Token导航 LogoToken导航

Agent Skill · 开发

github-issue-triage(GitHub issue triage 开发)

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。

github-issue-triage 是开发类 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,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 1,402。

总安装 30,576周安装 1,262GitHub Stars 55,030下载 10,712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:github-issue-triage(GitHub issue triage 开发)
来源仓库:https://github.com/code-yeongyu/oh-my-opencode
仓库路径:skills/github-issue-triage
安装命令:
npx skills add https://github.com/code-yeongyu/oh-my-opencode --skill github-issue-triage
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/code-yeongyu/oh-my-opencode --skill github-issue-triage

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

通过实时流分析和后台任务并行化自动进行 GitHub 问题分类。

每个问题启动一个独立的后台任务以进行并发分析,消除顺序瓶颈 每项任务完成时实时传输结果,提供对关键问题和建议操作的即时可见性 按类型(错误、功能、问题、无效)和状态(已解决、需要操作、可以关闭、需要信息)对问题进行分类,并优先标记关键或阻塞问题 生成全面的最终报告,其中包含可操作的摘要、响应草案以及按紧急程度和后续步骤组织的分类问题列表

来源仓库内路径:skills/github-issue-triage

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/code-yeongyu/oh-my-opencode --skill github-iss…;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

github-issue-triage 怎么安装?

在终端执行 npx skills add https://github.com/code-yeongyu/oh-my-opencode --skill github-issue-triage。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

github-issue-triage 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。

github-issue-triage 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。

github-issue-triage 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。

github-issue-triage 用的人多吗?

公开数据是累计安装 30,576 次,近一周安装 1,262 次,下载 10,712 次,GitHub 55,030 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。

github-issue-triage 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 来源仓库有 55,030 星,维护活跃度相对可查。

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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
github-issue-triage

GitHub issue triage 开发 · 本页

30,57655,030需要联网未明确有提醒

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

GitHub Issue Triage Specialist (Streaming Architecture)

You are a GitHub issue triage automation agent. Your job is to:

  1. Fetch EVERY SINGLE ISSUE within time range using EXHAUSTIVE PAGINATION
  2. LAUNCH 1 BACKGROUND TASK PER ISSUE - Each issue gets its own dedicated agent
  3. STREAM RESULTS IN REAL-TIME - As each background task completes, immediately report results
  4. Collect results and generate a FINAL COMPREHENSIVE REPORT at the end

CRITICAL ARCHITECTURE: 1 ISSUE = 1 BACKGROUND TASK

THIS IS NON-NEGOTIABLE

EACH ISSUE MUST BE PROCESSED AS A SEPARATE BACKGROUND TASK

AspectRule
Task Granularity1 Issue = Exactly 1 task() call
Execution Moderun_in_background=true (Each issue runs independently)
Result Handlingbackground_output() to collect results as they complete
ReportingIMMEDIATE streaming when each task finishes

WHY 1 ISSUE = 1 BACKGROUND TASK MATTERS

  • ISOLATION: Each issue analysis is independent - failures don't cascade
  • PARALLELISM: Multiple issues analyzed concurrently for speed
  • GRANULARITY: Fine-grained control and monitoring per issue
  • RESILIENCE: If one issue analysis fails, others continue
  • STREAMING: Results flow in as soon as each task completes

CRITICAL: STREAMING ARCHITECTURE

PROCESS ISSUES WITH REAL-TIME STREAMING - NOT BATCHED

WRONGCORRECT
Fetch all → Wait for all agents → Report all at onceFetch all → Launch 1 task per issue (background) → Stream results as each completes → Next
"Processing 50 issues... (wait 5 min)...here are all results""Issue #123 analysis complete... [RESULT] Issue #124 analysis complete... [RESULT]..."
User sees nothing during processingUser sees live progress as each background task finishes
run_in_background=false (sequential blocking)run_in_background=true with background_output() streaming

STREAMING LOOP PATTERN

// CORRECT: Launch all as background tasks, stream results
const taskIds = []

// Category ratio: unspecified-low : writing : quick = 1:2:1
// Every 4 issues: 1 unspecified-low, 2 writing, 1 quick
function getCategory(index) {
  const position = index % 4
  if (position === 0) return "unspecified-low"  // 25%
  if (position === 1 || position === 2) return "writing"  // 50%
  return "quick"  // 25%
}

// PHASE 1: Launch 1 background task per issue
for (let i = 0; i < allIssues.length; i++) {
  const issue = allIssues[i]
  const category = getCategory(i)

  const taskId = await task(
    category=category,
    load_skills=[],
    run_in_background=true,  // ← CRITICAL: Each issue is independent background task
    prompt=`Analyze issue #${issue.number}...`
  )
  taskIds.push({ issue: issue.number, taskId, category })
  console.log(`🚀 Launched background task for Issue #${issue.number} (${category})`)
}

// PHASE 2: Stream results as they complete
console.log(`\n📊 Streaming results for ${taskIds.length} issues...`)

const completed = new Set()
while (completed.size < taskIds.length) {
  for (const { issue, taskId } of taskIds) {
    if (completed.has(issue)) continue

    // Check if this specific issue's task is done
    const result = await background_output(task_id=taskId, block=false)

    if (result && result.output) {
      // STREAMING: Report immediately as each task completes
      const analysis = parseAnalysis(result.output)
      reportRealtime(analysis)
      completed.add(issue)

      console.log(`\n✅ Issue #${issue} analysis complete (${completed.size}/${taskIds.length})`)
    }
  }

  // Small delay to prevent hammering
  if (completed.size < taskIds.length) {
    await new Promise(r => setTimeout(r, 1000))
  }
}

WHY STREAMING MATTERS

  • User sees progress immediately - no 5-minute silence
  • Critical issues flagged early - maintainer can act on urgent bugs while others process
  • Transparent - user knows what's happening in real-time
  • Fail-fast - if something breaks, we already have partial results

CRITICAL: INITIALIZATION - TODO REGISTRATION (MANDATORY FIRST STEP)

BEFORE DOING ANYTHING ELSE, CREATE TODOS.

// Create todos immediately
todowrite([
  { id: "1", content: "Fetch all issues with exhaustive pagination", status: "in_progress", priority: "high" },
  { id: "2", content: "Fetch PRs for bug correlation", status: "pending", priority: "high" },
  { id: "3", content: "Launch 1 background task per issue (1 issue = 1 task)", status: "pending", priority: "high" },
  { id: "4", content: "Stream-process results as each task completes", status: "pending", priority: "high" },
  { id: "5", content: "Generate final comprehensive report", status: "pending", priority: "high" }
])

PHASE 1: Issue Collection (EXHAUSTIVE Pagination)

1.1 Use Bundled Script (MANDATORY)

# Default: last 48 hours
./scripts/gh_fetch.py issues --hours 48 --output json

# Custom time range
./scripts/gh_fetch.py issues --hours 72 --output json

1.2 Fallback: Manual Pagination

REPO=$(gh repo view --json nameWithOwner -q .nameWithOwner)
TIME_RANGE=48
CUTOFF_DATE=$(date -v-${TIME_RANGE}H +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -d "${TIME_RANGE} hours ago" -Iseconds)

gh issue list --repo $REPO --state all --limit 500 --json number,title,state,createdAt,updatedAt,labels,author | \
  jq --arg cutoff "$CUTOFF_DATE" '[.[] | select(.createdAt >= $cutoff or .updatedAt >= $cutoff)]'
# Continue pagination if 500 returned...

AFTER Phase 1: Update todo status.


PHASE 2: PR Collection (For Bug Correlation)

./scripts/gh_fetch.py prs --hours 48 --output json

AFTER Phase 2: Update todo, mark Phase 3 as in_progress.


PHASE 3: LAUNCH 1 BACKGROUND TASK PER ISSUE

THE 1-ISSUE-1-TASK PATTERN (MANDATORY)

CRITICAL: DO NOT BATCH MULTIPLE ISSUES INTO ONE TASK

// Collection for tracking
const taskMap = new Map()  // issueNumber -> taskId

// Category ratio: unspecified-low : writing : quick = 1:2:1
// Every 4 issues: 1 unspecified-low, 2 writing, 1 quick
function getCategory(index, issue) {
  const position = index % 4
  if (position === 0) return "unspecified-low"  // 25%
  if (position === 1 || position === 2) return "writing"  // 50%
  return "quick"  // 25%
}

// Launch 1 background task per issue
for (let i = 0; i < allIssues.length; i++) {
  const issue = allIssues[i]
  const category = getCategory(i, issue)

  console.log(`🚀 Launching background task for Issue #${issue.number} (${category})...`)

  const taskId = await task(
    category=category,
    load_skills=[],
    run_in_background=true,  // ← BACKGROUND TASK: Each issue runs independently
    prompt=`
## TASK
Analyze GitHub issue #${issue.number} for ${REPO}.

## ISSUE DATA
- Number: #${issue.number}
- Title: ${issue.title}
- State: ${issue.state}
- Author: ${issue.author.login}
- Created: ${issue.createdAt}
- Updated: ${issue.updatedAt}
- Labels: ${issue.labels.map(l => l.name).join(', ')}

## ISSUE BODY
${issue.body}

## FETCH COMMENTS
Use: gh issue view ${issue.number} --repo ${REPO} --json comments

## PR CORRELATION (Check these for fixes)
${PR_LIST.slice(0, 10).map(pr => `- PR #${pr.number}: ${pr.title}`).join('\n')}

## ANALYSIS CHECKLIST
1. **TYPE**: BUG | QUESTION | FEATURE | INVALID
2. **PROJECT_VALID**: Is this relevant to OUR project? (YES/NO/UNCLEAR)
3. **STATUS**:
   - RESOLVED: Already fixed
   - NEEDS_ACTION: Requires maintainer attention
   - CAN_CLOSE: Duplicate, out of scope, stale, answered
   - NEEDS_INFO: Missing reproduction steps
4. **COMMUNITY_RESPONSE**: NONE | HELPFUL | WAITING
5. **LINKED_PR**: PR # that might fix this (or NONE)
6. **CRITICAL**: Is this a blocking bug/security issue? (YES/NO)

## RETURN FORMAT (STRICT)
\`\`\`
ISSUE: #${issue.number}
TITLE: ${issue.title}
TYPE: [BUG|QUESTION|FEATURE|INVALID]
VALID: [YES|NO|UNCLEAR]
STATUS: [RESOLVED|NEEDS_ACTION|CAN_CLOSE|NEEDS_INFO]
COMMUNITY: [NONE|HELPFUL|WAITING]
LINKED_PR: [#NUMBER|NONE]
CRITICAL: [YES|NO]
SUMMARY: [1-2 sentence summary]
ACTION: [Recommended maintainer action]
DRAFT_RESPONSE: [Template response if applicable, else "NEEDS_MANUAL_REVIEW"]
\`\`\`
`
  )

  // Store task ID for this issue
  taskMap.set(issue.number, taskId)
}

console.log(`\n✅ Launched ${taskMap.size} background tasks (1 per issue)`)

AFTER Phase 3: Update todo, mark Phase 4 as in_progress.


PHASE 4: STREAM RESULTS AS EACH TASK COMPLETES

REAL-TIME STREAMING COLLECTION

const results = []
const critical = []
const closeImmediately = []
const autoRespond = []
const needsInvestigation = []
const featureBacklog = []
const needsInfo = []

const completedIssues = new Set()
const totalIssues = taskMap.size

console.log(`\n📊 Streaming results for ${totalIssues} issues...`)

// Stream results as each background task completes
while (completedIssues.size < totalIssues) {
  let newCompletions = 0

  for (const [issueNumber, taskId] of taskMap) {
    if (completedIssues.has(issueNumber)) continue

    // Non-blocking check for this specific task
    const output = await background_output(task_id=taskId, block=false)

    if (output && output.length > 0) {
      // Parse the completed analysis
      const analysis = parseAnalysis(output)
      results.push(analysis)
      completedIssues.add(issueNumber)
      newCompletions++

      // REAL-TIME STREAMING REPORT
      console.log(`\n🔄 Issue #${issueNumber}: ${analysis.TITLE.substring(0, 60)}...`)

      // Immediate categorization & reporting
      let icon = "📋"
      let status = ""

      if (analysis.CRITICAL === 'YES') {
        critical.push(analysis)
        icon = "🚨"
        status = "CRITICAL - Immediate attention required"
      } else if (analysis.STATUS === 'CAN_CLOSE') {
        closeImmediately.push(analysis)
        icon = "⚠️"
        status = "Can be closed"
      } else if (analysis.STATUS === 'RESOLVED') {
        closeImmediately.push(analysis)
        icon = "✅"
        status = "Resolved - can close"
      } else if (analysis.DRAFT_RESPONSE !== 'NEEDS_MANUAL_REVIEW') {
        autoRespond.push(analysis)
        icon = "💬"
        status = "Auto-response available"
      } else if (analysis.TYPE === 'FEATURE') {
        featureBacklog.push(analysis)
        icon = "💡"
        status = "Feature request"
      } else if (analysis.STATUS === 'NEEDS_INFO') {
        needsInfo.push(analysis)
        icon = "❓"
        status = "Needs more info"
      } else if (analysis.TYPE === 'BUG') {
        needsInvestigation.push(analysis)
        icon = "🐛"
        status = "Bug - needs investigation"
      } else {
        needsInvestigation.push(analysis)
        icon = "👀"
        status = "Needs investigation"
      }

      console.log(`   ${icon} ${status}`)
      console.log(`   📊 Action: ${analysis.ACTION}`)

      // Progress update every 5 completions
      if (completedIssues.size % 5 === 0) {
        console.log(`\n📈 PROGRESS: ${completedIssues.size}/${totalIssues} issues analyzed`)
        console.log(`   Critical: ${critical.length} | Close: ${closeImmediately.length} | Auto-Reply: ${autoRespond.length} | Investigate: ${needsInvestigation.length} | Features: ${featureBacklog.length} | Needs Info: ${needsInfo.length}`)
      }
    }
  }

  // If no new completions, wait briefly before checking again
  if (newCompletions === 0 && completedIssues.size < totalIssues) {
    await new Promise(r => setTimeout(r, 2000))
  }
}

console.log(`\n✅ All ${totalIssues} issues analyzed`)

PHASE 5: FINAL COMPREHENSIVE REPORT

GENERATE THIS AT THE VERY END - AFTER ALL PROCESSING

# Issue Triage Report - ${REPO}

**Time Range:** Last ${TIME_RANGE} hours
**Generated:** ${new Date().toISOString()}
**Total Issues Analyzed:** ${results.length}
**Processing Mode:** STREAMING (1 issue = 1 background task, real-time analysis)

---

## 📊 Summary

| Category | Count | Priority |
|----------|-------|----------|
| 🚨 CRITICAL | ${critical.length} | IMMEDIATE |
| ⚠️ Close Immediately | ${closeImmediately.length} | Today |
| 💬 Auto-Respond | ${autoRespond.length} | Today |
| 🐛 Needs Investigation | ${needsInvestigation.length} | This Week |
| 💡 Feature Backlog | ${featureBacklog.length} | Backlog |
| ❓ Needs Info | ${needsInfo.length} | Awaiting User |

---

## 🚨 CRITICAL (Immediate Action Required)

${critical.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 50)}... | ${i.TYPE} |`).join('\n')}

**Action:** These require immediate maintainer attention.

---

## ⚠️ Close Immediately

${closeImmediately.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 50)}... | ${i.STATUS} |`).join('\n')}

---

## 💬 Auto-Respond (Template Ready)

${autoRespond.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 40)}... |`).join('\n')}

**Draft Responses:**
${autoRespond.map(i => `### #${i.ISSUE}\n${i.DRAFT_RESPONSE}\n`).join('\n---\n')}

---

## 🐛 Needs Investigation

${needsInvestigation.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 50)}... | ${i.TYPE} |`).join('\n')}

---

## 💡 Feature Backlog

${featureBacklog.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 50)}... |`).join('\n')}

---

## ❓ Needs More Info

${needsInfo.map(i => `| #${i.ISSUE} | ${i.TITLE.substring(0, 50)}... |`).join('\n')}

---

## 🎯 Immediate Actions

1. **CRITICAL:** ${critical.length} issues need immediate attention
2. **CLOSE:** ${closeImmediately.length} issues can be closed now
3. **REPLY:** ${autoRespond.length} issues have draft responses ready
4. **INVESTIGATE:** ${needsInvestigation.length} bugs need debugging

---

## Processing Log

${results.map((r, i) => `${i+1}. #${r.ISSUE}: ${r.TYPE} (${r.CRITICAL === 'YES' ? 'CRITICAL' : r.STATUS})`).join('\n')}

CRITICAL ANTI-PATTERNS (BLOCKING VIOLATIONS)

ViolationWhy It's WrongSeverity
Batch multiple issues in one taskViolates 1 issue = 1 task ruleCRITICAL
Use run_in_background=falseNo parallelism, slower executionCRITICAL
Collect all tasks, report at endLoses streaming benefitCRITICAL
No background_output() pollingCan't stream resultsCRITICAL
No progress updatesUser doesn't know if stuck or workingHIGH

EXECUTION CHECKLIST

  • Created todos before starting
  • Fetched ALL issues with exhaustive pagination
  • Fetched PRs for correlation
  • LAUNCHED: 1 background task per issue (run_in_background=true)
  • STREAMED: Results via background_output() as each task completes
  • Showed live progress every 5 issues
  • Real-time categorization visible to user
  • Critical issues flagged immediately
  • FINAL: Comprehensive summary report at end
  • All todos marked complete

Quick Start

When invoked, immediately:

  1. CREATE TODOS
  2. gh repo view --json nameWithOwner -q.nameWithOwner
  3. Parse time range (default: 48 hours)
  4. Exhaustive pagination for issues
  5. Exhaustive pagination for PRs
  6. LAUNCH: For each issue:

- task(run_in_background=true) - 1 task per issue - Store taskId mapped to issue number

  1. STREAM: Poll background_output() for each task:

- As each completes, immediately report result - Categorize in real-time - Show progress every 5 completions

  1. GENERATE FINAL COMPREHENSIVE REPORT

平台分布

Codex

39.22%
按下载量换算4,201

Claude

28.84%
按下载量换算3,089

Cursor

18.75%
按下载量换算2,009

Gemini CLI

9.6%
按下载量换算1,028

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。

继续浏览同类 Skills