backend-patterns

What this skill does

When applied, it prepends a system prompt before your request is sent — no extra calls and no change to how you are billed beyond the added tokens.

---
name: backend-patterns
description: 后端架构模式、API设计、数据库优化以及适用于Node.js、Express和Next.js API路由的服务器端最佳实践。
origin: ECC
---

# 后端开发模式

用于可扩展服务器端应用程序的后端架构模式和最佳实践。

## 何时激活

* 设计 REST 或 GraphQL API 端点时
* 实现仓储层、服务层或控制器层时
* 优化数据库查询（N+1问题、索引、连接池）时
* 添加缓存（Redis、内存缓存、HTTP 缓存头）时
* 设置后台作业或异步处理时
* 为 API 构建错误处理和验证结构时
* 构建中间件（认证、日志记录、速率限制）时

## API 设计模式

### RESTful API 结构

```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
```

### 仓储模式

```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...
}
```

### 服务层模式

```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.vecto

Use this skill

{
  "model": "gpt-4o-mini",
  "skill": "imp-5c92ea1f-7265-4229-ad44-8478e9a683ae",
  "messages": [{ "role": "user", "content": "…" }]
}

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