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Agent Skill · 研究检索

fix-hard(努力修复)

fix-hard 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。

fix-hard 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,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,073。

总安装 808周安装 33GitHub Stars 6下载 259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-hard(努力修复)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/fix-hard
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill fix-hard
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-hard

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-hard 用于查找、检索和筛选相关信息。适合在复杂场景中快速定位关键信息或解决方案。通过 npx skills add 命令从 duc01226/easyplatform 仓库安装。需评估是否访问外部知识库或私有资源。建议先测试其在目标环境的表现。

fix-hard 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-hard

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-hard;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

fix-hard 怎么安装?

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

fix-hard 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-hard 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。

fix-hard 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-hard 用的人多吗?

公开数据是累计安装 808 次,近一周安装 33 次,下载 259 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-hard 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
fix-hard

努力修复 · 本页

8086需要联网未明确未通过

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.
Fix-Layer Accountability — NEVER fix at the crash site. Trace the full flow, fix at the owning layer. AI default behavior: see error at Place A → fix Place A. This is WRONG. The crash site is a SYMPTOM, not the cause. MANDATORY before ANY fix: 1. Trace full data flow — Map the complete path from data origin to crash site across ALL layers (storage → backend → API → frontend → UI). Identify where the bad state ENTERS, not where it CRASHES. 2. Identify the invariant owner — Which layer's contract guarantees this value is valid? That layer is responsible. Fix at the LOWEST layer that owns the invariant — not the highest layer that consumes it. 3. One fix, maximum protection — Ask: "If I fix here, does it protect ALL downstream consumers with ONE change?" If fix requires touching 3+ files with defensive checks, you are at the wrong layer — go lower. 4. Verify no bypass paths — Confirm all data flows through the fix point. Check for: direct construction skipping factories, clone/spread without re-validation, raw data not wrapped in domain models, mutations outside the model layer. BLOCKED until: - [] Full data flow traced (origin → crash) - [] Invariant owner identified with file:line evidence - [] All access sites audited (grep count) - [] Fix layer justified (lowest layer that protects most consumers) Anti-patterns (REJECT these): - "Fix it where it crashes" — Crash site ≠ cause site. Trace upstream. - "Add defensive checks at every consumer" — Scattered defense = wrong layer. One authoritative fix > many scattered guards. - "Both fix is safer" — Pick ONE authoritative layer. Redundant checks across layers send mixed signals about who owns the invariant.
Skill Variant: Variant of /fix — deep investigation with subagents for complex issues.

Quick Summary

Goal: Systematically diagnose and fix complex bugs using parallel subagent investigation.

Workflow:

  1. Scout — Use scout/researcher subagents to explore the issue in parallel
  2. Diagnose — Trace root cause through code paths with evidence
  3. Plan — Create fix plan with impact analysis
  4. Fix — Implement and verify the fix

Key Rules:

  • Debug Mindset: every claim needs file:line evidence
  • Use subagents for parallel investigation of multiple hypotheses
  • Always create a plan before implementing complex fixes
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.

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.

Ultrathink to plan & start fixing these issues follow the Orchestration Protocol, Core Responsibilities, Subagents Team and Development Rules: $ARGUMENTS

Workflow:

If the user provides a screenshots or videos, use ai-multimodal skill to describe as detailed as possible the issue, make sure developers can predict the root causes easily based on the description.

Fullfill the request

Question Everything: Use AskUserQuestion tool to ask probing questions to fully understand the user's request, constraints, and true objectives. Don't assume - clarify until you're 100% certain.

  • If you have any questions, use AskUserQuestion tool to ask the user to clarify them.
  • Ask 1 question at a time, wait for the user to answer before moving to the next question.
  • If you don't have any questions, start the next step.
⚠️ Validate Before Fix (NON-NEGOTIABLE): After root cause + plan creation, MUST ATTENTION present findings + proposed fix plan to user via AskUserQuestion and get explicit approval BEFORE any code changes. No silent fixes.

Fix the issue

Use sequential-thinking skill to break complex problems into sequential thought steps. Use problem-solving skills to tackle the issues. Analyze the skills catalog and activate other skills that are needed for the task during the process.

  1. Use debugger subagent to find the root cause of the issues and report back to main agent. 1.5. Write investigation results to .ai/workspace/analysis/{issue-name}.analysis.md. Re-read ENTIRE file before planning fix.
  2. Use researcher subagent to research quickly about the root causes on the internet (if needed) and report back to main agent.
  3. Use planner subagent to create an implementation plan based on the reports, then report back to main agent.
  4. 🛑 Present root cause + fix plan → AskUserQuestion → wait for user approval.
  5. Then use /code SlashCommand to implement the plan step by step.
  6. Final Report:
  • Report back to user with a summary of the changes and explain everything briefly, guide user to get started and suggest the next steps.
  • Ask the user if they want to commit and push to git repository, if yes, use git-manager subagent to commit and push to git repository.
  • IMPORTANT: Sacrifice grammar for the sake of concision when writing reports.
  • IMPORTANT: In reports, list any unresolved questions at the end, if any.

REMEMBER:

  • You can always generate images with ai-multimodal skills on the fly for visual assets.
  • You always read and analyze the generated assets with ai-multimodal skills to verify they meet requirements.
  • For image editing (removing background, adjusting, cropping), use media-processing skill as needed.
  • After fixing, MUST ATTENTION run /prove-fix — build code proof traces per change with confidence scores. Never skip.

Next Steps (Standalone: MUST ATTENTION ask user via AskUserQuestion. Skip if inside workflow.)

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: If this skill was called outside a workflow, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:
  • "Proceed with full workflow (Recommended)" — I'll detect the best workflow to continue from here (fix applied). This ensures prove-fix, review, testing, and docs steps aren't skipped.
  • "/prove-fix" — Prove fix correctness with code traces
  • "/test" — Run tests to verify fix
  • "Skip, continue manually" — user decides
If already inside a workflow, skip — the workflow handles sequencing.

Closing Reminders

  • IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • 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:
  • IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim. Confidence >80% to act, <60% = do NOT recommend.
  • IMPORTANT MUST ATTENTION include story_points and complexity in plan frontmatter. SP > 8 = split.
  • IMPORTANT MUST ATTENTION trace full data flow and fix at the owning layer, not the crash site. Audit all access sites before adding ?..

平台分布

Codex

33.67%
按下载量换算87

Claude

27.35%
按下载量换算71

Cursor

20.33%
按下载量换算53

Gemini CLI

9.64%
按下载量换算25

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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