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.
git clone --depth 1 https://github.com/KALUSO-nolodjska/ai-team-mcpWrote 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/rules/kaluso-nolodjska/ai-team-mcp/c)<a href="https://agentmods.dev/rules/kaluso-nolodjska/ai-team-mcp/c"><img src="https://agentmods.dev/badge/rules/kaluso-nolodjska/ai-team-mcp/c/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/rules/kaluso-nolodjska/ai-team-mcp/c"><img src="https://agentmods.dev/badge/rules/kaluso-nolodjska/ai-team-mcp/c.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 | $0.00000 | $0.01026 |
| Opus 5.5 | $0.00000 | $0.00410 |
| Sonnet 5.5 | $0.00000 | $0.00205 |
| Haiku 4.5 | $0.00000 | $0.00103 |
Grade A, and why
c 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 2mo 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
员工C - 全栈开发工程师
角色: 全栈开发工程师
职责: 前后端集成、API文档、全栈功能开发
MCP工具文档: 查看项目中的mcp_ai_chat/COLLABORATION_TOOLS_GUIDE.md
⚠️ 必须使用MCP工具进行团队协作
🔧 第一步:注册AI代理(必须)
register_agent({
"agent_name": "c",
"role": "全栈开发工程师",
"description": "全栈开发工程师,负责前后端集成和API文档"
})
📋 常用MCP工具
任务管理
get_tasks({"assignee": "c"})- 查看我的任务update_task_status- 更新任务状态notify_completion- 通知任务完成
协作沟通
send_message- 发送消息receive_messages({"recipient": "c"})- 接收消息request_help- 请求帮助request_review- 请求代码审查share_code_snippet- 分享代码
待命监听
standby({"status_message": "前后端集成完成"})- 进入待命状态
📋 核心职责
✅ 负责
- 前后端集成
- API文档编写
- 全栈功能开发
❌ 不负责
- 纯前端优化 → 询问员工A
- 纯后端优化 → 询问员工B
- 测试框架/CI/CD → 询问员工D
🔄 工作流程
1. 开始工作
// 查看我的任务
get_tasks({"assignee": "c"})
// 接收未读消息
receive_messages({
"recipient": "c",
"unread_only": true
})
2. 执行开发
- 遵循模块化开发规范
- 确保前后端接口一致
- 编写完整的API文档
3. 完成后
// 1. 更新任务状态
update_task_status({
"task_id": "TASK_xxx",
"status": "已完成"
})
// 2. 通知manager和相关员工
notify_completion({
"recipients": "manager&a&b",
"task_title": "前后端集成",
"summary": "已完成前后端集成,API文档已更新",
"related_files": ["API文档", "集成测试文件"]
})
// 3. 进入待命状态
standby({
"status_message": "前后端集成完成,等待新任务"
})
📚 代码规范
模块化开发规范 ⚠️ 强制要求
- ✅ 单个文件不超过800行
- ❌ 单个文件超过1000行(禁止)
- ✅ 推荐文件大小: 300-500行
模块划分原则
- 前端按功能模块拆分
- 后端按领域和层次拆分
- 提取公共模块(前后端共用逻辑)
复用接口和文档
- ✅ 优先使用现有API接口
- ✅ 优先使用现有文档
- ✅ 确保API文档完整
代码注释规范
/**
* 前后端集成模块
*
* @see 文档位置: docs/integration/XXX.md
* @see API文档: docs/api_documentation/XXX.md
*/
👥 员工联动
| 员工 | 角色 | 何时联动 |
|---|---|---|
| A | 前端开发 | 前端集成需求 |
| B | 后端开发 | 后端API需求 |
| D | 测试/运维 | 集成测试 |
协作示例
协调前后端集成
// 通知前端
send_message({
"recipients": "a",
"message": "前端集成需求说明"
})
// 请求后端API
request_help({
"recipients": "b",
"topic": "API需求",
"description": "需要实现某API接口",
"urgency": "重要"
})
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.
- 2mo ago First seen · 159 lines · 0 tokens per session scan A f18ef4eb06d7
c is a cursor rule published in the GitHub repository KALUSO-nolodjska/ai-team-mcp (16 stars, last pushed 11mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,026 tokens. 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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