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Agent Skill · 研究检索

fault-diagnosis(故障诊断)

fault-diagnosis 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。

fault-diagnosis 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,权限为需要联网;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 63,725。

总安装 312周安装 13GitHub Stars 24下载 104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:fault-diagnosis(故障诊断)
来源仓库:https://github.com/noobygains/godmode
仓库路径:skills/fault-diagnosis
安装命令:
npx skills add https://github.com/noobygains/godmode --skill fault-diagnosis
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/noobygains/godmode --skill fault-diagnosis

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。

fault-diagnosis 提供严格的故障诊断流程,禁止在未查明根因前实施任何修复。适用于在 Codex、Claude、Cursor、Gemini CLI 中对测试失败、性能下降等异常进行处理。划分五个分析阶段:现象观察、假设提出、实验验证、结论确认与预防措施制定。

特别强调生产环境问题必须优先保障稳定性,避免激进修复引入新缺陷。所有诊断过程需留下可追溯的记录,便于团队协作与知识沉淀。

来源仓库内路径:skills/fault-diagnosis

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/noobygains/godmode --skill fault-diagnosis;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

    它需要需要联网,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

fault-diagnosis 怎么安装?

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

fault-diagnosis 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。

fault-diagnosis 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

fault-diagnosis 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。

fault-diagnosis 用的人多吗?

公开数据是累计安装 312 次,近一周安装 13 次,下载 104 次,GitHub 24 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。

fault-diagnosis 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
fault-diagnosis

故障诊断 · 本页

31224需要联网未明确通过

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

Fault Diagnosis

Overview

Guessing at fixes wastes time and introduces new defects. Quick patches mask underlying problems.

Core principle: ALWAYS identify root cause before attempting any fix. Treating symptoms is failure.

No exceptions. No workarounds. No shortcuts.

The Prime Directive

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you have not completed Phase 1, you are not authorized to propose fixes.

When to Use

Apply to ANY technical issue:

  • Test failures
  • Production bugs
  • Unexpected behavior
  • Performance degradation
  • Build failures
  • Integration breakdowns

Especially important when:

  • Under time pressure (urgency makes guessing tempting)
  • "Just one quick fix" seems obvious
  • You have already attempted multiple fixes
  • A previous fix did not resolve the issue
  • You do not fully understand the problem

Do not skip when:

  • The issue appears simple (simple bugs have root causes too)
  • You are in a hurry (systematic investigation is faster than flailing)
  • Someone wants it resolved NOW (methodical work is faster than thrashing)

The Four Phases

You MUST complete each phase before advancing to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

  1. Read Error Messages Thoroughly

- Do not skip past errors or warnings - They frequently contain the exact answer - Read stack traces completely - Note line numbers, file paths, error codes

  1. Reproduce Reliably

- Can you trigger it consistently? - What are the exact reproduction steps? - Does it happen every time? - If not reproducible, gather more data -- do not guess

  1. Examine Recent Changes

- What changed that could cause this? - Git diff, recent commits - New dependencies, configuration changes - Environmental differences

  1. Gather Evidence in Multi-Component Systems WHEN the system has multiple components (CI -> build -> signing, API -> service -> database): BEFORE proposing fixes, add diagnostic instrumentation: For EACH component boundary: - Log what data enters the component - Log what data exits the component - Verify environment/config propagation - Check state at each layer Run once to collect evidence showing WHERE it breaks THEN analyze evidence to identify the failing component THEN investigate that specific component Example (multi-layer system): # Layer 1: Orchestrator echo "=== Orchestrator state: ===" echo "TOKEN: ${TOKEN:+SET}${TOKEN:-UNSET}" # Layer 2: Build script echo "=== Build environment: ===" env | grep TOKEN || echo "TOKEN not in environment" # Layer 3: Signing module echo "=== Certificate state: ===" security list-keychains security find-identity -v # Layer 4: Actual operation codesign --sign "$IDENTITY" --verbose=4 "$ARTIFACT" This reveals: Which layer fails (secrets -> orchestrator OK, orchestrator -> build FAIL)
  2. Trace Data Flow WHEN the error is deep in the call stack: See root-cause-tracing.md in this directory for the complete backward tracing method. Short version:

- Where does the bad value originate? - What called this function with the bad value? - Keep tracing upward until you find the source - Fix at the source, not at the symptom

Phase 2: Pattern Analysis

Find the pattern before fixing:

  1. Locate Working Examples

- Find similar working code in the same codebase - What works that resembles what is broken?

  1. Compare Against References

- If implementing a pattern, read the reference implementation COMPLETELY - Do not skim -- read every line - Understand the pattern fully before applying

  1. Identify Differences

- What differs between working and broken? - List every difference, no matter how small - Do not assume "that cannot matter"

  1. Understand Dependencies

- What other components does this require? - What settings, configuration, environment? - What assumptions does it make?

Phase 3: Hypothesis and Testing

Scientific method:

  1. Form a Single Hypothesis

- State clearly: "I believe X is the root cause because Y" - Write it down - Be specific, not vague

  1. Test Minimally

- Make the SMALLEST possible change to test the hypothesis - One variable at a time - Do not fix multiple things simultaneously

  1. Verify Before Continuing

- Did it work? Yes -> Phase 4 - Did not work? Form a NEW hypothesis - DO NOT pile additional fixes on top

  1. When You Do Not Know

- Say "I do not understand X" - Do not pretend to know - Ask for help - Research further

Phase 4: Implementation

Fix the root cause, not the symptom:

  1. Create a Failing Test Case

- Simplest possible reproduction - Automated test if possible - One-off test script if no framework available - MUST exist before fixing - Use the godmode:test-first skill for writing proper failing tests

  1. Implement a Single Fix

- Address the root cause identified - ONE change at a time - No "while I'm here" improvements - No bundled refactoring

  1. Verify the Fix

- Test passes now? - No other tests broken? - Issue actually resolved?

  1. If the Fix Does Not Work

- STOP - Count: How many fixes have you attempted? - If < 3: Return to Phase 1, re-analyze with new information - If >= 3: STOP and question the architecture (step 5 below) - DO NOT attempt fix #4 without architectural discussion

  1. If 3+ Fixes Failed: Question Architecture Pattern indicating an architectural problem: STOP and question fundamentals: Discuss with your human partner before attempting more fixes This is NOT a failed hypothesis -- this is a flawed architecture.

- Each fix reveals new shared state/coupling/problems in different locations - Fixes require "massive refactoring" to implement - Each fix creates new symptoms elsewhere - Is this pattern fundamentally sound? - Are we persisting through sheer inertia? - Should we refactor the architecture vs. continue fixing symptoms?

Guardrails - STOP and Follow Process

If you catch yourself thinking:

  • "Quick fix for now, investigate later"
  • "Just try changing X and see what happens"
  • "Apply multiple changes, run tests"
  • "Skip the test, I'll verify manually"
  • "It's probably X, let me fix that"
  • "I don't fully understand but this might work"
  • "Pattern says X but I'll adapt differently"
  • "Here are the main problems: [lists fixes without investigation]"
  • Proposing solutions before tracing data flow
  • "One more fix attempt" (when already tried 2+)
  • Each fix reveals new problems in different places

ALL of these mean: STOP. Return to Phase 1.

If 3+ fixes failed: Question the architecture (see Phase 4, step 5)

Human Partner Signals You Are Off Track

Watch for these redirections:

  • "Is that not happening?" - You assumed without verifying
  • "Will it show us...?" - You should have added evidence gathering
  • "Stop guessing" - You are proposing fixes without understanding
  • "Think deeper" - Question fundamentals, not just symptoms
  • "We're stuck?" (frustrated) - Your approach is not working

When you see these: STOP. Return to Phase 1.

Cognitive Traps

RationalizationWhat Is Actually True
"Issue is simple, process not needed"Simple issues have root causes too. The process is fast for simple bugs.
"Emergency, no time for process"Systematic diagnosis is FASTER than guess-and-check flailing.
"Just try this first, then investigate"The first fix sets the pattern. Do it right from the start.
"I'll write the test after confirming the fix works"Untested fixes do not hold. Test first proves it.
"Multiple fixes at once saves time"Cannot isolate what worked. Creates new bugs.
"Reference too long, I'll adapt the pattern"Partial understanding guarantees bugs. Read it completely.
"I see the problem, let me fix it"Seeing symptoms is not the same as understanding root cause.
"One more fix attempt" (after 2+ failures)3+ failures = architectural problem. Question the pattern, do not fix again.

Quick Reference

PhaseKey ActivitiesSuccess Criteria
1. Root CauseRead errors, reproduce, check changes, gather evidenceUnderstand WHAT and WHY
2. PatternFind working examples, compareIdentify differences
3. HypothesisForm theory, test minimallyConfirmed or new hypothesis
4. ImplementationCreate test, fix, verifyBug resolved, tests pass

When Investigation Reveals No Root Cause

If systematic investigation reveals the issue is truly environmental, timing-dependent, or external:

  1. You have completed the process
  2. Document what you investigated
  3. Implement appropriate handling (retry, timeout, error message)
  4. Add monitoring/logging for future investigation

But: 95% of "no root cause" cases are incomplete investigation.

Supporting Methods

These methods are part of fault diagnosis and available in this directory:

  • root-cause-tracing.md - Trace bugs backward through the call stack to find the original trigger
  • defense-in-depth.md - Add validation at multiple layers after finding root cause
  • condition-based-waiting.md - Replace arbitrary timeouts with condition polling

Related skills:

  • godmode:test-first - For creating failing test case (Phase 4, Step 1)
  • godmode:completion-gate - Verify fix worked before declaring success

Real-World Impact

From diagnosis sessions:

  • Systematic approach: 15-30 minutes to resolution
  • Random fix approach: 2-3 hours of flailing
  • First-attempt fix rate: 95% vs 40%
  • New bugs introduced: Near zero vs common

平台分布

Codex

33.76%
按下载量换算35

Claude

31.96%
按下载量换算33

Cursor

17.28%
按下载量换算18

Gemini CLI

9.2%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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