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 agentmods add skills/ryanzhao1011/workframe/systematic-debuggingnpx skills add ryanzhao1011/workframe --skill systematic-debugginggit clone --depth 1 https://github.com/ryanzhao1011/workframeWhat 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 | $0.00040 | $0.01614 |
| Opus 5 | $0.00020 | $0.00807 |
| Sonnet 5 | $0.00008 | $0.00323 |
| Haiku 4.5 | $0.00004 | $0.00161 |
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 yesterday.
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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
系统化调试技能
产物去向
RCA / 调试结论默认只在响应中呈现。需要留痕时：修复本身进 commit message；
值得跨需求复用的根因结论按 skill: document-norms §1 落 <sub>/decisions/；
线上故障走 projects/issues/BUG-*.yaml。不默认写文件。
适用场景
- @dev 收到 Bug/Issue 报告时（来自 @qa、用户反馈、线上监控等）
- 禁止"头痛医头脚痛医脚"式的随意修改
核心原则
先理解，再修复。修复前必须能回答三个问题：
- 为什么会出现这个 Bug？（根因）
- 这个修复会不会引入新 Bug？（影响面）
- 修复后如何验证确实修好了？（回归）
五步流程
第 1 步：复现确认
目标：确认问题存在且能稳定复现。
| 步骤 | 动作 |
|---|---|
| 读取 Issue | 从 projects/issues/{issue-id}.yaml 读取问题描述、复现步骤（issue-id 是全局唯一扁平 ID，例：BUG-001 / SEC-001；issues 目录是扁平结构，不按模块分子目录） |
| 解析归属 | 读取 Issue 的 area / module / component / spec_ref 字段，决定影响面分析的起点（例：area=backend, module=auth 提示先排查 auth 模块代码与相关 spec） |
| 构造复现条件 | 按 Issue 描述构造输入数据、执行环境、操作序列 |
| 执行复现 | 运行并观察实际输出 vs 期望输出 |
| 复现结论 | ✅ 能稳定复现 / ⚠️ 偶发 / ❌ 无法复现 |
如果无法复现：
- 向 Issue 报告者询问更详细的复现步骤
- 检查环境差异（版本、配置、数据）
- 不要立即关闭 Issue——保持
status: open，把「待补充的复现信息」写进 issue 的复现步骤/描述字段（issue schema 无 tags 字段，见projects/issues/TEMPLATES.md）
第 2 步：根因分析（RCA）
目标：定位问题代码并理解"为什么会出错"。
## 根因分析
### 症状
{Bug 的外在表现}
### 触发路径
{代码执行的调用链：A → B → C → 出错}
### 根因
{具体哪行代码、哪个逻辑导致问题}
### 为什么会写成这样
{原作者的意图 / 遗漏的边界条件 / 错误的假设}
### 为什么之前没暴露
{之前的使用场景为何没触发此问题}
第 3 步：影响面评估
目标：评估修复可能波及的其他模块（Blast Radius）。
| 评估维度 | 说明 |
|---|---|
| 代码依赖 | 谁调用了这段出错代码？改动后他们会受影响吗？ |
| 数据影响 | 修复会改变数据结构/存储吗？老数据需要迁移吗？ |
| 接口变更 | 是否改变了对外 API 行为？调用方需要知晓吗？ |
| 性能影响 | 修复引入的新逻辑是否影响性能？ |
| 安全影响 | 修复是否引入新的安全隐患？ |
第 4 步：修复与自测
目标：执行修复并验证修复有效。
- 实施修复：最小范围修改，不做无关重构
- 复现步骤重跑：确认原问题不再出现
- 边界测试：测试修复逻辑的边界条件（空值、极值、并发等）
- 影响面验证：对 Step 3 识别的影响模块做快速验证
第 5 步：回归标注
目标：为 @qa 标注此次修复的回归测试要点。
## 回归测试要点
### 必测（直接相关）
- [ ] 原 Bug 复现场景已修复
- [ ] 修复代码的边界条件测试
### 建议测（影响面）
- [ ] {被影响的模块 A}
- [ ] {被影响的模块 B}
### 关注点（潜在风险）
- {需要长期观察的性能/稳定性指标}
输出模板
## RCA 报告：{Issue-ID}
### 1. 复现确认
- 复现结果：{✅ 稳定复现 / ⚠️ 偶发 / ❌ 无法复现}
- 复现步骤：{...}
### 2. 根因分析
- 症状：{...}
- 触发路径：{...}
- 根因：{具体代码位置 + 错误逻辑}
- 为什么会写成这样：{...}
### 3. 影响面评估
- 代码依赖：{...}
- 数据影响：{...}
- 接口变更：{...}
### 4. 修复方案
- 修改文件：{路径}
- 修改内容：{具体改动}
- 自测结果：{...}
### 5. 回归测试要点
- 必测：{...}
- 建议测：{...}
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.
- yesterday First seen · 157 lines · 40 tokens per session scan A 32d8574dd905
systematic-debugging is a skill published in the GitHub repository ryanzhao1011/workframe (4 stars, last pushed 14d ago), licensed MIT. It adds 40 tokens to every session and 1,614 once invoked, about $0.0002 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 2026-08-31.
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