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研究检索需要联网github未标认证来源可访问许可证需确认审计异常

fix-issue解决问题

Agent Skill

用于围绕 GitHub 仓库、Issue、Pull Request、分支、提交和代码协作流程提供辅助能力。它适合让 Agent 查询项目状态、整理变更、辅助创建或检查协作事项,并把仓库中的信息转成可执行的下一步。使用时需要区分只读查询和写入操作;涉及创建 PR、修改 Issue、推送分支或访问私有仓库时,应确认 token 权限、目标仓库范围和用户授权。

总安装

753

周安装

32

GitHub Stars

6

下载量

264
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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-issue(解决问题)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/fix-issue
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill fix-issue
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-issue

简介

fix-issue 用于围绕 GitHub 仓库、Issue 和 PR 提供协作辅助,查询状态、整理变更或创建事项。

  • 适用于只读查询与写入操作,需确认 token 权限和仓库范围。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 涉及推送分支或修改 Issue 时应获得用户授权。
  • fix-issue 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

[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.
Skill Variant: Variant of /fix — debug and fix GitHub issues with systematic investigation.

Quick Summary

Goal: Investigate and fix bugs reported as GitHub issues with full traceability.

Workflow:

  1. Fetch — Read GitHub issue details (title, description, reproduction steps)
  2. Reproduce — Trace the reported behavior in code
  3. Fix — Apply fix with root cause evidence

Key Rules:

  • Debug Mindset: every claim needs file:line evidence
  • Link fix back to the GitHub issue for traceability
  • Verify fix addresses the specific reproduction steps from the issue
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.

$ARGUMENTS

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, MUST ATTENTION present findings + proposed fix to user via AskUserQuestion and get explicit approval BEFORE any code changes. No silent fixes.

Activate debug-investigate skill and follow its workflow.

IMPORTANT: Always use external memory at .ai/workspace/analysis/issue-[number].analysis.md for structured analysis. Re-read ENTIRE analysis file before proposing any fix — this prevents knowledge loss.

🛑 Present root cause + proposed fix → AskUserQuestion → wait for user approval before implementing.

See .claude/docs/AI-DEBUGGING-PROTOCOL.md for comprehensive guidelines.

⚠️ MANDATORY: Post-Fix Verification

After applying the fix, MUST ATTENTION run /prove-fix — build code proof traces per change with confidence scores. Never skip.


Standalone Review Gate (Non-Workflow Only)

MANDATORY IMPORTANT MUST ATTENTION: If this skill is called outside a workflow (standalone /fix-issue), you MUST ATTENTION create a TaskCreate todo task for /review-changes as the last task in your task list. This ensures all changes are reviewed before commit even without a workflow enforcing it. If already running inside a workflow (e.g., bugfix), skip this — the workflow sequence handles /review-changes at the appropriate step.

Closing Reminders

MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality. 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.

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能力 2

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能力 3

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能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.83%
按下载量换算89

Claude

28.93%
按下载量换算76

Cursor

19.13%
按下载量换算51

Gemini CLI

8.45%
按下载量换算22

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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