github-explorer▌
blessonism/github-explorer-skill · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Philosophy: README 只是门面,真正的价值藏在 Issues、Commits 和社区讨论里。
GitHub Explorer — 项目深度分析
Philosophy: README 只是门面,真正的价值藏在 Issues、Commits 和社区讨论里。
Workflow
[项目名] → [1. 定位 Repo] → [2. 多源采集] → [3. 分析研判] → [4. 结构化输出]
Phase 1: 定位 Repo
- 用
web_search搜索site:github.com <project_name>确认完整 org/repo - 用
search-layer(Deep 模式 + 意图感知)补充获取社区链接和非 GitHub 资源:python3 skills/search-layer/scripts/search.py \ --queries "<project_name> review" "<project_name> 评测 使用体验" \ --mode deep --intent exploratory --num 5 - 用
web_fetch抓取 repo 主页获取基础信息(README、Stars、Forks、License、最近更新)
Phase 2: 多源采集(并行)
⚠️ GitHub 页面抓取规则(强制):GitHub repo 页面是 SPA(客户端渲染),web_fetch 只能拿到导航栏壳子,禁止用 web_fetch 抓 github.com 的 repo 页面。一律使用 GitHub API:
- README:
curl -s -H "Authorization: token {PAT}" -H "Accept: application/vnd.github.v3.raw" "https://api.github.com/repos/{owner}/{repo}/readme" - Repo 元数据:
curl -s -H "Authorization: token {PAT}" "https://api.github.com/repos/{owner}/{repo}" - Issues:
curl -s -H "Authorization: token {PAT}" "https://api.github.com/repos/{owner}/{repo}/issues?state=all&sort=comments&per_page=10" - Commits:
curl -s -H "Authorization: token {PAT}" "https://api.github.com/repos/{owner}/{repo}/commits?per_page=10" - File tree:
curl -s -H "Authorization: token {PAT}" "https://api.github.com/repos/{owner}/{repo}/git/trees/{branch}?recursive=1"
PAT 见 TOOLS.md。
以下来源按需检查,有则采集,无则跳过:
| 来源 | URL 模式 | 采集内容 | 建议工具 |
|---|---|---|---|
| GitHub Repo | github.com/{org}/{repo} |
README、About、Contributors | web_fetch |
| GitHub Issues | github.com/{org}/{repo}/issues?q=sort:comments |
Top 3-5 高质量 Issue | browser |
| 中文社区 | 微信/知乎/小红书 | 深度评测、使用经验 | content-extract |
| 技术博客 | Medium/Dev.to | 技术架构分析 | web_fetch / content-extract |
| 讨论区 | V2EX/Reddit | 用户反馈、槽点 | search-layer(Deep 模式) |
search-layer 调用规范
search-layer v2 支持意图感知评分。github-explorer 场景下的推荐用法:
| 场景 | 命令 | 说明 |
|---|---|---|
| 项目调研(默认) | python3 skills/search-layer/scripts/search.py --queries "<project> review" "<project> 评测" --mode deep --intent exploratory --num 5 |
多查询并行,按权威性排序 |
| 最新动态 | python3 skills/search-layer/scripts/search.py "<project> latest release" --mode deep --intent status --freshness pw --num 5 |
优先新鲜度,过滤一周内 |
| 竞品对比 | python3 skills/search-layer/scripts/search.py --queries "<project> vs <competitor>" "<project> alternatives" --mode deep --intent comparison --num 5 |
对比意图,关键词+权威双权重 |
| 快速查链接 | python3 skills/search-layer/scripts/search.py "<project> official docs" --mode fast --intent resource --num 3 |
精确匹配,最快 |
| 社区讨论 | python3 skills/search-layer/scripts/search.py "<project> discussion experience" --mode deep --intent exploratory --domain-boost reddit.com,news.ycombinator.com --num 5 |
加权社区站点 |
意图类型速查:factual(事实) / status(动态) / comparison(对比) / tutorial(教程) / exploratory(探索) / news(新闻) / resource(资源定位)
不带
--intent时行为与 v1 完全一致(无评分,按原始顺序输出)。
降级规则:Exa/Tavily 任一 429/5xx → 继续用剩余源;脚本整体失败 → 退回 web_search 单源。
抓取降级与增强协议 (Extraction Upgrade)
当遇到以下情况时,必须从 web_fetch 升级为 content-extract:
- 域名限制:
mp.weixin.qq.com,zhihu.com,xiaohongshu.com。 - 结构复杂: 页面包含大量公式 (LaTeX)、复杂表格、或
web_fetch返回的 Markdown 极其凌乱。 - 内容缺失:
web_fetch因反爬返回空内容或 Challenge 页面。
调用方式:
python3 skills/content-extract/scripts/content_extract.py --url <URL>
content-extract 内部会:
- 先检查域名白名单(微信/知乎等),命中则直接走 MinerU
- 否则先用
web_fetch探针,失败再 fallback 到 MinerU-HTML - 返回统一 JSON 合同(含
ok,markdown,sources等字段)
Phase 3: 分析研判
基于采集数据进行判断:
- 项目阶段: 早期实验 / 快速成长 / 成熟稳定 / 维护模式 / 停滞(基于 commit 频率和内容)
- 精选 Issue 标准: 评论数多、maintainer 参与、暴露架构问题、或包含有价值的技术讨论
- 竞品识别: 从 README 的 "Comparison"/"Alternatives" 章节、Issues 讨论、以及 web 搜索中提取
Phase 4: 结构化输出
严格按以下模板输出,每个模块都必须有实质内容或明确标注"未找到"。
排版规则(强制)
- 标题必须链接到 GitHub 仓库(格式:
# [Project Name](https://github.com/org/repo),确保可点击跳转) - 标题前后都统一空行(上一板块结尾 → 空行 → 标题 → 空行 → 内容,确保视觉分隔清晰)
- Telegram 空行修复(强制):Telegram 会吞掉列表项(
-开头)后面的空行。解决方案:在列表末尾与下一个标题之间,插入一行盲文空格⠀(U+2800),格式如下:
这确保在 Telegram 渲染时标题前的空行不被吞掉。- 列表最后一项 ⠀ **下一个标题** - 所有标题加粗(emoji + 粗体文字)
- 竞品对比必须附链接(GitHub / 官网 / 文档,至少一个)
- 社区声量必须具体:引用具体的帖子/推文/讨论内容摘要,附原始链接。不要写"评价很高"、"热度很高"这种概括性描述,要写"某某说了什么"或"某帖讨论了什么具体问题"
- 信息溯源原则:所有引用的外部信息都应附上原始链接,让读者能追溯到源头
# [{Project Name}]({GitHub Repo URL})
**🎯 一句话定位**
{是什么、解决什么问题}
**⚙️ 核心机制**
{技术原理/架构,用人话讲清楚,不是复制 README。包含关键技术栈。}
**📊 项目健康度**
- **Stars**: {数量} | **Forks**: {数量} | **License**: {类型}
- **团队/作者**: {背景}
- **Commit 趋势**: {最近活跃度 + 项目阶段判断}
- **最近动态**: {最近几条重要 commit 概述}
**🔥 精选 Issue**
{Top 3-5 高质量 Issue,每条包含标题、链接、核心讨论点。如无高质量 Issue 则注明。}
**✅ 适用场景**
{什么时候该用,解决什么具体问题}
**⚠️ 局限**
{什么时候别碰,已知问题}
**🆚 竞品对比**
{同赛道项目对比,差异点。每个竞品必须附 GitHub 或官网链接,格式示例:}
- **vs [GraphRAG](https://github.com/microsoft/graphrag)** — 差异描述
- **vs [RAGFlow](https://github.com/infiniflow/ragflow)** — 差异描述
**🌐 知识图谱**
- **DeepWiki**: {链接或"未收录"}
- **Zread.ai**: {链接或"未收录"}
**🎬 Demo**
{在线体验链接,或"无"}
**📄 关联论文**
{arXiv 链接,或"无"}
**📰 社区声量**
**X/Twitter**
{具体引用推文内容摘要 + 链接,格式示例:}
- [@某用户](链接): "具体说了什么..."
- [某讨论串](链接): 讨论了什么具体问题...
{如未找到则注明"未找到相关讨论"}
**中文社区**
{具体引用帖子标题/内容摘要 + 链接,格式示例:}
- [知乎: 帖子标题](链接) — 讨论了什么
- [V2EX: 帖子标题](链接) — 讨论了什么
{如未找到则注明"未找到相关讨论"}
**💬 我的判断**
{主观评价:值不值得投入时间,适合什么水平的人,建议怎么用}
Execution Notes
- 优先使用
web_search+web_fetch,browser 作为备选 - 搜索增强:项目调研类任务默认使用
search-layerv2 Deep 模式 +--intent exploratory(Brave + Exa + Tavily 三源并行去重 + 意图感知评分),单源失败不阻塞主流程 - 抓取降级(强制):当
web_fetch失败/403/反爬页/正文过短,或来源域名属于高风险站点(如微信/知乎/小红书)时:改用content-extract(其内部会 fallback 到 MinerU-HTML),拿到更干净的 Markdown + 可追溯 sources - 并行采集不同来源以提高效率
- 所有链接必须真实可访问,不要编造 URL
- 中文输出,技术术语保留英文
⚠️ 输出自检清单(强制,每次输出前逐条核对)
输出报告前,必须逐条检查以下项目,全部通过才可发送:
- 标题链接:
# [Project Name](GitHub URL)格式,可点击跳转 - 标题空行:每个粗体标题(
**🎯 ...**)前后各有一个空行 - Telegram 空行:每个列表块末尾与下一个标题之间有盲文空格
⠀行(防止 Telegram 吞空行) - Issue 链接:精选 Issue 每条都有完整
[#号 标题](完整URL)格式 - 竞品链接:每个竞品都附
[名称](GitHub/官网链接) - 社区声量链接:每条引用都有
[来源: 标题](URL)格式 - 无空泛描述:社区声量部分没有"评价很高"、"热度很高"等概括性描述
- 信息溯源:所有外部引用都附原始链接
Dependencies
本 Skill 依赖以下 OpenClaw 工具和 Skills:
| 依赖 | 类型 | 用途 |
|---|---|---|
web_search |
内置工具 | Brave Search 检索 |
web_fetch |
内置工具 | 网页内容抓取 |
browser |
内置工具 | 动态页面渲染(备选) |
search-layer |
Skill | 多源搜索 + 意图感知评分(Brave + Exa + Tavily + Grok),v2.1 支持 --intent / --queries / --freshness |
content-extract |
Skill | 高保真内容提取(反爬站点降级方案) |
How to use github-explorer on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add github-explorer
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches github-explorer from GitHub repository blessonism/github-explorer-skill and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate github-explorer. Access the skill through slash commands (e.g., /github-explorer) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★34 reviews- ★★★★★Harper Sharma· Dec 8, 2024
Useful defaults in github-explorer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Pratham Ware· Dec 4, 2024
Useful defaults in github-explorer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sofia Li· Dec 4, 2024
We added github-explorer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Harper Li· Nov 27, 2024
github-explorer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sakshi Patil· Nov 23, 2024
github-explorer has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aanya Okafor· Nov 23, 2024
Keeps context tight: github-explorer is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Harper Thomas· Oct 18, 2024
Solid pick for teams standardizing on skills: github-explorer is focused, and the summary matches what you get after install.
- ★★★★★Chaitanya Patil· Oct 14, 2024
Solid pick for teams standardizing on skills: github-explorer is focused, and the summary matches what you get after install.
- ★★★★★Zaid Tandon· Oct 14, 2024
github-explorer is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Amelia Srinivasan· Sep 21, 2024
Solid pick for teams standardizing on skills: github-explorer is focused, and the summary matches what you get after install.
showing 1-10 of 34