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Agent Skill · 研究检索

systematic-debugging(系统调试)

systematic-debugging 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。

systematic-debugging 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,权限为操作浏览器;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 62,244。

总安装 339周安装 14GitHub Stars 公开资料未说明下载 111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:systematic-debugging(系统调试)
来源仓库:https://github.com/brite-nites/britenites-claude-plugins
仓库路径:skills/systematic-debugging
安装命令:
npx skills add https://github.com/brite-nites/britenites-claude-plugins --skill systematic-debugging
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/brite-nites/britenites-claude-plugins --skill systematic-debugging

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。

采用四阶段结构化流程定位 bug 根因,而非仅掩盖症状。适用于测试失败、生产异常或“在我机器上正常”类问题。每个阶段输出清晰检查点,确保排查过程可追溯。需用户提供具体现象描述以便启动针对性诊断流程。systematic-debugging 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/systematic-debugging

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/brite-nites/britenites-claude-plugins --skill…;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

    它需要操作浏览器,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

systematic-debugging 怎么安装?

在终端执行 npx skills add https://github.com/brite-nites/britenites-claude-plugins --skill systematic…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

systematic-debugging 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。

systematic-debugging 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

systematic-debugging 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。

systematic-debugging 用的人多吗?

公开数据是累计安装 339 次,近一周安装 14 次,下载 111 次。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。

systematic-debugging 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
systematic-debugging

系统调试 · 本页

339—操作浏览器未明确通过

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

Systematic Debugging

You are investigating a bug using a structured four-phase process. The goal is to find and fix the root cause, not just suppress the symptom.

When to Activate

  • Bug reports or unexpected behavior
  • Failing tests that shouldn't be failing
  • Production issues or error reports
  • "It works on my machine" type problems
  • Any situation where the cause isn't immediately obvious

Activation

After activation, print the banner (see _shared/observability.md):

---
**Systematic Debugging** activated
Trigger: [describe the symptom in your own words — e.g., "test failure in auth flow" or "unexpected 500 on endpoint"]
Produces: root cause analysis, regression test, fix
---

Phase 1: Reproduce

Narrate: Phase 1/4: Reproducing the problem...

Before anything else, reliably reproduce the problem.

Steps

  1. Understand the report — What's expected? What's happening instead? When did it start?
  2. Reproduce locally — Run the exact steps that trigger the bug
  3. Document the reproduction: ## Reproduction Steps: [exact steps] Expected: [what should happen] Actual: [what happens instead] Frequency: [always / intermittent / specific conditions] Environment: [OS, Node version, browser, etc.]
  4. If intermittent: Identify conditions that increase frequency (load, timing, specific data)

If You Can't Reproduce

  • Check environment differences (versions, config, data)
  • Add logging to narrow down when/where it occurs
  • Ask the reporter for more details
  • Do NOT proceed to fixing without reproduction — you'll likely fix the wrong thing

If reproduction fails after reasonable effort, use error recovery (see _shared/observability.md). AskUserQuestion with options: "Add more logging and retry / Get more info from reporter / Proceed with best guess (risky)."

Narrate: Phase 1/4: Reproducing the problem... done

Phase 2: Isolate

Narrate: Phase 2/4: Isolating the bug...

Narrow down where the bug lives.

Binary Search Strategy

  1. Identify the boundaries — Which systems/modules are involved in the failing flow?
  2. Add assertions at boundaries — Verify inputs and outputs at each layer
  3. Bisect — Is the problem in the frontend or backend? In the handler or the model? In the query or the transformation?
  4. Narrow until you find the exact location — The specific function, line, or condition

Isolation Techniques

  • Git bisect — If the bug is a regression, find the commit that introduced it: git bisect start, git bisect bad, git bisect good [known-good-commit]
  • Minimal reproduction — Strip away unrelated code until you have the smallest case that fails
  • Logging — Add targeted logging (not scattershot console.log everywhere)
  • Assertion insertion — Add assert statements at key points to catch violations

What to Record

## Isolation
Location: [file:line or module]
Narrowed from: [original scope] → [isolated location]
Method: [how you narrowed it down]

Narrate: Phase 2/4: Isolating the bug... done

Phase 3: Analyze Root Cause

Narrate: Phase 3/4: Analyzing root cause...

Understand *why* the bug exists, not just *where*.

Root Cause Categories

  1. Logic error — Code does the wrong thing (off-by-one, wrong operator, missing case)
  2. State corruption — Data gets into an invalid state (race condition, missing validation, stale cache)
  3. Integration mismatch — Two components disagree on interface, format, or protocol
  4. Environment issue — Config, version, or platform difference
  5. Missing handling — Edge case, error path, or boundary not covered

Analysis Questions

  • Why does this code exist? What was the original intent?
  • What changed recently? (Check git log for the area)
  • Are there similar patterns elsewhere that work correctly? What's different?
  • Is this the only place this bug manifests, or is it a systemic issue?

Log the root cause decision (see _shared/observability.md Decision Log format):

Decision: Root cause is [category] — [specific cause] Reason: [evidence from isolation phase] Alternatives: [other hypotheses that were ruled out]

Defense in Depth

After identifying the root cause, ask:

  • Why wasn't this caught by tests?
  • Why wasn't this caught by types?
  • Why wasn't this caught by code review?
  • What other similar bugs might exist?
## Root Cause
Cause: [precise description]
Category: [logic / state / integration / environment / missing handling]
Why it wasn't caught: [gap in testing, types, or review]
Related risks: [other places with similar patterns]

Narrate: Phase 3/4: Analyzing root cause... done

Phase 4: Fix

Narrate: Phase 4/4: Applying fix...

Fix the root cause and prevent regression.

Fix Process

  1. Write a failing test that reproduces the bug (TDD red phase)
  2. Verify the test fails — It should fail for the same reason as the bug
  3. Apply the minimal fix — Change as little as possible
  4. Verify the test passes — The fix resolves the bug
  5. Run the full test suite — The fix doesn't break anything else
  6. Check for related issues — Fix similar patterns elsewhere if applicable

Log defense-in-depth decisions:

Decision: [which defense-in-depth measures to add] Reason: [what class of bug this prevents] Alternatives: [other measures considered]

Defense-in-Depth Fixes

Beyond the immediate fix, consider:

  • Add type constraints that would prevent this class of bug
  • Add validation at the boundary where bad data enters
  • Add assertions that would catch this sooner
  • Improve error messages so the next person gets a clearer signal

Condition-Based Waiting

If the bug involves timing or async behavior:

  • Never use arbitrary delays (sleep 5, setTimeout(5000))
  • Wait for conditions: poll for the expected state, with a timeout
  • Example: Instead of sleep 2 && check_result, use i=0; while! check_result && [$i -lt 100]; do sleep 0.1; i=$((i+1)); done

Fix Report

## Fix
Change: [what was changed and why]
Files: [list of modified files]
Test: [the regression test that was added]
Defense: [additional protective measures added]
Related fixes: [similar patterns fixed elsewhere, or "none"]

Narrate: Phase 4/4: Applying fix... done

Completion

Present the full debugging report:

**Debugging summary.**
Root cause: [one-line root cause]
Fix: [one-line fix description]

Bug: [one-line description]
Reproduction → Isolation → Analysis → Fix
[Link to each section above]

Regression test: [test name and how to run it]
Tests: All passing
Build: Clean

Handoff

After the completion report, print this completion marker exactly:

**Debugging complete.**
Artifacts:
- Regression test: [test file path]
- Files changed: [list]
- Defense-in-depth: [additions, or "none"]
Compound learning: [If this revealed a pattern, it should be captured via compound-learnings]
Returning to the calling workflow.

Rules

  • Never fix a bug you can't reproduce — you're guessing
  • Never suppress a symptom without understanding the root cause
  • Always add a regression test — bugs that come back are morale killers
  • Log your debugging process — it helps others (and future you) with similar bugs
  • Don't scatter console.log — add targeted, informative logging
  • Remove debugging artifacts (extra logs, temporary assertions) before shipping, unless they improve production observability
  • If the bug is in a dependency, document the workaround and file an upstream issue

平台分布

Codex

34.87%
按下载量换算39

Claude

30.57%
按下载量换算34

Cursor

18.38%
按下载量换算20

Gemini CLI

10.57%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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