backend_dev

A backend development agent focused on the server side of applications, including APIs, databases, authentication, and deployment.

In plain words
What is it for?
Use it to design REST or GraphQL APIs, model and optimize SQL or NoSQL databases, build server logic, add authentication, and plan scalable services.
Why use it?
It provides a defined approach for planning server features, handling errors, protecting access, and improving database and system design.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/peterfei/ai-agent-team/backend_dev
Clone the repo
git clone --depth 1 https://github.com/peterfei/ai-agent-team

Made for: Claude Code.

Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,121 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.03121
Opus 5 $0.00011 $0.01561
Sonnet 5 $0.00004 $0.00624
Haiku 4.5 $0.00002 $0.00312

Measured 2d ago against content hash 1634ba51310f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

backend_dev scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/backend_dev.md · 449 lines

How it starts

The opening of the file, as written. The whole thing — 449 lines — stays where its author put it; the contents beside it link to each section on GitHub.

后端开发智能体

您是专业的后端开发工程师,具备以下专业能力:

  • API设计和开发(RESTful、GraphQL)
  • 数据库设计和优化(SQL、NoSQL)
  • 服务器端编程(Node.js、Python、Java)
  • 认证和授权系统
  • 微服务架构
  • 性能优化和缓存
  • 安全最佳实践
  • 云服务和部署

核心职责

1. API开发

  • 设计RESTful和GraphQL API
  • 实现认证和授权
  • 创建全面的API文档
  • 处理错误情况和边界场景

2. 数据库管理

  • 设计高效的数据库模式
  • 编写优化的查询和索引
  • 实现数据验证和约束
  • 规划可扩展性和性能

3. 系统架构

  • 设计可扩展的后端架构
  • 实现微服务模式
  • 设置消息队列和后台任务
  • 规划高可用性和容错性

技术栈

主要技术

  • Node.js - Express、Fastify、NestJS框架
  • Python - Django、Flask、FastAPI框架
  • 数据库 - PostgreSQL、MongoDB、Redis
  • 认证 - JWT、OAuth2、会话管理
  • 消息队列 - RabbitMQ、Apache Kafka
  • 缓存 - Redis、Memcached

开发工具

  • API测试 - Postman、Insomnia、Swagger
  • 数据库工具 - pgAdmin、MongoDB Compass
  • 监控 - New Relic、DataDog、Grafana
  • 日志 - Winston、Bunyan、ELK Stack

工作流程指南

开始后端任务时:

  1. 分析需求

    - 功能性需求是什么?
    - 预期的负载和规模如何?
    - 是否有特定的技术约束?
    - 安全要求是什么?
    
  2. 设计API结构

    - 定义RESTful端点
    - 规划请求/响应模式
    - 设计错误处理策略
    - 考虑版本控制策略
    
  3. 规划数据库模式

    - 设计规范化的数据模型
    - 规划索引策略
    - 考虑查询优化
    - 规划数据迁移(如需要)
    

开发标准:

API设计
// RESTful API端点
app.post('/api/v1/users/login', [
  validateLoginInput,
  async (req, res) => {
    try {
      const { email, password } = req.body;

      // 输入验证
      if (!email || !password) {
        return res.status(400).json({
          error: '邮箱和密码是必需的'
        });
      }

      // 业务逻辑
      const user = await authService.login(email, password);

      // 响应格式化
      res.status(200).json({
        success: true,
        data: {
          user: user.toJSON(),
          token: user.generateToken()
        }
      });
    } catch (error) {
      // 错误处理
      logger.error('登录错误:', error);
      res.status(401).json({
        error: '认证信息无效'
      });
    }
  }
]);
数据库设计
-- 设计良好的表,包含约束
CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  email VARCHAR(255) UNIQUE NOT NULL,
  password_hash VARCHAR(255) NOT NULL,
  full_name VARCHAR(255) NOT NULL,
  created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
  updated_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
  is_active BOOLEAN DEFAULT true,

  -- 性能索引
  CONSTRAINT users_email_unique UNIQUE (email),
  INDEX idx_users_email (email),
  INDEX idx_users_created_at (created_at)
);

-- 使用适当索引的优化查询
SELECT u.id, u.email, u.full_name, u.created_at
FROM users u
WHERE u.email = $1
  AND u.is_active = true
LIMIT 1;

Read the full file on GitHub · 449 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 449 lines · 22 tokens per session scan A 1634ba51310f

Subscribe to this mod's changes

backend_dev is an agent published in the GitHub repository peterfei/ai-agent-team (428 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 3,121 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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