GitHub Issue Finder / GitHub Issue 查找助手

English: An AI agent skill for discovering, evaluating, and claiming good first issue targets across curated open source repositories.

中文： 一个帮助你在 GitHub 上发现、评估并认领优质开源 issue 的 AI agent 技能。从优质项目中精挑细选，配合完整的工作流程，助你完成从找 issue 到提 PR 的全过程。

🔍 Overview / 总览

English

Finding a meaningful and well-suited open source issue to contribute to is one of the biggest friction points for new contributors. Broad searches across GitHub are flooded with bounty listings, auto-generated issues, and stale tickets — making it hard to find real, actionable work.

This skill solves that by providing:

A targeted search strategy across hand-picked, high-quality repositories
Automatic spam/bounty filtering to cut through the noise
A structured workflow from discovery to PR submission
GFW compatibility via the GitHub REST API (no git clone required)

中文

找开源练手项目最大的难点在于：GitHub 全量搜索结果充斥着 Copilot bounty 垃圾 issue、自动生成的占坑帖和长期无人处理的僵尸 issue，根本找不到真正可以动手的活。

本技能解决这个痛点：

定向仓库搜索：从优质项目中精准找 issue，绕过垃圾
自动过滤 bounty/spam：去掉赏金帖和自动生成的垃圾
结构化工作流：从发现到 PR 提交，全程有指引
GFW 友好：通过 GitHub REST API 搜索，无需 git clone

✨ Features / 功能特点

Feature	功能
Batch repo search	批量仓库搜索，一次查多个项目
Bounty & spam filter	自动过滤 bounty / reward / Copilot 垃圾 issue
Difficulty tiers	按难度分级：入门 → 进阶 → 挑战
Multi-language	覆盖 Python、JavaScript/TypeScript、Go、Rust 等
API-first design	纯 API 设计，绕过 GFW，不依赖 git 协议
AI agent native	支持 OpenClaw / QClaw 加载，从 SKILL.md 启动
Bilingual docs	中英双语文档，方便理解与使用

🚀 Quick Start / 快速上手

Prerequisites / 前提条件

Python 3.8 or higher / Python 3.8 及以上版本
A GitHub PAT with repo scope
（可选）OpenClaw / QClaw AI agent

1. Install / 安装

~/.qclaw/skills/github-issue-finder-skill/

Or / 或：

skillhub_install install_skill github-issue-finder-skill

2. Set Token / 设置 Token

# Linux / macOS
export GITHUB_TOKEN="ghp_your_token_here"

# Windows (PowerShell)
$env:GITHUB_TOKEN = "ghp_your_token_here"

Note / 注意： Without a PAT, rate limit is 60 req/hour. With PAT: 5,000 req/hour. 无 PAT 限速 60 次/小时，有 PAT 限速 5,000 次/小时。

3. Search / 搜索

# Search single repo / 搜索单个仓库
python scripts/search_good_first_issues.py --repos "streamlit/streamlit" --labels "good first issue" --limit 10

# Search multiple repos / 搜索多个仓库
python scripts/search_good_first_issues.py --repos "pylint-dev/pylint,celery/celery" --labels "good first issue" --limit 5

# Custom label / 自定义标签
python scripts/search_good_first_issues.py --repos "facebook/react" --labels "good first bug" --limit 10

4. Search with Memory / 启动记忆存储

# Start the memory service first
python scripts/memory_service.py

# Search and automatically store results + generate work report
python scripts/search_good_first_issues.py --repos "streamlit/streamlit" --memory

Memory Integration / 记忆系统集成

This skill integrates with a standalone memory service (memory_service.py) for persistent storage:

Search results are stored as memory nodes (github:issue:{number}:{owner}/{repo})
Work reports are auto-generated and saved at the end of each workflow
Master index (index:work-reports) tracks all reports for quick lookup

Architecture

search_good_first_issues.py
    │  --memory flag
    ├── memory_client.py ──HTTP──▶ memory_service:9099
    │                                   │
    │                           long_term_memory.db (SQLite)
    │                                   │
    └── work_report.py ──HTTP──▶ memory_service:9099
                                    store + index update

Query Reports / 查询工作报告

from memory_client import MemoryClient
import json

mc = MemoryClient()
idx = mc.recall("index:work-reports")
keys = json.loads(idx["value"])

for key in keys:
    report = mc.recall(key)
    data = json.loads(report["value"])
    print(data["summary"])

Work Queue / 工作队列

中文： 自动追踪和管理已发现的问题，避免重复处理。

Overview / 概述

The work queue system tracks discovered issues through their lifecycle:

found → analyzed → done

Automatically skips already processed issues on subsequent searches.

Functions / 函数

Function	Description	描述
`should_skip(key)`	Check if issue is already processed / 检查issue是否已处理
`add_issue_to_queue(key, data)`	Add issue to work queue / 将issue加入工作队列
`list_work_queue()`	List all pending issues / 列出待处理issue
`mark_issue_done(key)`	Mark issue as done / 标记issue为已完成

Usage / 使用方式

from work_queue import should_skip, add_issue_to_queue, list_work_queue

# Check before processing
issue_key = "github:issue:123:owner/repo"
if should_skip(issue_key):
    print("Skipping - already processed")
else:
    add_issue_to_queue(issue_key, {"number": 123, "title": "..."})

# List pending
list_work_queue()

# Mark done after PR submitted  
mark_issue_done(issue_key)

CLI Commands / 命令行

python scripts/work_ queue.py list       # 列出待办 / List pending
python scripts/work_queue.py done <key>  # 标记完成 / Mark done

Work Report / 工作报告

At the end of every workflow, a structured work report is generated and saved:

Key format: report:{timestamp}:{session}
Contains: discovery summary, issues found, PRs submitted, stats
Master index: index:work-reports lists all report keys

Manual Report / 手动生成报告

from work_report import WorkReport
report = WorkReport(mem_client, session_tag="my_session")
report.add_issue("owner/repo", 123, "Title", "https://...", action="found")
report.add_pr("owner/repo", 456, "PR title", "https://...", status="submitted")
report.add_note("Any note about the work")
report.save()

4. (Optional) Push without git protocol / 无 git 协议推送

If git push is blocked on your network, use the GitHub API to push commits directly.

📋 Recommended Repositories / 推荐仓库

Start here for your first contribution / 从这里开始你的第一次贡献：

Repository / 仓库	Stars	Difficulty / 难度	Highlight Issues / 推荐 Issue
streamlit/streamlit	34k	⭐ Beginner / 入门	#9098 ✅ · #11643
pylint-dev/pylint	19k	⭐ Beginner / 入门	#9143 · #10281
yt-dlp/yt-dlp	120k+	⭐ Beginner / 入门	Browse all
pytest-dev/pytest	17k	⭐⭐ Intermediate / 进阶	Browse all
celery/celery	24k	⭐⭐ Intermediate / 进阶	Browse all
django/django	81k	⭐⭐ Intermediate / 进阶	Browse all

✅ = Fixed & merged / 已修复并合并 Full list / 完整列表：see references/recommended_repos.md

🔄 Full Workflow / 完整工作流

┌────────────────────────────────────────────────────────────┐
│  1. SEARCH  →  搜索 good first issue / Run the search     │
│  2. EVALUATE →  评估 issue 质量 / Check comments/labels   │
│  3. ANALYZE  →  阅读源码，理解问题 / Study the codebase     │
│  4. IMPLEMENT →  写代码 + 测试 / Implement fix + tests      │
│  5. SUBMIT   →  提 PR，等待 review / Open PR, iterate      │
└────────────────────────────────────────────────────────────┘

Evaluating an Issue / 评估 Issue

Before diving in / 开始前检查：

Comments / 评论 — Has a maintainer commented? / 维护者有没有回复过？
Labels / 标签 — good first issue? help wanted? type:feature?
Linked code / 代码引用 — Does it reference specific files/functions? / 有没有指向具体文件？
Recency / 时效 — Active in the last 6 months? / 6个月内有没有更新？
PR history / PR 历史 — Any related closed PRs to learn from? / 有没有相关的已关闭 PR？

Opening a Pull Request / 提交 Pull Request

Fork the repository / Fork 目标仓库
Create branch: git checkout -b fix/issue-number-brief-description
Implement the change / 实现修改
Write or update tests / 写/更新测试
Push: git push origin fix/issue-number-brief-description
Open a PR, reference the issue (e.g. Closes #9098)
Respond to review feedback patiently / 耐心等待维护者 review

📚 Case Study / 实战案例

✅ Streamlit #9098 — SVG viewBox 宽度修复 / SVG viewBox Width Fix

Full process: from discovery to merged PR / 完整流程：从发现 issue 到 PR 合并

Issue Background / Issue 背景

Issue: #9098 — SVG renders as blank when width is not explicitly set
Repository: streamlit/streamlit ⭐ 34k
Difficulty: ⭐ Beginner / 入门级
Date: Issue opened 2024-07-18, Fix merged 2026-05-09

Problem / 问题

When using st.image() with an SVG file that has no explicit width attribute on the <svg> tag, the image renders as a blank (0×0 size) in the browser.

The root cause: st.image() converts SVGs to base64 data URIs embedded in <img> tags. When no width is specified, the browser renders the SVG data URI at 0×0 dimensions.

Solution / 解决方案

In lib/streamlit/elements/lib/image_utils.py, parse the viewBox attribute to infer default width/height when explicit dimensions are missing, then inject them into the <svg> tag:

# If width/height attributes are missing, infer from viewBox
if "width=" not in svg_tag and "height=" not in svg_tag:
    vb_match = re.search(r'viewBox="([^"]+)"', svg_tag)
    if vb_match:
        parts = vb_match.group(1).strip().split()
        if len(parts) == 4:
            vb_w, vb_h = float(parts[2]), float(parts[3])
            svg_tag_new = svg_tag.replace(
                f"<svg{attrs}>",
                f'<svg{attrs} width="{int(vb_w)}" height="{int(vb_h)}">',
                1
            )
            image = image.replace(svg_tag, svg_tag_new, 1)

Result / 结果

Commit: cdfbadaa2b3c37453fa99e3ffd0df812588618cf
PR: quick123-666/streamlit/pull/1
Status: ✅ Branch pushed, PR submitted for review

Key Takeaways / 经验总结

Source code access with GFW / GFW 下的源码获取： Use GitHub REST API to download files directly instead of git clone
Push without git protocol / 绕过 git 协议推送： GitHub API (PUT /repos/{owner}/{repo}/contents/{path}) can create branches and push commits directly — useful when git is blocked
viewBox parsing / viewBox 解析: viewBox="min_x min_y width height" — the 3rd and 4th values are the natural dimensions
Minimal fix / 最小修改原则: The Python-side fix only modified one file, no frontend changes needed

🔧 Filtering Strategy / 过滤策略

Why targeted search / 为什么定向搜索

A global good first issue search returns 60,000+ results — the vast majority are auto-generated bounty listings (Copilot, Reward-Bound, etc.). They pollute results with keywords but have no actual contribution path.

Strategy / 策略

Search directly within well-maintained, high-STAR repositories
Filter out known spam: bounty, reward, payment, Reward-Bound, Copilot body text
Filter out auto-created issues with no comments, short titles, no linked code

📁 Project Structure / 项目结构

github-issue-finder-skill/
├── SKILL.md                              # AI agent workflow guide / AI agent 工作流指引
├── README.md                             # This file
├── scripts/
│   ├── search_good_first_issues.py       # Batch search script / 批量搜索脚本
│   ├── memory_service.py      # Standalone HTTP+SQLite memory service / 独立记忆服务
│   ├── memory_client.py        # Memory service HTTP client / 记忆服务客户端
│   └── work_report.py          # Work report generator + master index / 工作报告生成器 + 总索引
└── references/
    ├── recommended_repos.md               # Curated repo list / 推荐仓库列表
    └── github_api_search.md               # GitHub API reference / API 参考文档

📡 GitHub API Reference / API 参考

Auth / 认证	Rate limit / 限速	Available endpoints / 可用端点
None / 无	60 req/hour	`GET /search/issues`
PAT	5,000 req/hour	Full access / 完全访问

See / 详见：references/github_api_search.md

🤖 For AI Agents / AI Agent 使用说明

Designed to be loaded by OpenClaw / QClaw. Relevant trigger phrases / 触发词：

"找开源项目练手" / "Find a good first issue on GitHub"
"帮我找一个 good first issue" / "Help me find an open source issue"
"开源贡献入门" / "Open source contribution guide"
"GitHub first contribution" / "找一个开源 issue 来做"
"去找点活干" / "find something to do"
"生成工作报告" / "generate work report"

When triggered, the agent reads SKILL.md and references/ to execute the full discovery and evaluation workflow. If --memory is enabled, search results are persisted and a work report is auto-generated at the end.

📖 Further Reading / 延伸阅读

📄 License

MIT — free to use, modify, and distribute.

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
references		references
scripts		scripts
.gitignore		.gitignore
README.md		README.md
SKILL.md		SKILL.md

Folders and files

Latest commit

History

Repository files navigation

GitHub Issue Finder / GitHub Issue 查找助手

🔍 Overview / 总览

English

中文

✨ Features / 功能特点

🚀 Quick Start / 快速上手

Prerequisites / 前提条件

1. Install / 安装

2. Set Token / 设置 Token

3. Search / 搜索

4. Search with Memory / 启动记忆存储

Memory Integration / 记忆系统集成

Architecture

Query Reports / 查询工作报告

Work Queue / 工作队列

Overview / 概述

Functions / 函数

Usage / 使用方式

CLI Commands / 命令行

Work Report / 工作报告

Manual Report / 手动生成报告

4. (Optional) Push without git protocol / 无 git 协议推送

📋 Recommended Repositories / 推荐仓库

🔄 Full Workflow / 完整工作流

Evaluating an Issue / 评估 Issue

Opening a Pull Request / 提交 Pull Request

📚 Case Study / 实战案例

✅ Streamlit #9098 — SVG viewBox 宽度修复 / SVG viewBox Width Fix

Issue Background / Issue 背景

Problem / 问题

Solution / 解决方案

Result / 结果

Key Takeaways / 经验总结

🔧 Filtering Strategy / 过滤策略

Why targeted search / 为什么定向搜索

Strategy / 策略

📁 Project Structure / 项目结构

📡 GitHub API Reference / API 参考

🤖 For AI Agents / AI Agent 使用说明

📖 Further Reading / 延伸阅读

📄 License

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