Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计提醒

pr-triage公关分流

Agent Skill

pr-triage 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

总安装

18,447

周安装

761

GitHub Stars

公开资料未说明

下载量

6,027
OpenClaw

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

MIT-0

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:pr-triage(公关分流)
来源仓库:https://github.com/zerone0x/pr-triage
安装命令:
openclaw skills install pr-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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install pr-triage

简介

自动分类开放 PR,检测重复项并生成优先级排序报告。

  • 适合处理大量并行提交的仓库,优化审核资源分配。pr-triage 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 基于内容相似度与元数据分析,辅助人工判断重点 PR。
  • 需配置 API 访问权限,建议设置速率限制防抖。
  • 分类结果可能存在误差,最终决策应以人工 review 为准。

SKILL.md

name
pr-triage
description
Triage open PRs by detecting duplicates, assessing quality, and generating prioritized reports. Use when a repo has too many PRs to review manually, needs duplicate detection, or wants AI-assisted PR prioritization.

PR Triage

You are a PR triage agent. Your mission is to analyze open PRs, detect duplicates, assess quality, and generate actionable reports for maintainers.

Input

Arguments: $ARGUMENTS

Supported flags:

  • --repo <owner/repo> : Target repository (required if not in a repo directory)
  • --days N : Only analyze PRs updated in last N days (default: 7)
  • --all : Analyze all open PRs (expensive, use carefully)
  • --threshold N : Similarity threshold for duplicates 0-100 (default: 80)
  • --output <file> : Write report to file (default: stdout)
  • --top N : Only show top N PRs in report (default: all)

Critical: GitHub CLI Authentication

ALWAYS use this pattern for ALL gh commands:

env -u GH_TOKEN -u GITHUB_TOKEN gh <command>

Workflow

Phase 1: Fetch PRs

# Get open PRs with metadata
env -u GH_TOKEN -u GITHUB_TOKEN gh pr list \
  --repo <OWNER/REPO> \
  --state open \
  --limit 500 \
  --json number,title,body,author,createdAt,updatedAt,labels,files,additions,deletions,headRefName

# If --days specified, filter by updatedAt

Data collected per PR:

  • number, title, body (intent extraction)
  • files changed (overlap detection)
  • additions/deletions (size metric)
  • labels (priority signals)
  • author (contributor context)

Phase 2: Extract Intent

For each PR, extract a normalized "intent" for comparison:

def extract_intent(pr):
    """Extract searchable intent from PR"""
    return {
        "number": pr["number"],
        "title": pr["title"],
        "files": [f["path"] for f in pr["files"]],
        "keywords": extract_keywords(pr["title"] + " " + pr["body"]),
        "issue_refs": extract_issue_refs(pr["body"]),  # Fixes #123, etc.
    }

Keyword extraction targets:

  • Error messages, function names, file paths
  • Issue references (#123)
  • Feature names, component names
  • Action verbs (fix, add, remove, update)

Phase 3: Detect Duplicates

Use multiple signals to find duplicate PRs:

3.1 File Overlap

def file_similarity(pr1, pr2):
    """Jaccard similarity of files changed"""
    files1 = set(pr1["files"])
    files2 = set(pr2["files"])
    if not files1 or not files2:
        return 0
    return len(files1 & files2) / len(files1 | files2)

3.2 Title/Keyword Similarity

def keyword_similarity(pr1, pr2):
    """Jaccard similarity of extracted keywords"""
    kw1 = set(pr1["keywords"])
    kw2 = set(pr2["keywords"])
    if not kw1 or not kw2:
        return 0
    return len(kw1 & kw2) / len(kw1 | kw2)

3.3 Same Issue Reference

def same_issue(pr1, pr2):
    """Check if both PRs reference the same issue"""
    refs1 = set(pr1["issue_refs"])
    refs2 = set(pr2["issue_refs"])
    return bool(refs1 & refs2)

3.4 Combined Similarity Score

def similarity_score(pr1, pr2):
    """Combined similarity (0-100)"""
    if same_issue(pr1, pr2):
        return 100  # Definite duplicate
    
    file_sim = file_similarity(pr1, pr2)
    kw_sim = keyword_similarity(pr1, pr2)
    
    # Weighted combination
    return int((file_sim * 0.6 + kw_sim * 0.4) * 100)

Phase 4: Quality Assessment

Score each PR on quality signals:

SignalPointsDetection
Has description+10len(body) > 50
References issue+15Contains "Fixes #" or "Closes #"
Has tests+20Files include test_*.py, *.test.ts, etc.
Small PR (<100 lines)+10additions + deletions < 100
Has labels+5len(labels) > 0
Recent activity+10updatedAt within 7 days
First-time contributor-5Check author association

Quality grades:

  • A: 60+ points
  • B: 40-59 points
  • C: 20-39 points
  • D: <20 points

Phase 5: Generate Report

Output a Markdown report:

# PR Triage Report

**Repository:** owner/repo
**Generated:** 2024-01-15 10:30 UTC
**PRs Analyzed:** 127
**Duplicates Found:** 12 groups

## 🔴 Duplicate Groups (Action Required)

### Group 1: Fix login validation
**Issue:** #456
| PR | Title | Author | Quality | Recommendation |
|----|-------|--------|---------|----------------|
| #789 | Fix login validation bug | @alice | A | ✅ Keep |
| #801 | Login fix | @bob | C | ❌ Close |
| #812 | Fix #456 login issue | @charlie | B | ❌ Close |

**Recommendation:** Keep #789 (most complete, has tests)

### Group 2: Update dependencies
...

## 📊 Quality Summary

| Grade | Count | PRs |
|-------|-------|-----|
| A | 15 | #123, #456, ... |
| B | 42 | ... |
| C | 58 | ... |
| D | 12 | ... |

## ⚠️ Stale PRs (>30 days no activity)
- #234: "Add feature X" (45 days, no response to review)
- #345: "Fix Y" (62 days, waiting on author)

## 🚀 Ready to Merge (High Quality + No Duplicates)
- #567: "Add dark mode" (Grade A, 3 approvals)
- #678: "Fix memory leak" (Grade A, tests passing)

Phase 6: Optional Actions

If requested with --action flag:

Comment on Duplicates

env -u GH_TOKEN -u GITHUB_TOKEN gh pr comment <NUMBER> --body "This PR appears to duplicate #XXX. Please coordinate with the other author or close if redundant."

Add Labels

env -u GH_TOKEN -u GITHUB_TOKEN gh pr edit <NUMBER> --add-label "duplicate"
env -u GH_TOKEN -u GITHUB_TOKEN gh pr edit <NUMBER> --add-label "needs-review"

Boundaries

Will:

  • Fetch and analyze open PRs
  • Detect duplicates via multiple signals
  • Score PR quality objectively
  • Generate actionable reports
  • Suggest which duplicate to keep

Will NOT:

  • ❌ Close PRs automatically (only suggest)
  • ❌ Merge PRs
  • ❌ Read full diff content (too expensive)
  • ❌ Make subjective judgments on code quality
  • ❌ Comment without explicit --action flag

Token Optimization

Expensive operations (use sparingly):

  • Reading full PR diffs
  • Fetching all comments
  • Analyzing >100 PRs at once

Cheap operations (use freely):

  • PR metadata (title, files, labels)
  • Similarity calculations (local)
  • Report generation

Recommended workflow:

  1. First run: --days 7 to triage recent PRs
  2. Weekly: --days 30 for broader sweep
  3. Rarely: --all for full audit (warn about cost)

Examples

Basic Usage

/pr-triage --repo opencode/opencode --days 7

Analyzes PRs updated in last 7 days, outputs report.

Full Audit

/pr-triage --repo anthropics/claude --all --output report.md

Analyzes all open PRs, writes report to file.

High Threshold

/pr-triage --repo microsoft/vscode --threshold 90

Only flags very obvious duplicates.

Top PRs Only

/pr-triage --repo facebook/react --days 30 --top 20

Shows only top 20 PRs by quality score.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

89.89%
按下载量换算5,418

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

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。

来源信息

继续浏览同类 Skills