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 skills add Nikolahuang/nova-cli --skill systematic-debugginggit clone --depth 1 https://github.com/Nikolahuang/nova-cliWrote 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/skills/nikolahuang/nova-cli/systematic-debugging)<a href="https://agentmods.dev/skills/nikolahuang/nova-cli/systematic-debugging"><img src="https://agentmods.dev/badge/skills/nikolahuang/nova-cli/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/skills/nikolahuang/nova-cli/systematic-debugging"><img src="https://agentmods.dev/badge/skills/nikolahuang/nova-cli/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 | $0.00031 | $0.00806 |
| Opus 5.5 | $0.00012 | $0.00322 |
| Sonnet 5.5 | $0.00006 | $0.00161 |
| Haiku 4.5 | $0.00003 | $0.00081 |
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.
What it actually says
系统化调试 - 4 阶段根因分析
概述
使用结构化的 4 阶段流程系统化地找出并修复 bug，而不是靠猜测。
阶段 1: 复现和理解
复现问题
- 记录确切的复现步骤
- 确定是否可稳定复现
- 记录环境信息（OS、版本、配置）
- 记录错误消息和堆栈跟踪
理解期望行为
- 期望发生什么？
- 实际发生了什么？
- 差异是什么？
收集信息
- 使用
read_file查看相关代码 - 使用
search_content查找相关逻辑 - 使用
execute_command运行诊断命令
阶段 2: 隔离
缩小范围
- 二分法：哪一半代码有问题？
- 注释掉代码块，看问题是否消失
- 创建最小复现示例
检查边界
- 输入边界（空值、最大值、最小值）
- 状态边界（初始化、中间、结束）
- 时间边界（竞态、超时）
验证假设
- 每次只改变一个变量
- 记录每次测试的结果
- 不要同时修复多个问题
阶段 3: 根因分析
5 个为什么
对每个发现问"为什么"，深入到根本原因：
问题: X 发生了
为什么? → 因为 Y
为什么? → 因为 Z
为什么? → 因为 [根本原因]
常见根因模式
- 状态错误: 变量值不正确
- 时序问题: 竞态、死锁
- 边界遗漏: 未处理边界情况
- 配置错误: 配置不匹配
- 依赖问题: 版本不兼容
根因追踪技术
- 添加日志追踪变量值
- 使用调试器逐步执行
- 检查最近的代码变更
阶段 4: 修复和验证
修复原则
- 最小化改动 - 只修改必要的
- 不引入新功能
- 保持代码风格一致
验证修复
- 原问题是否修复？
- 是否引入新问题？
- 边缘情况是否处理？
- 相关测试是否通过？
深度防御
- 添加验证和断言
- 添加错误处理
- 记录限制和假设
文档化
- 记录问题原因
- 记录修复方案
- 更新相关文档
调试反模式
避免这些：
- ❌ 随机修改代码看效果
- ❌ 复制粘贴修复而不理解
- ❌ 忽略偶发问题
- ❌ 同时修改多处
关键原则
- 系统化 - 有条理地排除可能性
- 证据驱动 - 基于证据而非猜测
- 一次一个变量 - 控制变量
- 记录过程 - 便于回溯和学习
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 · 110 lines · 31 tokens per session scan A 677c1a6eaaa9
systematic-debugging is a skill published in the GitHub repository Nikolahuang/nova-cli (14 stars, last pushed 6mo ago), licensed MIT. It adds 31 tokens to every session and 806 once invoked, about $0.0001 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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