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/systematic-debugging)<a href="https://agentmods.dev/rules/mr-chen-05/rules-2.1-optimized/systematic-debugging"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/systematic-debugging/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/systematic-debugging"><img src="https://agentmods.dev/badge/rules/mr-chen-05/rules-2.1-optimized/systematic-debugging.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 | $0.03887 | $0.03887 |
| Opus 5.5 | $0.01555 | $0.01555 |
| Sonnet 5.5 | $0.00777 | $0.00777 |
| Haiku 4.5 | $0.00389 | $0.00389 |
Grade A, and why
systematic-debugging 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 — 583 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🐛 Systematic Debugging - 智能系统化调试
AI驱动的系统化调试工具,集成智能故障诊断、自动化调试流程和解决方案推荐引擎。
🧠 AI Intelligence Core - AI智能核心
智能激活条件
自动激活场景:
- 检测到代码执行错误或异常
- 用户执行 "/debug" 命令
- code-quality-check发现严重Bug
- root-cause-analysis需要深度调试
- 超级大脑系统推荐系统化调试
智能分析维度:
- 错误类型和严重程度 (30%)
- 代码复杂度和调试难度 (25%)
- 系统环境和依赖关系 (20%)
- 历史调试经验匹配 (15%)
- 调试工具可用性 (10%)
🚀 Commands - 智能命令
/debug- AI智能系统化调试(推荐)/debug --error <type>- 指定错误类型调试/debug --trace- 执行跟踪调试/debug --performance- 性能调试模式/debug --security- 安全问题调试/debug --auto-fix- 自动修复调试
✨ AI-Powered Features - AI驱动功能
🤖 智能故障诊断引擎
错误类型识别:
语法错误:
- 编译时错误
- 语法解析错误
- 类型不匹配
- 缺少依赖
运行时错误:
- 空指针异常
- 数组越界
- 内存泄露
- 死锁问题
逻辑错误:
- 算法逻辑错误
- 业务逻辑缺陷
- 数据处理错误
- 状态管理问题
环境错误:
- 配置错误
- 依赖版本冲突
- 权限问题
- 网络连接问题
智能诊断能力:
- 错误堆栈智能分析
- 异常模式识别
- 相关代码定位
- 影响范围评估
🔧 自动化调试工具集成
调试工具编排:
前端调试:
- Chrome DevTools
- React Developer Tools
- Vue.js DevTools
- Browser Console
后端调试:
- Node.js Inspector
- Python Debugger (pdb)
- Java Debugger (jdb)
- .NET Debugger
数据库调试:
- SQL Query Analyzer
- Database Profiler
- Connection Pool Monitor
- Transaction Analyzer
性能调试:
- Memory Profiler
- CPU Profiler
- Network Monitor
- I/O Analyzer
📋 Debugging Categories - 调试分类
🔴 Critical Debugging - 致命调试
系统崩溃:
- 应用程序崩溃
- 服务器宕机
- 数据库连接失败
- 内存溢出
调试策略:
- 立即错误定位
- 紧急恢复方案
- 核心转储分析
- 系统状态快照
🟠 High Priority Debugging - 高优先级调试
功能故障:
- 核心功能异常
- API接口错误
- 数据处理失败
- 用户操作阻塞
调试策略:
- 功能流程跟踪
- 数据流分析
- 接口调用监控
- 用户行为重现
🟡 Medium Priority Debugging - 中优先级调试
性能问题:
- 响应时间慢
- 内存使用高
- CPU占用率高
- 网络延迟
调试策略:
- 性能瓶颈分析
- 资源使用监控
- 代码热点识别
- 优化建议生成
🟢 Low Priority Debugging - 低优先级调试
体验问题:
- 界面显示异常
- 交互响应慢
- 功能使用不便
- 错误提示不清
调试策略:
- 用户体验分析
- 界面渲染检查
- 交互流程优化
- 错误信息改进
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 · 583 lines · 3,887 tokens per session scan A ce939fe2055a
systematic-debugging 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 3,887 tokens to every session, about $0.0155 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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