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/intelligent-workflow-orchestrationgit 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/intelligent-workflow-orchestration)<a href="https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/intelligent-workflow-orchestration"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/intelligent-workflow-orchestration.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 5.1 | $0.00000 | $0.02528 |
| Opus 5 | $0.00000 | $0.01264 |
| Sonnet 5 | $0.00000 | $0.00506 |
| Haiku 4.5 | $0.00000 | $0.00253 |
Grade A, and why
intelligent-workflow-orchestration 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 5d 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 — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🚀 企业级智能工作流编排系统
企业级工作流: 专为大型团队(10+人员)和复杂企业项目设计的高级智能编排系统
🎯 系统概述
适用范围:
- ✅ 大型团队协作 (10+ 人员)
- ✅ 复杂微服务架构
- ✅ 多项目并行管理
- ✅ 企业级CI/CD流程
- ✅ 跨部门协作项目
不适用范围:
- ❌ 小型项目 (< 5人团队) → 请使用
intelligent-project-management.mdc - ❌ 简单单体应用 → 请使用
intelligent-project-management.mdc - ❌ 个人项目 → 请使用
intelligent-project-management.mdc
基于2025年AI代理发展趋势，实现企业级复杂工作流的自主编排和性能优化。
🧠 企业级智能代理核心能力
企业级自主能力矩阵:
高级推理能力:
- 复杂上下文理解和分析
- 多项目关联分析
- 企业级约束识别
- 战略目标对齐
企业级规划能力:
- 大规模任务分解和编排
- 跨部门资源协调
- 复杂依赖关系管理
- 企业级里程碑规划
高级执行能力:
- 企业级工具链编排
- 大规模并行协调
- 智能异常处理
- 企业级质量控制
组织学习能力:
- 企业知识管理
- 跨项目经验复用
- 组织策略优化
- 企业知识图谱构建
🚀 高级工作流架构
基础项目启动: 请使用
intelligent-project-management.mdc中的 "启动超级大脑系统" 命令
📋 企业级工作流增强
适用场景:
- 大型团队协作 (10+ 人员)
- 复杂微服务架构
- 多项目并行管理
- 企业级CI/CD流程
- 跨部门协作项目
🎯 企业级任务编排引擎
大规模任务编排策略:
企业级分析维度:
- 跨部门影响评估
- 企业级业务价值分析
- 合规性风险评定
- 大规模资源协调
- 长期战略对齐
高级编排算法:
- 企业级历史数据挖掘
- 组织能力建模
- 跨项目依赖优化
- 企业级并行度最大化
- 风险传播分析
企业级动态调整:
- 多项目进度协调
- 企业级资源重分配
- 战略优先级调整
- 组织变更适应
注意: 基础任务分解请使用 intelligent-project-management.mdc
🔄 智能执行编排
执行编排策略:
并行执行优化:
- 无依赖任务并行处理
- 资源冲突检测和避免
- 负载均衡和调度
- 性能瓶颈识别
工具链智能选择:
- 任务特性分析
- 工具能力匹配
- 性能效率评估
- 故障恢复能力
质量控制集成:
- 实时代码质量检查
- 自动化测试触发
- 安全扫描集成
- 性能基准验证
🎨 智能开发模式
🏗️ 架构设计智能助手
架构智能分析:
需求理解:
- 业务需求自动解析
- 非功能性需求识别
- 约束条件分析
- 扩展性需求预测
架构推荐:
- 基于需求的架构模式推荐
- 技术栈最优组合建议
- 性能优化策略
- 安全架构设计
设计验证:
- 架构一致性检查
- 性能影响评估
- 可维护性分析
- 成本效益评估
💻 智能编码助手
编码智能支持:
代码生成:
- 基于规范的代码模板生成
- 业务逻辑自动实现
- 测试用例自动生成
- 文档自动同步
代码优化:
- 性能瓶颈自动识别
- 代码重构建议
- 最佳实践应用
- 安全漏洞检测
协作支持:
- 代码冲突预测和解决
- 代码审查自动化
- 知识共享和传递
- 技能差距识别
🧪 智能测试编排
测试智能化:
测试策略:
- 风险驱动的测试优先级
- 测试覆盖率智能优化
- 测试数据自动生成
- 测试环境自动配置
执行优化:
- 并行测试执行
- 失败测试快速定位
- 回归测试智能选择
- 性能测试自动化
结果分析:
- 测试结果智能分析
- 质量趋势预测
- 缺陷模式识别
- 改进建议生成
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.
- 5d ago First seen · 372 lines · 0 tokens per session scan A de381b47b7db
intelligent-workflow-orchestration 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 2,528 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
ponytail
Ponytail, lazy senior dev mode. Always pick the simplest solution that works.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
control-plane-descriptors
Control plane descriptor and instance implementation patterns.