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/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/custom-command-builder)<a href="https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/custom-command-builder"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/custom-command-builder/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/mr-chen-05/rules-2.1-optimized/custom-command-builder"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/custom-command-builder.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 | $0.04841 | $0.04841 |
| Opus 5.5 | $0.01936 | $0.01936 |
| Sonnet 5.5 | $0.00968 | $0.00968 |
| Haiku 4.5 | $0.00484 | $0.00484 |
Grade A, and why
custom-command-builder 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 — 702 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🛠️ Custom Command Builder - 智能自定义命令构建器
AI驱动的用户自定义命令和规则构建系统，支持智能模板生成、规则扩展和插件开发。
🧠 AI Intelligence Core - AI智能核心
智能激活条件
自动激活场景:
- 用户执行 "/create-command" 命令
- 检测到重复性操作需要自动化
- 超级大脑系统推荐创建自定义命令
- 项目需要特定的工作流定制
- 团队需要标准化操作流程
智能分析维度:
- 用户操作模式和频率 (30%)
- 项目特定需求分析 (25%)
- 团队协作模式识别 (20%)
- 工作流效率评估 (15%)
- 自动化潜力评估 (10%)
🚀 Commands - 智能命令
/create-command- AI智能命令创建（推荐）/create-command --template <type>- 使用指定模板创建/create-command --workflow- 创建工作流命令/create-command --rule- 创建自定义规则/create-command --plugin- 创建插件扩展/list-commands- 列出所有自定义命令/edit-command <name>- 编辑现有命令/delete-command <name>- 删除自定义命令
✨ AI-Powered Features - AI驱动功能
🤖 智能命令生成引擎
命令类型识别:
工作流命令:
- 开发流程自动化
- 测试和部署流程
- 代码审查流程
- 发布管理流程
工具集成命令:
- MCP工具快捷调用
- 外部API集成
- 数据库操作
- 文件系统操作
项目管理命令:
- 项目状态查询
- 进度跟踪和报告
- 团队协作支持
- 质量指标监控
自动化脚本:
- 重复任务自动化
- 批量操作处理
- 数据处理和转换
- 系统维护任务
智能生成能力:
- 基于用户描述自动生成命令逻辑
- 智能参数识别和验证
- 错误处理和异常管理
- 帮助文档自动生成
🔧 模板系统
内置模板:
基础模板:
- simple-command: 简单命令模板
- workflow-command: 工作流命令模板
- api-integration: API集成模板
- file-operation: 文件操作模板
高级模板:
- mcp-tool-wrapper: MCP工具包装器
- multi-step-workflow: 多步骤工作流
- conditional-logic: 条件逻辑模板
- error-handling: 错误处理模板
项目特定模板:
- frontend-command: 前端项目命令
- backend-command: 后端项目命令
- fullstack-command: 全栈项目命令
- devops-command: DevOps操作命令
自定义模板:
- 用户可创建自己的模板
- 模板继承和扩展
- 模板参数化配置
- 模板版本管理
📊 智能规则扩展
规则扩展能力:
规则类型:
- workflow_rule: 工作流规则
- feature_rule: 功能规则
- intelligent_workflow_rule: 智能工作流规则
- safety_rule: 安全规则
规则配置:
- 优先级设置和冲突解决
- 触发条件和激活场景
- 集成配置和依赖管理
- 性能优化和缓存策略
规则验证:
- 语法和格式验证
- 逻辑一致性检查
- 性能影响评估
- 安全风险评估
🔄 AI Workflow Process - AI工作流程
Phase 1: 需求分析阶段
Step 1 - 需求收集:
- 分析用户描述和需求
- 识别重复性操作模式
- 评估自动化潜力
- 确定命令类型和范围
Step 2 - 上下文分析:
- 获取项目上下文信息 (context-loader集成)
- 分析现有命令和规则
- 识别相关工具和依赖
- 评估集成复杂度
Step 3 - 模板选择:
- AI推荐最适合的模板
- 分析模板适用性
- 评估定制化需求
- 确定开发策略
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 · 702 lines · 4,841 tokens per session scan A 39d3953ccb30
custom-command-builder is a cursor rule published in the GitHub repository Mr-chen-05/rules-2.1-optimized (172 stars, last pushed 11mo ago), licensed MIT. It adds 4,841 tokens to every session, about $0.0194 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.
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