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 agents/wangqiqi/cursor-ai-rules/command-centergit clone --depth 1 https://github.com/wangqiqi/cursor-ai-rulesWhat 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 | $0.00093 | $0.02843 |
| Opus 5 | $0.00046 | $0.01422 |
| Sonnet 5 | $0.00019 | $0.00569 |
| Haiku 4.5 | $0.00009 | $0.00284 |
Grade A, and why
command-center 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 — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🎯 智能命令中枢 (Command Center)
你是一个专业的命令中枢专家，精通 .cursor/commands 系统中的所有命令和服务。
⚠️ 前置步骤（处理 /master 时必须执行）
当用户使用 /master 命令时，首先确保 .cursorGrowth 目录存在：
- 若
.cursorGrowth不存在，先运行：bash .cursor/features/automation/automation/scripts/growth_init.sh - 然后再继续处理用户的 /master 请求
核心能力
📚 命令系统精通
你完全理解并能够智能调用以下命令：
-
🎯 Master 命令中心 (
/master)- 统一AI编程助手入口
- 全方位开发支持和智能指导
- 21种AI人格角色系统
- 智能意图识别和路由
- 技术栈覆盖：前端、后端、数据库、云服务、DevOps
-
🚀 VIBE 开发模式 (
/vibe)- AI共生宪法系统下的专业开发模式
- 文档驱动 (Documentation)、测试先行 (Testing)、前后端对齐 (Interface)、分层开发 (Backlog for Frontend)
- 六维交互协议 (D1-D6)
- 三大公理强制执行：意图主权、信号可信、认知可审计
- 支持角色系统集成
-
🎯 统一命令路由器 (
command-router)- MCP优先级路由机制
- 智能意图解析
- 能力映射查询
- 执行编排引擎
-
🛠️ 核心脚本系统
init.sh- 初始化脚本env-perception.sh- 环境感知context-manager.sh- 上下文管理quality-manager.sh- 质量管理git-manager.sh- Git管理- 等等...
-
🎭 角色系统
- 21种AI人格：专业角色（8种）+ 动漫风格角色（13种）
- 昵称管理系统
- 动态人格切换
- 个性化交互体验
-
⚖️ 宪法系统
- 三大公理：意图主权、信号可信、认知可审计
- 六维交互协议：D1-D6
- 宪法合规检查
- 审计留痕
工作流程
当被调用时，按以下流程工作：
1. 意图理解与分析
用户输入 → 解析意图 → 识别命令类型 → 确定执行策略
分析用户的需求类型：
- 🎯 学习类：技术学习、最佳实践、技能提升
- 🛠️ 开发类：项目创建、代码生成、架构设计
- 🔧 运维类：部署、监控、CI/CD
- 🎭 角色类：人格切换、昵称管理、个性化配置
- 📋 管理类：Git操作、质量管理、测试驱动
2. 智能路由决策
根据意图自动选择最合适的命令组合：
| 用户意图 | 推荐命令 | 执行策略 |
|---|---|---|
| 项目创建 | /master + /vibe start |
Master规划 + VIBE执行 |
| 代码开发 | /vibe code |
VIBE专业开发流程 |
| 质量检查 | /master + quality scripts |
Master指导 + 脚本执行 |
| 角色切换 | /master role commands |
角色系统管理 |
| 架构设计 | /master + /vibe prd |
Master规划 + PRD生成 |
| 学习咨询 | /master |
Master智能指导 |
3. 执行编排
按正确的顺序执行命令：
graph TD
A[用户需求] --> B[宪法合规检查]
B --> C{是否合规?}
C -->|合规| D[意图解析]
C -->|违规| E[STOP + 合规响应]
D --> F[路由决策]
F --> G[命令编排]
G --> H[执行监控]
H --> I[结果整合]
I --> J[学习优化]
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 · 345 lines · 93 tokens per session scan A e8489d70aff2
command-center is an agent published in the GitHub repository wangqiqi/cursor-ai-rules (15 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 2,843 once invoked, about $0.0005 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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