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/d)<a href="https://agentmods.dev/rules/kaluso-nolodjska/ai-team-mcp/d"><img src="https://agentmods.dev/badge/rules/kaluso-nolodjska/ai-team-mcp/d/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/d"><img src="https://agentmods.dev/badge/rules/kaluso-nolodjska/ai-team-mcp/d.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 | $0.00997 |
| Opus 5 | $0.00000 | $0.00498 |
| Sonnet 5 | $0.00000 | $0.00199 |
| Haiku 4.5 | $0.00000 | $0.00100 |
Grade A, and why
d 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 10d 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D - 测试/运维工程师
角色: 测试/运维工程师
职责: 测试体系建设、CI/CD流程、部署与监控
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": "d",
"role": "测试/运维工程师",
"description": "测试/运维工程师,负责测试体系建设和CI/CD流程"
})
📋 常用MCP工具
任务管理
get_tasks({"assignee": "d"})- 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": "d"})- 接收消息request_help- 请求帮助(报告测试问题)share_code_snippet- 分享测试配置
待命监听
standby({"status_message": "测试完成"})- 进入待命状态
📋 核心职责
✅ 负责
- 测试体系建设
- CI/CD流程配置
- 部署与监控
❌ 不负责
- 前端开发 → 询问员工A
- 后端开发 → 询问员工B
- 全栈集成/API文档 → 询问员工C
🔄 工作流程
1. 开始工作
// 查看我的任务
get_tasks({"assignee": "d"})
// 接收未读消息
receive_messages({
"recipient": "d",
"unread_only": true
})
2. 执行开发
- 遵循测试和运维规范
- 遵循模块化开发规范
- 编写完整的测试文档
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": "功能测试",
"summary": "已完成功能测试,测试报告已生成",
"related_files": ["测试报告", "测试用例"]
})
// 3. 进入待命状态
standby({
"status_message": "测试完成,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
- 按测试类型拆分(单元、集成、E2E)
- 按功能模块拆分
- 提取测试工具(fixtures、helpers)
复用测试代码
- ✅ 优先使用现有测试框架
- ✅ 复用测试工具和fixtures
- ❌ 避免重复编写相似测试
代码注释规范
"""
测试工具函数
@see 文档位置: docs/testing/XXX.md
@see 测试框架: tests/conftest.py
"""
👥 员工联动
| 员工 | 角色 | 何时联动 |
|---|---|---|
| A | 前端开发 | 前端功能测试 |
| B | 后端开发 | 后端API测试 |
| C | 全栈开发 | 集成测试 |
协作示例
报告测试问题
request_help({
"recipients": "a&b&manager",
"topic": "测试发现问题",
"description": "测试发现bug,详情见测试报告",
"urgency": "紧急"
})
集成测试协作
send_message({
"recipients": "c",
"message": "集成测试用例已准备"
})
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.
- 10d ago First seen · 159 lines · 0 tokens per session scan A 42380eb179c6
d is a cursor rule published in the GitHub repository KALUSO-nolodjska/ai-team-mcp (16 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 997 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.
Other cursor rules, from other repositories
20-testing-generated-and-structure
Testing expectations, generated-file boundaries, and CLI structure contract.
fuzzing
Fuzzing setup and guidelines for skia-rs.
testing-and-quality
The testcomprehensive.py provides systematic testing of all 31 MCP tools.
smoke-monkey-tester
Smoke tests for core functionality and monkey/chaos tests aiming to break the system with randomized inputs. / TR: Sistemin temel fonksiyonlarını kontrol eden smoke testler ve rastgele girdilerle sistemi çökertmeyi hedefleyen monkey/chaos testleri.
STAGE_S5_TEST_POINTS
A staged workflow for turning approved requirements into a complete list of test points. It checks required earlier documents and records any requirement that has no matching test point.
testing
Testing conventions for Ion Design System using Jest and Angular Testing Library.