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repo-pr-triage回购分类

Agent Skill

repo-pr-triage 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

22,424

周安装

916

GitHub Stars

公开资料未说明

下载量

7,255
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:repo-pr-triage(回购分类)
来源仓库:https://github.com/patrob/repo-pr-triage
安装命令:
openclaw skills install repo-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 repo-pr-triage

简介

回购分类用于基于视觉评分对 GitHub PR 和问题进行分类。

  • 支持优先级判定、去重与批量处理打开请求。
  • 通过 clawhub 安装后,配置仓库权限即可调用服务。
  • 评分结果供参考,需人工二次确认。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • repo-pr-triage 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
pr-triage
description
Triage GitHub PRs and issues using vision-based scoring. Use when a user wants to prioritize, score, review, de-duplicate, or batch-process open pull requests or issues against their project's mission and values. Supports onboarding (interview repo owner to build vision doc), scanning (score PRs with rubric), and reporting (generate actionable markdown reports). Works with any GitHub repo via gh CLI.

PR Triage

Score and prioritize GitHub PRs against a project's vision document. Three-step workflow: onboard, scan, report.

Quick Start

# 1. Onboard: gather repo context, interview the owner
python3 scripts/onboard.py https://github.com/owner/repo --output-dir ./triage-config

# 2. Scan: score open PRs against the vision
python3 scripts/scan.py https://github.com/owner/repo ./triage-config/vision.md --output scores.json

# 3. Report: generate markdown triage reports
python3 scripts/report.py scores.json --output-dir ./triage-reports

Workflow

Step 1: Onboard (one-time per repo)

Run scripts/onboard.py with a GitHub repo URL. It fetches the README, CONTRIBUTING.md, recent releases, and repo metadata via gh CLI, then outputs an interview prompt.

Use the interview prompt to ask the repo owner these questions:

Identity & Mission:

  1. In one sentence, what is this project and who is it for?
  2. What problem does it solve that alternatives do not?
  3. What are your 3-5 non-negotiable principles?

Priorities:

  1. Rank contribution areas by importance: security, bugs, features, performance, docs, tests, refactoring
  2. What types of PRs would you auto-reject?
  3. What types of PRs would you fast-track?

Red/Green Flags:

  1. What patterns signal low-quality contributions?
  2. What makes you excited to review a PR?
  3. Specific areas where you want help?

Context:

  1. Growth mode, maintenance mode, or transitioning?
  2. Upcoming milestones affecting prioritization?
  3. How do you handle breaking changes?

After the interview, generate two files in the output directory:

  • vision.md - Project mission, identity, priorities, alignment signals
  • rubric.md - Scoring rubric customized from references/rubric-template.md

Step 2: Scan (run per triage session)

Run scripts/scan.py with the repo URL and vision doc path. It:

  • Fetches open PRs via gh pr list (title, body, labels, stats, author, date)
  • Applies rule-based scoring: base 50, with positive/negative modifiers
  • Detects potential duplicates via title similarity
  • Outputs JSON with scores, reasoning, and distribution

The scan uses heuristic scoring (keyword matching, diff size, test mentions). For deeper analysis, read the JSON output and apply additional LLM reasoning to ambiguous PRs (scores 40-60).

Options:

  • --count N - Number of PRs to fetch (default: 100)
  • --output file.json - Save to file instead of stdout

Step 3: Report (run after scan)

Run scripts/report.py with the scan JSON. It generates four markdown files:

  • prioritize.md - PRs scoring 80+ (fast-track for review)
  • review.md - PRs scoring 50-79 (standard queue)
  • close.md - PRs scoring below 50 (likely close or request changes)
  • summary.md - Distribution, top 3, patterns, duplicates, active authors

Scoring Overview

Base score: 50. Key modifiers:

SignalPoints
Security fix+20
Bug fix with tests+10
Core functionality improvement+10
Performance (measured)+8
Small focused diff+5
Has tests+5
Spam/promotion-30
Unwanted dependency-25
Large diff, no tests-15
No description-5

Full rubric: references/rubric-template.md Example vision doc: references/example-vision.md

Recurring Triage via Cron

Set up a cron job to scan weekly:

description: Weekly PR triage for owner/repo
schedule: "0 9 * * MON"
model: anthropic/claude-sonnet-4-20250514
channel: telegram

Cron prompt: "Run pr-triage scan on https://github.com/owner/repo using ./triage-config/vision.md, generate reports, and send the summary."

Requirements

  • gh CLI installed and authenticated (gh auth login)
  • Python 3.10+
  • No additional Python packages needed (stdlib only)

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

80.66%
按下载量换算5,852

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

安装前确认

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来源信息

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