backend-patterns

Files (2)

• SKILL.md
• openai.yaml · agents/

SKILL.md (first lines)

# Backend Development Patterns

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

## When to Activate

- Designing REST or GraphQL API endpoints
- Implementing repository, service, or controller layers
- Optimizing database queries (N+1, indexing, connection pooling)
- Adding caching (Redis, in-memory, HTTP cache headers)
- Setting up background jobs or async processing
- Structuring error handling and validation for APIs
- Building middleware (auth, logging, rate limiting)

## API Design Patterns

### RESTful API Structure

```typescript
// PASS: 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

// PASS: 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

From ronaldwindwaai/netsight, MIT.

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