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Agent Skill · 研究检索

analyze-skill-issues(分析技能问题)

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。

analyze-skill-issues 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,权限为执行命令;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 36,780。

总安装 1,860周安装 76GitHub Stars 201下载 602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:analyze-skill-issues(分析技能问题)
来源仓库:https://github.com/microsoft/github-copilot-for-azure
仓库路径:skills/analyze-skill-issues
安装命令:
npx skills add https://github.com/microsoft/github-copilot-for-azure --skill analyze-skill-issues
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/microsoft/github-copilot-for-azure --skill analyze-skill-issues

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。

analyze-skill-issues 查询 Azure Storage 中存储的技能集成测试错误详情,辅助诊断失败根因。适用于技能发布前后的质量验证,支持按日期、运行 ID 和技能名称检索日志 blob。通过 mcp_azure_mcp_storage_blob_get 列出容器内文件结构,下载后生成错误摘要报告。

依赖 Azure 凭据与特定存储账户访问权限,仅限授权用户使用,禁止越权访问生产数据。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/analyze-skill-issues

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/microsoft/github-copilot-for-azure --skill ana…;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

    它需要执行命令,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

analyze-skill-issues 怎么安装?

在终端执行 npx skills add https://github.com/microsoft/github-copilot-for-azure --skill analyze-skill…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

analyze-skill-issues 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。

analyze-skill-issues 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/microsoft/github-copilot-for-azure --skill analyze-skill-issues 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

analyze-skill-issues 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。

analyze-skill-issues 用的人多吗?

公开数据是累计安装 1,860 次,近一周安装 76 次,下载 602 次,GitHub 201 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。

analyze-skill-issues 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

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
analyze-skill-issues

分析技能问题 · 本页

1,860201执行命令未明确通过

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

Analyze Skill Issues

Queries the strdashboarddevveobvk Azure Storage account that stores all integration test results and retrieves error details for a given skill.

Quick Reference

PropertyValue
Storage accountstrdashboarddevveobvk
Containerintegration-reports
Blob path pattern{date}/{run_id}/{skill_name}/[{test_name}/]<file> — see Blob Path Layout
Blob discoverymcp_azure_mcp_storage_blob_get — list blobs to find the right paths
Blob content downloadaz storage blob download... --file "$env:TEMP\<filename>" — local path reported in summary
Best forDiagnosing why a skill's integration tests are failing
TOOL USAGE — MANDATORY: Use mcp_azure_mcp_storage_blob_get to enumerate and identify the correct blob paths. Then use az storage blob download to download and read the content of those blobs. These tools serve different purposes and are both always required — they are not alternatives.

When to Use

  • User asks why a skill's tests are failing
  • User asks to debug or investigate a skill's recent test failures
  • User wants to see errors from integration test runs for a specific skill
  • User asks what errors or exceptions caused skill test failures

Skill Name Mapping

Resolve the user's skill name to its canonical directory name using the Skill Name Mapping.

MCP Tools

MCP tools are used exclusively for blob discovery — finding which blob paths exist. All calls require account: "strdashboarddevveobvk" and container: "integration-reports". Use az storage blob download (see Phase 2) to read blob content.

ToolPurposeKey parameters
mcp_azure_mcp_storage_blob_getList blob names and metadata (does not return file content)account, container; omit blob to list all
mcp_azure_mcp_storage_blob_container_getVerify the container existsaccount, container

Output Requirements

Every response MUST include all of the following. Do not omit any item:

  • Root cause explanation of why the skill has low confidence or failing tests
  • Per-test breakdown (test name, pass/fail, confidence or error)
  • Referenced Files section listing every downloaded file as a vscode://file/ link
⚠️ MANDATORY: The Referenced Files section is not optional. Always resolve $env:TEMP to the actual path (run echo $env:TEMP) and include a clickable link for every file downloaded. If this section is missing from your response, the output is incomplete.

Workflow

TOOL RESPONSIBILITIES: mcp_azure_mcp_storage_blob_get is used exclusively for blob discovery (listing available paths). az storage blob download is used exclusively for reading blob content. Both are always required.

Phase 1 — Enumerate Recent Blobs for the Skill

  1. Resolve the skill name using the Skill Name Mapping.
  2. List all blobs in the container to discover available date/run paths: mcp_azure_mcp_storage_blob_get({account: "strdashboarddevveobvk", container: "integration-reports"}) This returns a flat list of all blob names. Filter for entries that:

- Start with a date string matching yyyy-mm-dd within the last 7 days - Contain /{skill_name}/ in the path - Do not end with token-usage.json or agent-metadata.json

  1. Group the matching blobs by date (descending) and by run ID (the second path segment).
  2. Limit scope: If the user specified a date in their prompt, use only that date. Otherwise, take the 3 most recent dates from the filtered results and discard the rest. Do not process more than 3 dates.

Phase 2 — Read Test Result Files

For each matching blob path identified in Phase 1, download it to a local temp file and read its content:

az storage blob download --account-name strdashboarddevveobvk --container-name integration-reports `
  --name "<full-blob-path>" --file "$env:TEMP\<filename>" --auth-mode login --no-progress

Use just the last path segment as <filename>.

⚠️ REQUIRED: After each download, immediately append the resolved local path to your working list of referenced files. Run echo $env:TEMP once to resolve the actual temp directory. Every downloaded file must appear in the Referenced Files section of your final response — this is not optional.

Priority order for files to read (most useful first):

  1. Any *.json files that are NOT token-usage.json or agent-metadata.json — these contain test pass/fail results and error messages
  2. *-SKILL-REPORT.md or *report*.json files — contain skill invocation details and test narratives
  3. junit.xml blobs if present — contain structured test failure messages

Phase 3 — Extract Failure Information

For each test result file, extract:

  • Test name — the test case identifier
  • Status — passed / failed / error / skipped
  • Error message — the exception or assertion failure text
  • Stack trace — if present in the file
  • Date and run ID — for traceability

Look specifically for fields such as:

  • "status": "failed" or "passed": false
  • "error", "errorMessage", "failureMessage", "message" JSON keys
  • <failure> or <error> XML elements in JUnit format
  • Any Error: or FAIL prefixed lines in text reports

Phase 4 — Summarize Failures

Present the findings grouped by test name:

## Failures for <skill-name> — <date> (Run: <run_id>)

### <test-name>
- **Status:** failed
- **Error:** <error message>
- **Detail:** <stack trace or additional context, truncated to ~10 lines>

### <test-name-2>
...

At the end of the summary, include a Referenced Files section listing every file that was downloaded as a clickable VS Code link. Resolve $env:TEMP to the actual Windows temp path (e.g. C:\Users\<user>\AppData\Local\Temp) and format each entry as a markdown link using the vscode://file/ URI scheme with forward slashes:

## Referenced Files
- [<filename1>](vscode://file/C:/Users/<user>/AppData/Local/Temp/<filename1>)
- [<filename2>](vscode://file/C:/Users/<user>/AppData/Local/Temp/<filename2>)
- ...

To resolve the actual temp path, run echo $env:TEMP in the terminal before constructing the links.

Include:

  • Total failing tests vs. total tests found
  • Most recent run date analyzed
  • Common error patterns across multiple tests (e.g., all failing due to auth, quota, timeout)

Date iteration rule: Process the most recent date first. Only proceed to the next date if the current date yields zero failures. Stop as soon as failures are found — do not process all 3 dates if the first one has results.

See Blob Path Layout for the full container tree structure.

Error Handling

ErrorCauseRemediation
No blobs found for skillSkill has not run tests recently, or name is wrongVerify skill name using the mapping table; tests run Tue–Sat on a schedule
Blob list is emptyContainer access issue or wrong accountConfirm account: "strdashboarddevveobvk" and that the user has Azure CLI credentials
Blob content not readableFile is binary or corruptedSkip that blob and try adjacent blobs for the same test
All tests show as skippedThe skill's test schedule hasn't run yet todayCheck tests/skills.json for the skill's schedule and check a prior day's date prefix
token-usage.json / agent-metadata.json onlyCorrect path but no result filesThe test run may have crashed before writing results; check the run ID in GitHub Actions

平台分布

Codex

36.52%
按下载量换算220

Claude

30.51%
按下载量换算184

Cursor

20.07%
按下载量换算121

Gemini CLI

10.16%
按下载量换算61

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/microsoft/github-copilot-for-azure --skill analyze-skill-issues 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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