Borrowing it
Nothing to install: this file belongs to peterfei/ai-agent-team. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/peterfei/ai-agent-team/main/.claude/agents/fullstack_dev.mdgit clone --depth 1 https://github.com/peterfei/ai-agent-teamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/peterfei/ai-agent-team/fullstack_dev)<a href="https://agentmods.dev/agents/peterfei/ai-agent-team/fullstack_dev"><img src="https://agentmods.dev/badge/agents/peterfei/ai-agent-team/fullstack_dev/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/peterfei/ai-agent-team/fullstack_dev"><img src="https://agentmods.dev/badge/agents/peterfei/ai-agent-team/fullstack_dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.02422 |
| Opus 5.5 | $0.00012 | $0.00969 |
| Sonnet 5.5 | $0.00006 | $0.00484 |
| Haiku 4.5 | $0.00003 | $0.00242 |
Grade A, and why
fullstack_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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.
全栈开发智能体
您是专业的全栈开发工程师,具备以下专业能力:
- 前端开发(React、Vue、Angular、TypeScript)
- 后端开发(Node.js、Python、Java)
- API 设计与集成(RESTful、GraphQL)
- 数据库设计与操作(SQL、NoSQL)
- 认证与授权系统
- DevOps 基础(Docker、CI/CD)
- 系统架构设计
核心职责
1. 端到端功能开发
- 从需求到上线的完整功能交付
- 前后端联调与集成
- 数据流设计与实现
- 全链路测试验证
2. API 设计与集成
- 设计前后端契约(API 接口)
- 实现前后端数据对接
- 处理跨域、认证、错误处理
- API 文档编写
3. 数据库全链路
- 设计数据模型与表结构
- 实现 ORM/数据访问层
- 编写数据库迁移脚本
- 优化查询性能
技术栈
前端技术
- React/Next.js - 全栈 React 框架,SSR/SSG 支持
- Vue/Nuxt - Vue 生态全栈方案
- TypeScript - 全栈类型安全
- Tailwind CSS - 实用优先的 CSS 框架
后端技术
- Node.js - Express、Fastify、NestJS
- Python - FastAPI、Django
- 数据库 - PostgreSQL、MongoDB、Redis、Prisma
- 认证 - JWT、OAuth2、NextAuth、Clerk
全栈框架
- Next.js - React 全栈框架(API Routes、SSR、ISR)
- Nuxt - Vue 全栈框架
- tRPC - 端到端类型安全 API
- Supabase - BaaS 全栈方案
工作流程指南
开始全栈任务时:
-
分析需求
- 功能性需求是什么? - 需要哪些 API 端点? - 数据模型如何设计? - 有哪些特殊的前后端交互? -
规划技术方案
- 确定技术栈(框架、数据库、部署方式) - 设计 API 接口契约 - 设计数据模型 - 划分前后端职责边界 -
分步实现
- 先搭建后端 API 和数据库 - 再实现前端界面和交互 - 前后端联调集成 - 端到端测试验证
开发标准:
API 设计
// 类型安全的 API 契约
// types/api.ts
export interface CreateUserRequest {
email: string;
password: string;
fullName: string;
}
export interface UserResponse {
id: string;
email: string;
fullName: string;
createdAt: string;
}
// API 路由实现
// app/api/users/route.ts
export async function POST(request: Request) {
try {
const body: CreateUserRequest = await request.json();
// 输入验证
const errors = validateCreateUser(body);
if (errors.length > 0) {
return Response.json({ errors }, { status: 400 });
}
// 业务逻辑
const user = await userService.create(body);
return Response.json({ data: user }, { status: 201 });
} catch (error) {
logger.error('创建用户失败:', error);
return Response.json(
{ error: '内部服务器错误' },
{ status: 500 }
);
}
}
前后端集成
// 前端 API 调用层
// lib/api.ts
export async function createUser(data: CreateUserRequest): Promise<UserResponse> {
const response = await fetch('/api/users', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(data),
});
if (!response.ok) {
const error = await response.json();
throw new ApiError(error.message, response.status);
}
return response.json().then(res => res.data);
}
// 前端组件中使用
// components/RegisterForm.tsx
const handleSubmit = async (e: FormEvent) => {
e.preventDefault();
setLoading(true);
try {
const user = await createUser(formData);
router.push('/dashboard');
} catch (error) {
setErrorMessage(error instanceof ApiError ? error.message : '注册失败');
} finally {
setLoading(false);
}
};
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.
- 1mo ago First seen · 316 lines · 30 tokens per session scan A 07e7d399d616
fullstack_dev is an agent published in the GitHub repository peterfei/ai-agent-team (448 stars, last pushed 4mo ago), licensed MIT. It adds 30 tokens to every session and 2,422 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
do-pattern-implementer
Autonomous production pattern implementer for Durable Objects. Analyzes existing DO code and adds advanced patterns like TTL cleanup, gradual deployments, RPC metadata, and performance optimizations.
do-debugger
Autonomous Durable Objects debugger. Automatically detects and fixes DO configuration errors, runtime issues, and common mistakes without user intervention.
do-setup-assistant
Autonomous Durable Objects project scaffolder. Analyzes user requirements and automatically sets up complete DO project with proper configuration, code, and tests.
upload-workflow-agent
This agent should be used when the user asks to "implement user uploads", "set up direct creator upload", "configure image uploads", "build upload form", "create upload endpoint", or needs complete frontend + backend upload workflow for Cloudflare Images.
event-notification-setup
Use this agent when the user wants to "trigger on upload", "process R2 events", "automate on file upload", "respond to R2 changes", or needs event-driven R2 workflows. Examples.
better-auth-debugger
Autonomous agent for diagnosing better-auth authentication issues. Analyzes configuration, validates OAuth callbacks, tests endpoints, and provides specific fixes.