this.redis.setex(`market:${id}`, 300, JSON.stringify(market))
    }

    return market
  }

  async invalidateCache(id: string): Promise<void> {
    await this.redis.del(`market:${id}`)
  }
}

Cache-Aside Pattern

typescript
async function getMarketWithCache(id: string): Promise<Market> {
  const cacheKey = `market:${id}`

  // Try cache
  const cached = await redis.get(cacheKey)
  if (cached) return JSON.parse(cached)

  // Cache miss - fetch from DB
  const market = await db.markets.findUnique({ where: { id } })

  if (!market) throw new Error('Market not found')

  // Update cache
  await redis.setex(cacheKey, 300, JSON.stringify(market))

  return market
}

Error Handling Patterns

Centralized Error Handler

typescript
class ApiError extends Error {
  constructor(
    public statusCode: number,
    public message: string,
    public isOperational = true
  ) {
    super(message)
    Object.setPrototypeOf(this, ApiError.prototype)
  }
}

export function errorHandler(error: unknown, req: Request): Response {
  if (error instanceof ApiError) {
    return NextResponse.json({
      success: false,
      error: error.message
    }, { status: error.statusCode })
  }

  if (error instanceof z.ZodError) {
    return NextResponse.json({
      success: false,
      error: 'Validation failed',
      details: error.errors
    }, { status: 400 })
  }

  // Log unexpected errors
  console.error('Unexpected error:', error)

  return NextResponse.json({
    success: false,
    error: 'Internal server error'
  }, { status: 500 })
}

// Usage
export async function GET(request: Request) {
  try {
    const data = await fetchData()
    return NextResponse.json({ success: true, data })
  } catch (error) {
    return errorHandler(error, request)
  }
}

Retry with Exponential Backoff

typescript
async function fetchWithRetry<T>(
  fn: () => Promise<T>,
  maxRetries = 3
): Promise<T> {
  let lastError: Error

  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn()
    } catch (error) {
      lastError = error as Error

      if (i < maxRetries - 1) {
        // Exponential backoff: 1s, 2s, 4s
        const delay = Math.pow(2, i) * 1000
        await new Promise(resolve => setTimeout(resolve, delay))
      }
    }
  }

  throw lastError!
}

// Usage
const data = await fetchWithRetry(() => fetchFromAPI())

Authentication & Authorization

JWT Token Validation

typescript
import jwt from 'jsonwebtoken'

interface JWTPayload {
  userId: string
  email: string
  role: 'admin' | 'user'
}

export function verifyToken(token: string): JWTPayload {
  try {
    const payload = jwt.verify(token, process.env.JWT_SECRET!) as JWTPayload
    return payload
  } catch (error) {
    throw new ApiError(401, 'Invalid token')
  }
}

export async function requireAuth(request: Request) {
  const token = request.headers.get('authorization')?.replace('Bearer ', '')

  if (!token) {
    throw new ApiError(401, 'Missing authorization token')
  }

  return verifyToken(token)
}

// Usage in API route
export async function GET(request: Request) {
  const user = await requireAuth(request)

  const data = await getDataForUser(user.userId)

  return NextResponse.json({ success: true, data })
}

Role-Based Access Control

typescript
type Permission = 'read' | 'write' | 'delete' | 'admin'

interface User {
  id: string
  role: 'admin' | 'moderator' | 'user'
}

const rolePermissions: Record<User['role'], Permission[]> = {
  admin: ['read', 'write', 'delete', 'admin'],
  moderator: ['read', 'write', 'delete'],
  user: ['read', 'write']
}

export function hasPermission(user: User, permission: Permission): boolean {
  return rolePermissions[user.role].includes(permission)
}

export function requirePermission(permission: Permission) {
  return async (request: Request) => {
    const user = await requireAuth(request)

    if (!hasPermission(user, permission)) {
      throw new ApiError(403, 'Insufficient permissions')
    }

    return user
  }
}

// Usage
export const DELETE = requirePermission('delete')(async (request: Request) => {
  // Handler with permission check
})

Rate Limiting

Simple In-Memory Rate Limiter

typescript
class RateLimiter {
  private requests = new Map<string, number[]>()

  async checkLimit(
    identifier: string,
    maxRequests: number,
    windowMs: number
  ): Promise<boolean> {
    const now = Date.now()
    const requests = this.requests.get(identifier) || []

    // Remove old requests outside window
    const recentRequests = requests.filter(time => now - time < windowMs)

    if (recentRequests.length >= maxRequests) {
      return false  // Rate limit exceeded
    }

    // Add current request
    recentRequests.push(now)
    this.requests.set(identifier, recentRequests)

    return true
  }
}

const limiter = new RateLimiter()

export async function GET(request: Request) {
  const ip = request.headers.get('x-forwarded-for') || 'unknown'

  const allowed = await limiter.checkLimit(ip, 100, 60000)  // 100 req/min

  if (!allowed) {
    return NextResponse.json({
      error: 'Rate limit exceeded'
    }, { status: 429 })
  }

  // Continue with request
}

Background Jobs & Queues

Simple Queue Pattern

typescript
class JobQueue<T> {
  private queue: T[] = []
  private processing = false

  async add(job: T): Promise<void> {
    this.queue.push(job)

    if (!this.processing) {
      this.process()
    }
  }

  private async process(): Promise<void> {
    this.processing = true

    while (this.queue.length > 0) {
      const job = this.queue.shift()!

      try {
        await this.execute(job)
      } catch (error) {
        console.error('Job failed:', error)
      }
    }

    this.processing = false
  }

  private async execute(job: T): Promise<void> {
    // Job execution logic
  }
}

// Usage for indexing markets
interface IndexJob {
  marketId: string
}

const indexQueue = new JobQueue<IndexJob>()

export async function POST(request: Request) {
  const { marketId } = await request.json()

  // Add to queue instead of blocking
  await indexQueue.add({ marketId })

  return NextResponse.json({ success: true, message: 'Job queued' })
}

Logging & Monitoring

Structured Logging

typescript
interface LogContext {
  userId?: string
  requestId?: string
  method?: string
  path?: string
  [key: string]: unknown
}

class Logger {
  log(level: 'info' | 'warn' | 'error', message: string, context?: LogContext) {
    const entry = {
      timestamp: new Date().toISOString(),
      level,
      message,
      ...context
    }

    console.log(JSON.stringify(entry))
  }

  info(message: string, context?: LogContext) {
    this.log('info', message, context)
  }

  warn(message: string, context?: LogContext) {
    this.log('warn', message, context)
  }

  error(message: string, error: Error, context?: LogContext) {
    this.log('error', message, {
      ...context,
      error: error.message,
      stack: error.stack
    })
  }
}

const logger = new Logger()

// Usage
export async function GET(request: Request) {
  const requestId = crypto.randomUUID()

  logger.info('Fetching markets', {
    requestId,
    method: 'GET',
    path: '/api/markets'
  })

  try {
    const markets = await fetchMarkets()
    return NextResponse.json({ success: true, data: markets })
  } catch (error) {
    logger.error('Failed to fetch markets', error as Error, { requestId })
    return NextResponse.json({ error: 'Internal error' }, { status: 500 })
  }
}

Remember: Backend patterns enable scalable, maintainable server-side applications. Choose patterns that fit your complexity level.

Frequently asked questions

What does the Backend Patterns AI skill do?

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Why use Backend Patterns on TypingMind?

Because you install it once and use it with any model. Backend Patterns is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Backend Patterns in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WorldFlowAI/everything-claude-code/tree/main/skills/backend-patterns. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Backend Patterns?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Backend Patterns?

As many as you like. As long as a model supports skills, you can use Backend Patterns with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Backend Patterns AI skill free?

It is published on GitHub by WorldFlowAI. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇