What is system-integration-config?

A set of Chinese rules for coordinating several AI systems, including requirement analysis, memory, recommendations, project management, and workflow control. It describes their roles, priorities, dependencies, and expected coordination.

Use it when organising multi-step AI workflows, interpreting requirements, managing project stages, retrieving stored context, selecting tools, or handling failures.

It gives an agent a defined way to decide which system should handle a request and how the systems should work together.

system-integration-config — Cursor rule for coding agents by Mr-chen-05: A set of Chinese rules for coordinating several AI…

Install

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.

agentmods

npx agentmods add rules/mr-chen-05/rules-2.1-optimized/system-integration-config

Clone the repo

git clone --depth 1 https://github.com/Mr-chen-05/rules-2.1-optimized

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/system-integration-config.svg)](https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/system-integration-config)

Your own site

<a href="https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/system-integration-config"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/system-integration-config.svg" alt="Measured on agentmods" height="20"></a>

Per session 6,661 This file is loaded in full into every session.

When invoked 6,661 The same file — it is already loaded in full.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.06661	$0.06661
Opus 5	$0.03331	$0.03331
Sonnet 5	$0.01332	$0.01332
Haiku 4.5	$0.00666	$0.00666

Measured 4d ago against content hash d4ec66606d7c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

system-integration-config 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 4d 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.

global-rules/system-integration-config.mdc · 757 lines

How it starts

The opening of the file, as written. The whole thing — 757 lines — stays where its author put it; the contents beside it link to each section on GitHub.

⚙️ 系统集成配置

统一协调: 确保超级大脑、项目管理、记忆系统和推荐引擎的无缝集成和协同工作

🎯 集成架构概述

智能系统组件关系

核心组件架构:
  超级大脑系统 (优先级: 960):
    角色: 统一管理和决策中心
    功能: 系统激活、状态监控、决策支持、智能推理
    依赖: 项目管理、记忆系统、推荐引擎、需求理解引擎
    智能特性: 自适应学习、多模态理解、上下文感知
  
  需求理解引擎 (优先级: 950):
    角色: 智能需求解析和澄清
    功能: 自然语言解析、多轮对话澄清、需求完整性验证
    依赖: 超级大脑、记忆系统、深度讨论框架
    智能特性: 语义理解、意图识别、智能问题生成
  
  深度讨论框架 (优先级: 945):
    角色: 结构化讨论管理和引导
    功能: 讨论管理、话题引导、质量评估、共识达成
    依赖: 需求理解引擎、记忆系统、推荐引擎
    智能特性: 动态策略调整、智能总结、知识提取
  
  记忆系统 (优先级: 940):
    角色: 信息存储和智能检索
    功能: 记忆管理、上下文感知、经验积累、知识图谱
    依赖: context7、codebase-retrieval（server-memory 可选）
    智能特性: 语义搜索、自动关联、持续学习
  
  推荐引擎 (优先级: 930):
    角色: 智能决策支持和预测分析
    功能: 阶段推荐、工具选择、策略优化、风险预警
    依赖: 记忆系统、项目状态、所有MCP工具
    智能特性: 个性化推荐、预测分析、实时优化
  
  项目管理系统 (优先级: 900):
    角色: 智能项目生命周期管理
    功能: 阶段管理、工作流编排、质量保证、成功跟踪
    依赖: 记忆系统、推荐引擎、MCP工具、超级大脑
    智能特性: 自动阶段切换、智能工具协同、实时监控
  
  工作流集成 (优先级: 920):
    角色: 智能完整生命周期管理
    功能: 端到端流程、质量标准、工具编排、异常恢复
    依赖: 所有其他系统
    智能特性: 动态流程调整、智能资源分配、自动故障恢复
  
  MCP策略 (优先级: 800):
    角色: 智能工具使用策略
    功能: 工具选择、效率优化、最佳实践、自动集成
    依赖: 智能系统指导、工作流集成
    智能特性: 使用模式学习、性能优化、智能故障转移

智能组件详细映射

智能系统组件映射:
  超级大脑系统:
    组件: ai-agent-intelligence-core.mdc
    功能: 
      - 智能决策和推理
      - 系统协调和监控
      - 预测性分析
    接口: 
      - 决策API、推理API
      - 协调API、监控API
      - 预测API、学习API
    智能特性:
      - 自适应学习和优化
      - 多模态理解和处理
      - 上下文感知和记忆

  需求理解引擎:
    组件: 新增智能组件
    功能:
      - 自然语言需求解析
      - 多轮对话需求澄清
      - 需求完整性验证
      - 需求冲突检测和解决
    接口:
      - 需求解析API、澄清对话API
      - 完整性验证API、冲突解决API
      - 需求跟踪API、变更管理API
    依赖: 超级大脑、记忆系统、mcp-feedback-enhanced
    智能特性:
      - 语义理解和意图识别
      - 上下文感知对话
      - 智能问题生成

  深度讨论框架:
    组件: 新增智能组件
    功能:
      - 结构化讨论管理
      - 智能话题引导
      - 讨论质量评估
      - 共识达成辅助
    接口:
      - 讨论管理API、话题引导API
      - 质量评估API、共识辅助API
      - 总结生成API、知识提取API
    依赖: 需求理解引擎、记忆系统、推荐引擎
    智能特性:
      - 动态讨论策略调整
      - 智能内容总结
      - 自动知识提取

  增强记忆系统（可选）:
    组件: memory 服务器 + 智能索引
    功能: 
      - 结构化信息存储和检索
      - 语义搜索和关联分析
      - 知识图谱构建和维护
      - 经验学习和模式识别
    接口: 
      - 智能存储API、语义检索API
      - 关联分析API、知识图谱API
      - 学习API、模式识别API
    依赖: context7、codebase-retrieval
    智能特性:
      - 自动知识提取和组织
      - 智能关联和推荐
      - 持续学习和优化

  智能推荐引擎:
    组件: intelligent-recommendation-engine.mdc + AI增强
    功能: 
      - 个性化智能推荐
      - 预测性建议和优化
      - 最佳实践识别和应用
      - 风险预警和缓解建议
    接口: 
      - 智能推荐API、预测分析API
      - 最佳实践API、风险评估API
      - 个性化API、优化建议API
    依赖: 记忆系统、超级大脑、所有MCP工具
    智能特性:
      - 多维度数据分析
      - 机器学习驱动推荐
      - 实时适应和优化

  智能项目管理系统:
    组件: context-systems-integration.mdc
    功能: 
      - 五阶段智能工作流管理
      - 智能MCP工具编排
      - 质量保证和监控
      - 成功指标跟踪
    接口: 
      - 智能工作流API、状态监控API
      - 工具编排API、质量评估API
      - 指标分析API、优化建议API
    依赖: 超级大脑、MCP策略、记忆系统
    智能特性:
      - 自动阶段切换和优化
      - 智能工具选择和协同
      - 实时质量监控和改进

  智能工作流集成:
    组件: context-systems-integration.mdc + 智能调度
    功能: 
      - 智能阶段间协调和管理
      - 自适应流程优化
      - 异常检测和自动恢复
      - 性能监控和调优
    接口: 
      - 智能协调API、自适应管理API
      - 异常处理API、性能监控API
      - 流程优化API、调度API
    依赖: 所有其他组件
    智能特性:
      - 动态流程调整
      - 智能资源分配
      - 自动故障恢复

  智能MCP策略:
    组件: 各种MCP服务器 + 智能编排引擎
    功能: 
      - 智能工具选择和编排
      - 自适应工具协同
      - 性能监控和优化
      - 新工具自动集成
    接口: 
      - 智能工具API、编排优化API
      - 协同管理API、性能分析API
      - 集成API、监控API
    依赖: 工作流集成、推荐引擎
    智能特性:
      - 工具使用模式学习
      - 自动性能优化
      - 智能故障转移

Read the full file on GitHub · 757 lines

Changes

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.

4d ago First seen · 757 lines · 6,661 tokens per session scan A d4ec66606d7c

Subscribe to this mod's changes

system-integration-config 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 adds 6,661 tokens to every session, about $0.0333 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.

system-integration-config

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

⚙️ 系统集成配置

🎯 集成架构概述

智能系统组件关系

智能组件详细映射

What this file has done since we first saw it

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