Token导航 LogoToken导航

Agent Skill · 研究检索

debugging-protocol(调试协议)

debugging-protocol 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

debugging-protocol 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 32,766。

总安装 2,471周安装 99GitHub Stars 2下载 1,136核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:debugging-protocol(调试协议)
来源仓库:https://github.com/jwilger/agent-skills
仓库路径:skills/debugging-protocol
安装命令:
npx skills add https://github.com/jwilger/agent-skills --skill debugging-protocol
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jwilger/agent-skills --skill debugging-protocol

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

该技能建立四阶段调试纪律,确保理解问题本质后再尝试修复方案。适用于任何需要避免盲目修改代码的技术问题场景。通过 GitHub 仓库安装,需严格遵守'无调查不修复'的核心原则。建议将每次失败尝试计入三次阈值,超限时重新评估整体策略。

debugging-protocol 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/debugging-protocol

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jwilger/agent-skills --skill debugging-protoco…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

debugging-protocol 怎么安装?

在终端执行 npx skills add https://github.com/jwilger/agent-skills --skill debugging-protocol。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

debugging-protocol 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

debugging-protocol 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

debugging-protocol 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

debugging-protocol 用的人多吗?

公开数据是累计安装 2,471 次,近一周安装 99 次,下载 1,136 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

debugging-protocol 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
debugging-protocol

调试协议 · 本页

2,4712调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Debugging Protocol

Value: Feedback -- systematic investigation produces understanding. Understanding produces correct fixes. Correct fixes prevent recurrence. Skipping investigation produces symptom fixes that hide bugs.

Purpose

Teaches a disciplined 4-phase debugging process that enforces root cause analysis before any fix attempt. Prevents the most common debugging failure mode: jumping to a fix without understanding why the problem exists.

Practices

The Iron Law: No Fixes Without Investigation

Never change code to fix a bug until you have completed root cause investigation. When you see an error and immediately know the fix, that is exactly when you are most likely to be wrong. Investigate first.

Do:

  • Read the complete error message and stack trace before doing anything else
  • Reproduce the bug consistently before investigating
  • Understand WHY something is broken, not just WHAT is broken

Do not:

  • Add a null check because you see a null pointer error (symptom fix)
  • Try "a few things" to see what sticks (random debugging)
  • Skip investigation because "this is an easy one"

Phase 1: Understand the Failure

Gather facts. Do not interpret yet.

  1. Read the full error message -- every line, not just the first
  2. Identify the exact file and line where the failure occurs
  3. Reproduce the failure consistently (if it does not reproduce, that is important information)
  4. Check recent changes: git log --oneline -10 and git diff
  5. Note the data flow: where does the bad value come from?

Output: A clear statement of what is happening, where, and since when.

Phase 2: Find Working Examples

Compare broken against working. The difference is the bug.

  1. Find similar code that works correctly
  2. Compare setup, inputs, state, and configuration
  3. Identify what differs between the working and failing case
  4. Check dependencies: did a library update? Did an environment change?

Output: A specific difference between working and failing cases.

Phase 3: Test One Hypothesis

Form a single, explicit hypothesis. Test it with one change. Learn from the result.

  1. State the hypothesis: "I believe the bug is caused by [X] because [evidence]"
  2. Make ONE change to test it
  3. Observe the result
  4. If the hypothesis is wrong, UNDO the change completely
  5. Form a new hypothesis incorporating what you learned

Do not change multiple things at once. If you change the import, the type, and the logic simultaneously, you cannot know which change mattered.

Output: Confirmed or refuted hypothesis with evidence.

Phase 4: Fix and Verify

Fix with confidence because you understand the root cause.

  1. Write a failing test that reproduces the bug (if one does not already exist)
  2. Implement the fix targeting the root cause identified in Phase 3
  3. Verify: the new test passes, all existing tests still pass
  4. Confirm you fixed the cause, not the symptom

Output: A fix backed by a test, with all tests green.

Escalation: Three Strikes Rule

If three fix attempts fail, stop. The problem is not what you think it is.

After the third failure:

  1. Stop attempting fixes entirely
  2. Document what you tried and why each attempt failed
  3. Question your assumptions: wrong abstraction? Wrong domain model? Wrong problem entirely?
  4. Seek a broader perspective -- architecture review, domain expert, or escalate to the user

Three failed fixes almost always signal a design problem, not a code problem. More code fixes will not help.

Example:

Attempt 1: Add caching (hypothesis: slow queries) -> Still slow
Attempt 2: Add index (hypothesis: missing index) -> Still slow
Attempt 3: Eager loading (hypothesis: N+1) -> Still slow
STOP. Profile the system.
Result: 90% of time in external API call. Not a database problem at all.

Enforcement Note

  • Standalone mode: Advisory. The Iron Law is self-enforced.
  • Pipeline mode: Gating. Debugging evidence is required before fix commits pass the TDD gate.

Hard constraints:

  • Iron Law (investigate before fix): [H]
  • Three Strikes escalation: [RP]

Constraints

  • Iron Law: The temptation to skip investigation is strongest when the fix seems obvious. That is exactly when investigation is most valuable -- because "obvious" fixes that are wrong waste more time than investigation would have cost. If you're reasoning about why THIS bug is the exception that doesn't need investigation, you're violating the Iron Law.
  • Three Strikes: After three failed hypotheses, the problem is not what you think it is. "Stop" means stop fixing and return to investigation. It does not mean stop working entirely. Re-examine your assumptions, widen your investigation, look at adjacent systems. If you still can't identify the root cause, escalate.
  • Undo failed hypotheses: "Undo completely" means the codebase returns to exactly the state before the hypothesis was tested. Not "mostly undone with a few improvements kept." Not "undone in the main file but I left the debug logging." Every change from the failed hypothesis is reverted.

Verification

After debugging guided by this skill, verify:

  • Completed Phase 1 investigation before any code changes
  • Read the complete error message (not just the first line)
  • Reproduced the bug consistently
  • Found a working example to compare against
  • Stated an explicit hypothesis before each fix attempt
  • Made only one change per hypothesis test
  • Undid failed hypotheses before trying new ones
  • Wrote or confirmed a failing test before implementing the fix
  • Verified all tests pass after the fix
  • Did not exceed three fix attempts without escalating

If any criterion is not met, revisit the relevant phase.

Dependencies

This skill works standalone with no required dependencies. It integrates with:

  • tdd: When a test fails unexpectedly during TDD, this skill guides investigation before modifying code
  • user-input-protocol: When debugging reaches an ambiguous decision point, pause and ask the user rather than guessing
  • domain-modeling: If three fixes fail, the root cause may be a domain modeling problem -- escalate to domain review

Missing a dependency? Install with:

npx skills add jwilger/agent-skills --skill tdd

平台分布

Codex

34.33%
按下载量换算390

Claude

32.86%
按下载量换算373

Cursor

19.44%
按下载量换算221

Gemini CLI

9.34%
按下载量换算106

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills