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研究检索external-servicegithub未标认证来源可访问许可证需确认审计异常

github-opsGitHub OPS 工具

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

1,117

周安装

48

GitHub Stars

25

下载量

392
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:github-ops(GitHub OPS 工具)
来源仓库:https://github.com/oimiragieo/agent-studio
仓库路径:skills/github-ops
安装命令:
npx skills add https://github.com/oimiragieo/agent-studio --skill github-ops
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/oimiragieo/agent-studio --skill github-ops

简介

github-ops 围绕 GitHub 仓库、Issue、PR 等提供辅助能力,适合查询项目状态和整理变更。

  • 适用于协助创建或检查协作事项,并将仓库信息转为可执行步骤的场景。
  • 通过 npx skills add 命令从 GitHub 安装,支持只读查询和写入操作。
  • 涉及修改 Issue、推送分支或访问私有仓库时,需确认 token 权限和用户授权范围。
  • github-ops 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

GitHub Ops Skill

Provides structured guidance for repository reconnaissance using gh api and gh search.

Overview

Repository reconnaissance often fails when agents guess file paths or attempt to fetch large files blindly. This skill enforces a structured Map -> Identify -> Fetch sequence using the GitHub CLI to minimize token waste and improve reliability.

⚡ Essential Reconnaissance Commands

Use these commands to understand a repository structure before fetching content.

1. List Repository Root

gh api repos/{owner}/{repo}/contents --jq '.[].name'

2. List Specific Directory

gh api repos/{owner}/{repo}/contents/{path} --jq '.[].name'

3. Fetch File Content (Base64 Decoded)

gh api repos/{owner}/{repo}/contents/{path} --jq '.content' | base64 -d

4. Search for Pattern in Repository

gh search code "{pattern}" --repo {owner}/{repo}

5. Get Repository Metadata

gh repo view {owner}/{repo} --json description,stargazerCount,updatedAt

🔄 Token-Efficient Workflow

  1. Map Tree: List the root and core directories (commands, src, docs).
  2. Identify Entrypoints: Look for README.md, gemini-extension.json, package.json, or SKILL.md.
  3. Targeted Fetch: Download only the entrypoints first.
  4. Deep Dive: Use gh search code to find logic patterns rather than reading every file.

🛡️ Platform Safety (Windows)

  • When using base64 -d, ensure the output is redirected to a file using the Write tool if it's large.
  • Avoid Linux-style /dev/stdin patterns in complex pipes.
  • Use native paths for any local storage.

Iron Laws

  1. ALWAYS follow the Map → Identify → Fetch sequence before reading any file — blindly fetching files by guessed path wastes tokens, triggers 404s, and produces hallucinated repo structure.
  2. NEVER fetch a file without first listing its parent directory or confirming it exists via gh api — large files fetched unnecessarily can exhaust the context window.
  3. ALWAYS use --jq to filter gh api JSON output to only the fields needed — unfiltered API responses contain hundreds of irrelevant fields that inflate token usage.
  4. NEVER use gh search code without a scoping qualifier (repo, org, or path) — unscoped code search returns results from all of GitHub, producing irrelevant noise.
  5. ALWAYS prefer gh api structured queries over reading repository files directly when repository metadata is needed — API queries are faster, structured, and don't require authentication context for public repos.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
Guessing file paths and fetching them directlyHigh 404 rate; wasted tokens on non-existent pathsMap root tree first: gh api repos/{owner}/{repo}/git/trees/HEAD --jq '.tree[].path'
Fetching entire files for a single fieldLarge files exhaust context; slow and impreciseUse --jq to extract only the required field from API response
Unscoped gh search code queriesReturns GitHub-wide results; noise overwhelms signalAlways add --repo owner/name or --owner org scope qualifier
Reading binary or generated filesBinary content is unreadable; generated files change frequentlyIdentify file type first; skip binaries; read source files only
Sequential API calls for each fileUnnecessary round-trips inflate latencyBatch: use gh api trees or search to identify multiple targets, then fetch in parallel

GitHub MCP Server Operations

When the official GitHub MCP server (@modelcontextprotocol/server-github) is configured, use these higher-level tools for repository management and automation:

// settings.json configuration
"github": {
  "command": "npx",
  "args": ["-y", "@modelcontextprotocol/server-github"],
  "env": { "GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_TOKEN}" }
}

PR Automation Pattern

# Create PR with auto-generated description
gh pr create \
  --title "feat: add feature X" \
  --body "$(gh api repos/{owner}/{repo}/compare/{base}...{head} --jq '.commits[].commit.message' | head -5)" \
  --base main \
  --head feature/x

# Auto-merge after CI passes
gh pr merge --auto --squash --delete-branch

Issue Management

# List open issues by label
gh issue list --label "bug" --state open --json number,title,assignees

# Bulk-close resolved issues
gh issue list --label "stale" --json number --jq '.[].number' | \
  xargs -I{} gh issue close {} --comment "Closing as stale"

# Create issue from template
gh issue create \
  --title "Bug: [description]" \
  --body-file .github/ISSUE_TEMPLATE/bug_report.md \
  --label "bug,needs-triage"

Release Automation

# Create release with auto-generated notes
gh release create v1.2.0 \
  --generate-notes \
  --title "v1.2.0" \
  --target main

# Upload release assets
gh release upload v1.2.0 dist/*.tar.gz dist/*.zip

Workflow Management

# Trigger workflow manually
gh workflow run deploy.yml --field environment=production

# Watch workflow run
gh run watch $(gh run list --workflow=deploy.yml --limit=1 --json databaseId --jq '.[0].databaseId')

# Download workflow artifacts
gh run download --name=build-artifacts --dir=./artifacts

Assigned Agents

  • artifact-integrator: Lead agent for repository onboarding.
  • developer: PR management and exploration.

Memory Protocol (MANDATORY)

Before starting: Read .claude/context/memory/learnings.md

After completing:

  • New pattern -> .claude/context/memory/learnings.md
  • Issue found -> .claude/context/memory/issues.md
  • Decision made -> .claude/context/memory/decisions.md
ASSUME INTERRUPTION: If it's not in memory, it didn't happen.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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

33.29%
按下载量换算130

Claude

31.45%
按下载量换算123

Cursor

20.82%
按下载量换算82

Gemini CLI

9.53%
按下载量换算37

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

来源信息

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