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.
npx agentmods add rules/mr-chen-05/rules-2.1-optimized/super-brain-systemgit clone --depth 1 https://github.com/Mr-chen-05/rules-2.1-optimizedWrote 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/mr-chen-05/rules-2.1-optimized/super-brain-system)<a href="https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/super-brain-system"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/super-brain-system.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.04669 |
| Opus 5 | $0.00000 | $0.02335 |
| Sonnet 5 | $0.00000 | $0.00934 |
| Haiku 4.5 | $0.00000 | $0.00467 |
Grade A, and why
super-brain-system 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 3d 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 — 600 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🧠 超级大脑系统
智能核心: 集成项目管理、阶段控制、记忆系统和智能推荐的统一管理平台
🎯 系统定义
超级大脑系统是一个智能化的AI代理管理平台，整合了项目生命周期管理、智能决策支持、记忆系统和自动化工作流编排功能。
🚀 激活机制
触发词和激活规则
激活触发词
系统激活:
完整触发词:
- "启动超级大脑系统"
- "启动智能项目管理"
- "激活项目大脑"
- "开启智能管理"
- "启动AI项目助手"
简化触发词:
- "超级大脑"
- "智能管理"
- "项目大脑"
状态查询:
- "查看项目状态"
- "项目进度如何"
- "当前在哪个阶段"
- "系统状态"
- "大脑状态"
触发词匹配策略
匹配优先级:
P1 - 严格完全匹配 (100% 置信度):
- 完整触发词精确匹配
- 立即激活系统
P2 - 前缀/后缀匹配 (95% 置信度):
- 触发词作为前缀: "启动超级大脑系统，我要..."
- 触发词作为后缀: "我想启动超级大脑系统"
- 立即激活系统
P3 - 意图识别 (85% 置信度):
- 动词+对象组合: 启动 + 项目 / 项目管理 / 大脑
- 分析 + 项目需求 / 方案
- 查询 + 项目状态 / 进度
- 进入确认对话或激活系统
P4 - 上下文判断 (需要验证):
- 检查是否在代码块内 (跳过触发)
- 检查是否为引用/示例 (跳过触发)
- 检查用户意图是否明确 (模糊则确认)
激活响应模板
激活成功响应:
"🧠 超级大脑系统已激活！
📊 系统状态: 运行中
🎯 当前项目: [项目名称或'未设定']
📋 当前阶段: [阶段信息或'待确定']
💾 记忆状态: [已加载/空白]
📝 记录员状态: [已集成/待激活]
🔎 记忆策略: Recorder 优先，Memory 可选（按需联动）
🤖 可用功能:
• 智能阶段推荐 (/recommend)
• 项目状态查询 (/status)
• 阶段切换 (/switch [阶段号])
• 记忆查看 (/memory) [可选]
• 自动记录 (/brain-record)
• 工具编排优化
💡 请告诉我您的项目需求，我将为您提供最佳的管理方案！
📝 所有决策和操作将自动记录到项目上下文中。"
执行约束 (新增)
强制执行规则:
触发词识别后:
✅ 必须做:
- 立即开始激活流程
- 直接执行状态检测
- 显示标准激活响应
❌ 禁止做:
- 重新读取本规则文件进行"二次确认"
- 询问"是否需要启动"（触发词本身就是明确指令）
- 解释"什么是超级大脑系统"（用户说启动，不是问是什么）
- 等待额外确认（除非涉及文件创建需要安全规则）
执行时限:
- 识别触发词 → 开始执行：< 1秒
- 完成检测 → 显示响应：< 5秒
常见执行错误（避免）
❌ 错误示例1 - 重复验证:
用户: "启动超级大脑系统"
AI: "让我先读取规则文件确认一下..." # ← 错误！规则已加载
✅ 正确示例1:
用户: "启动超级大脑系统"
AI: 立即执行检测 → 显示激活响应 # ← 正确！直接行动
❌ 错误示例2 - 过度解释:
用户: "启动超级大脑系统"
AI: "超级大脑系统是一个..." # ← 错误！用户要的是启动
✅ 正确示例2:
用户: "启动超级大脑系统"
AI: "🧠 超级大脑系统已激活！..." # ← 正确！直接响应
❌ 错误示例3 - 询问确认:
用户: "启动超级大脑系统"
AI: "您确定要启动吗？" # ← 错误！触发词就是确认
✅ 正确示例3:
用户: "启动超级大脑系统"
AI: 直接执行激活流程 # ← 正确！无需二次确认
🎛️ 核心功能模块
1. 智能项目识别
项目类型识别:
Web应用:
关键词: ["网站", "Web", "前端", "后端", "全栈"]
推荐阶段: 需求分析
技术栈: React/Vue + Node.js/Python
移动应用:
关键词: ["APP", "移动", "手机", "iOS", "Android"]
推荐阶段: 需求分析
技术栈: React Native/Flutter
桌面应用:
关键词: ["桌面", "客户端", "软件", "工具"]
推荐阶段: 需求分析
技术栈: Electron/Tauri
数据分析:
关键词: ["数据", "分析", "可视化", "报表"]
推荐阶段: 需求分析
技术栈: Python/R + 可视化库
AI/ML项目:
关键词: ["AI", "机器学习", "深度学习", "模型"]
推荐阶段: 需求分析
技术栈: Python + ML框架
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.
- 3d ago First seen · 600 lines · 0 tokens per session scan A 51e3548ac889
super-brain-system is a cursor rule published in the GitHub repository Mr-chen-05/rules-2.1-optimized (172 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,669 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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