What is systematic-debugging?

A structured debugging guide for finding causes of software errors, including syntax, runtime, logic, environment, and security problems. It defines commands such as /debug and modes for tracing, performance, and automatic fixes.

Use it to investigate stack traces, dependency conflicts, deadlocks, configuration failures, performance issues, or security-related bugs.

It gives agents a repeatable way to inspect errors and narrow down their causes instead of applying random changes.

systematic-debugging — Cursor rule by Mr-chen-05

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/systematic-debugging

Clone the repo

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

Per session 3,887 This file is loaded in full into every session.

When invoked 3,887 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	$0.03887	$0.03887
Opus 5	$0.01944	$0.01944
Sonnet 5	$0.00777	$0.00777
Haiku 4.5	$0.00389	$0.00389

Measured 2d ago against content hash ce939fe2055a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

project-rules/systematic-debugging.mdc · 583 lines

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

Read the full file on GitHub · 583 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.

2d ago First seen · 583 lines · 3,887 tokens per session scan A ce939fe2055a

Subscribe to this mod's changes

systematic-debugging is a cursor rule published in the GitHub repository Mr-chen-05/rules-2.1-optimized (172 stars, last pushed 9mo ago), licensed MIT. It adds 3,887 tokens to every session, about $0.0194 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.

Debugging Research Security

systematic-debugging