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Agent Skill · 研究检索

fix-test(修复测试)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

fix-test 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,权限为只读;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 46,340。

总安装 784周安装 33GitHub Stars 6下载 275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:fix-test(修复测试)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/fix-test
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill fix-test
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/duc01226/easyplatform --skill fix-test

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。

fix-test 用于辅助测试设计、自动化测试和回归验证。适合编写单元测试、端到端测试或根据失败日志定位问题。使用时需确认项目测试框架、运行命令和夹具数据,避免误改真实逻辑。涉及浏览器或外部服务时应区分本地模拟与生产环境。fix-test 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/fix-test

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/duc01226/easyplatform --skill fix-test;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

fix-test 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill fix-test。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

fix-test 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。

fix-test 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

fix-test 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。

fix-test 用的人多吗?

公开数据是累计安装 784 次,近一周安装 33 次,下载 275 次,GitHub 6 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。

fix-test 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
fix-test

修复测试 · 本页

7846只读未明确通过

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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code. 1. Search 3+ similar patterns (grep/glob) — cite file:line evidence 2. Read existing files in target area — understand structure, base classes, conventions 3. Run python.claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists 4. Map dependencies via connections or callers_of — know what depends on your target 5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files) 6. Re-read analysis file before implementing — never work from memory alone 7. NEVER invent new patterns when existing ones work — match exactly or document deviation BLOCKED until: - [] Read target files - [] Grep 3+ patterns - [] Graph trace (if graph.db exists) - [] Assumptions verified with evidence
Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof. 1. Cite file:line, grep results, or framework docs for EVERY claim 2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend 3. Cross-service validation required for architectural changes 4. "I don't have enough evidence" is valid and expected output BLOCKED until: - [] Evidence file path (file:line) - [] Grep search performed - [] 3+ similar patterns found - [] Confidence level stated Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."
  • docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected:...] header before reading)
Estimation — Modified Fibonacci: 1(trivial) → 2(small) → 3(medium) → 5(large) → 8(very large) → 13(epic, SHOULD split) → 21(MUST ATTENTION split). Output story_points and complexity in plan frontmatter. Complexity auto-derived: 1-2=Low, 3-5=Medium, 8=High, 13+=Critical.
  • docs/test-specs/ — Test specifications by module (read existing TCs for expected behavior context when diagnosing failures)
Skill Variant: Variant of /fix — test suite failure diagnosis and resolution.

Quick Summary

Goal: Run test suites, analyze failures, and fix the underlying code or test issues.

Workflow:

  1. Run — Execute test suite and capture results
  2. Analyze — Identify failing tests, classify as code bug vs test issue
  3. Fix — Apply targeted fix to code or test

Key Rules:

  • Debug Mindset: every claim needs file:line evidence
  • Distinguish between code bugs and flawed test expectations
  • Run tests again after fix to confirm all pass
Root Cause Debugging — Systematic approach, never guess-and-check. 1. Reproduce — Confirm the issue exists with evidence (error message, stack trace, screenshot) 2. Isolate — Narrow to specific file/function/line using binary search + graph trace 3. Trace — Follow data flow from input to failure point. Read actual code, don't infer. 4. Hypothesize — Form theory with confidence %. State what evidence supports/contradicts it 5. Verify — Test hypothesis with targeted grep/read. One variable at a time. 6. Fix — Address root cause, not symptoms. Verify fix doesn't break callers via graph connections NEVER: Guess without evidence. Fix symptoms instead of cause. Skip reproduction step.

Analyze the skills catalog and activate the skills that are needed for the task during the process.

Debug Mindset (NON-NEGOTIABLE)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

  • Do NOT assume the first hypothesis is correct — verify with actual code traces
  • Every root cause claim must include file:line evidence
  • If you cannot prove a root cause with a code trace, state "hypothesis, not confirmed"
  • Question assumptions: "Is this really the cause?" → trace the actual execution path
  • Challenge completeness: "Are there other contributing factors?" → check related code paths
  • No "should fix it" without proof — verify the fix addresses the traced root cause

⚠️ MANDATORY: Confidence & Evidence Gate

MANDATORY IMPORTANT MUST ATTENTION declare Confidence: X% with evidence list + file:line proof for EVERY claim. 95%+ recommend freely | 80-94% with caveats | 60-79% list unknowns | <60% STOP — gather more evidence.

⚠️ Validate Before Fix (NON-NEGOTIABLE): After root cause analysis + plan creation, MUST ATTENTION present findings + proposed fix to user via AskUserQuestion and get explicit approval BEFORE any code changes. No silent fixes.

Reported Issues:

$ARGUMENTS

Workflow:

  1. Use tester subagent to compile the code and fix all syntax errors if any.
  2. Use tester subagent to run the tests and report back to main agent.

- External Memory: Write test failure analysis to .ai/workspace/analysis/{test-issue}.analysis.md. Re-read before fixing.

  1. If there are issues or failed tests, use debugger subagent to find the root cause of the issues, then report back to main agent.
  2. Use planner subagent to create an implementation plan based on the reports, then report back to main agent.
  3. 🛑 Present root cause + fix plan → AskUserQuestion → wait for user approval.
  4. Use main agent to implement the plan step by step.
  5. Use tester agent to test the fix and make sure it works, then report back to main agent.
  6. Use code-reviewer subagent to quickly review the code changes and make sure it meets requirements, then report back to main agent.
  7. If there are issues or failed tests, repeat from step 2.
  8. After finishing, respond back to user with a summary of the changes and explain everything briefly, guide user to get started and suggest the next steps.
  • After fixing, MUST ATTENTION run /prove-fix — build code proof traces per change with confidence scores. Never skip.

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MANDATORY IMPORTANT MUST ATTENTION STOP after 3 failed fix attempts — report outcomes, ask user before #4 MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:
  • MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
  • MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim. Confidence >80% to act, <60% = do NOT recommend.
  • MANDATORY IMPORTANT MUST ATTENTION include story_points and complexity in plan frontmatter. SP > 8 = split.

平台分布

Codex

34.28%
按下载量换算94

Claude

28.58%
按下载量换算79

Cursor

18.63%
按下载量换算51

Gemini CLI

9.48%
按下载量换算26

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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