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 lync-cyber/CataForge --skill debuggit clone --depth 1 https://github.com/lync-cyber/CataForgeWrote 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/lync-cyber/cataforge/debug)<a href="https://agentmods.dev/skills/lync-cyber/cataforge/debug"><img src="https://agentmods.dev/badge/skills/lync-cyber/cataforge/debug/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/lync-cyber/cataforge/debug"><img src="https://agentmods.dev/badge/skills/lync-cyber/cataforge/debug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.01465 |
| Opus 5.5 | $0.00040 | $0.00586 |
| Sonnet 5.5 | $0.00020 | $0.00293 |
| Haiku 4.5 | $0.00010 | $0.00146 |
Grade A, and why
debug 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
调试诊断 (debug)
能力边界
- 能做: 分析错误/stacktrace、定位根因、应用最小修复、回归验证、检查同类问题
- 不做: 功能开发、性能优化、架构重构、需求变更
输入规范
调用方提供以下信息（至少一项）:
- 错误信息 / stacktrace
- 触发命令或复现步骤
- 期望 vs 实际行为描述
输出规范
- 修复后的文件（就地修改）
- 回归验证结果（测试通过或命令成功）
- 执行摘要: 根因 + 修复措施 + 验证结果
操作指令
语言细则: 根据
framework.jsonproject.languages，按需载入本 skillreferences/lang-<lang>.md（仅 active 语言，逐个 Read），获取对应语言的调试诊断细则（调试器使用、traceback 解读、日志实践、运行时问题定位）。与本 skillreferences/debug-patterns.md（scan-similar 的特征模式范例）分工：lang-.md 为完整调试细则，debug-patterns 为同类扫描的模式库。
指令1: 完整调试流程 (full)
适用于: 收到错误报告，需要从零开始诊断和修复。
Step 1: 复现与信息收集
- 解析错误信息，提取关键信号: 文件路径、行号、异常类型、错误消息
- 如有复现命令，执行以确认问题可复现
- 如错误信息不完整（缺少 stacktrace 或文件路径），通过 AskUserQuestion 请求补充（每批问题数不超过 MAX_QUESTIONS_PER_BATCH）
Step 2: 定位根因
- 从 stacktrace 最内层帧开始，Read 相关文件和行号
- 向调用链上游追溯，理解数据流和控制流
- 识别根因类别:
- 编码/环境: 字符编码、路径分隔符、平台差异、语言运行时版本
- 数据/类型: 空值、类型不匹配、格式解析错误、边界条件
- 依赖/配置: 缺失依赖、版本不兼容、配置错误
- 逻辑: 算法错误、状态管理、竞态条件
- 形成根因假设并通过代码阅读或小范围测试验证
Step 3: 应用修复
- 使用 Edit 工具应用最小化修复（只改必要的代码）
- 如修复模式适用于多个文件，使用 Grep 扫描同类问题并一并修复
- 确保修复不改变公共接口行为（如需改变，返回 needs_input）
Step 4: 回归验证
- 重新执行触发错误的命令，确认问题已修复
- 运行相关测试套件（如有），确认未引入新失败
- 如无自动化测试，手动验证关键路径
Step 5: 总结
- 输出执行摘要: 根因（一句话）、修复措施、验证结果、同类修复（如有）
指令2: 快速修复 (quick-fix)
适用于: 根因已明确（如用户已定位到具体文件和行），剩余动作仅为应用修复和验证。
Step 1: Read 相关文件确认问题 Step 2: 应用修复（Edit） Step 3: Grep 检查同类问题并一并修复 Step 4: 回归验证（Bash 运行命令/测试） Step 5: 输出摘要
指令3: 同类扫描 (scan-similar)
适用于: 已修复一个问题，需要检查整个项目中是否存在同类问题。
Step 1: 从已修复的问题中提取特征模式（如未显式声明编码的文件读写、未转义的正则元字符；语言特定示例见 debug-patterns.md） Step 2: 使用 Grep 在项目范围内搜索该模式 Step 3: 逐一检查匹配项，判断是否存在同类问题 Step 4: 对确认存在问题的文件应用修复 Step 5: 汇总扫描结果: 检查了 N 个文件，修复了 M 个
常见问题模式库
语言/平台特定的症状—修复对照（Python/Windows 等）见 debug-patterns.md，新增语言在该文档增条。
Anti-Patterns
- 禁止: 修复表面 symptom 而不查 root cause —— 让最近一次报错消失不等于修了 bug，root_cause 可能在两层调用栈以上
- 禁止: 改测试让它通过而非改实现 —— 测试是契约，把红灯绿掉是把契约改成了已坏状态的快照
- 禁止: 静默
catch + pass吞异常 —— 信号被埋掉后续 debug 复杂度指数上升 - 避免: 一次改多个变量再跑验证 —— 失败时无法定位是哪个改动生效，回到二分查找
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 97 lines · 99 tokens per session scan A 6cef5efa3018
debug is a skill published in the GitHub repository lync-cyber/CataForge (128 stars, last pushed 2mo ago), licensed MIT. It adds 99 tokens to every session and 1,465 once invoked, about $0.0004 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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