systematic-debug
A structured debugging workflow requiring evidence-based hypothesis testing and minimal-impact fixes.
Install
mkdir -p .claude/skills/systematic-debug && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17534" && unzip -o skill.zip -d .claude/skills/systematic-debug && rm skill.zipInstalls to .claude/skills/systematic-debug
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
系统化调试技能 - 按证据驱动流程定位和修复bugKey capabilities
- →Collect evidence for bug reports (logs, stack traces, screenshots)
- →Narrow down the scope of a bug to specific files and functions
- →Formulate root-cause hypotheses for bugs
- →Verify hypotheses by adding log statements or checking tests
- →Implement minimal fixes for identified bugs
- →Validate fixes by running builds and existing tests
How it works
This skill guides a systematic debugging process, starting with evidence collection, narrowing the scope, formulating and verifying hypotheses, implementing minimal fixes, and finally validating the solution.
Inputs & outputs
When to use systematic-debug
- →Systematically debug bug
- →Analyze stack trace
- →Verify fix impact
- →Troubleshoot crashes
About this skill
系统化调试技能
当用户描述一个 bug 或异常行为时，按以下流程执行：
第一步：收集证据
- 让用户描述：预期行为 vs 实际行为
- 收集错误日志、堆栈跟踪、截图
- 确认复现条件（设备/操作步骤/频率）
- 用
grep_search在代码中搜索相关错误信息和关键字
第二步：缩小范围
- 根据错误信息定位到具体文件和函数
- 用
view_code_item阅读相关代码，理解调用链 - 画出调用链路：入口 → 中间层 → 出错点
- 识别可能的竞态条件、空值、类型错误
第三步：提出假设
- 列出 2-3 个最可能的根因假设
- 为每个假设说明：
- 为什么认为这是原因
- 如何验证/排除
- 按可能性排序
第四步：验证假设
- 添加日志语句验证假设（标记为
// DEBUG-TEMP） - 阅读相关测试文件，检查是否有覆盖
- 对比类似功能的正常实现（如果有）
- 如果项目有其他参考实现（如 nekobox），对比关键差异
第五步：实施修复
- 编写最小化修复（不要过度重构）
- 所有修改标注
// fix: [issue描述]注释 - 确保修复不引入新问题（检查调用方）
- 清理第四步添加的
// DEBUG-TEMP日志
第六步：验证修复
- 运行编译确认无语法错误
- 运行现有测试（如果有）
- 列出手动测试步骤让用户验证
- 检查边界情况和并发场景
注意事项
- 不要猜测：每一步都要基于代码证据
- 不要过度修复：只修改导致 bug 的代码，不要顺便重构
- 保留上下文：在 walkthrough 中记录发现和修复过程
- Android 特别注意：多进程通信、生命周期、主线程阻塞
When not to use it
- →When a bug fix requires extensive refactoring beyond minimal changes
Limitations
- →Emphasizes minimal fixes, not extensive refactoring
- →Requires evidence-based decisions at each step
- →Focuses on locating and fixing bugs, not general code improvements
How it compares
This skill provides a structured, evidence-driven approach to debugging, minimizing guesswork and ensuring thorough verification, which is more reliable than ad-hoc troubleshooting.
Compared to similar skills
systematic-debug side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| systematic-debug (this skill) | 0 | 5mo | No flags | Intermediate |
| godot | 1,044 | 4mo | Review | Intermediate |
| python-testing-patterns | 77 | 2mo | Review | Intermediate |
| error-handling-patterns | 35 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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