Agent skill

GitHub Explorer

by nicepkg in nicepkg/auto-company

Deep-dive analysis of GitHub projects. An agent skill from nicepkg/auto-company.

MITAuto-check passedDevelopment

Install GitHub Explorer

skills CLI
$ npx skills add nicepkg/auto-company --skill github-explorer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install nicepkg/auto-company github-explorer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/nicepkg/auto-company.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/github-explorer .claude/skills/github-explorer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
github-explorer
GitHub stars
192
Used in
1 other repo
Token cost
~1.5k tokens
SKILL.md length
370 words
Files
3
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Deep-dive analysis of GitHub projects. An agent skill from nicepkg/auto-company.

  • Works in 4 steps: 定位 Repo → 多源采集(并行) → 分析研判 → …
  • The user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like 帮我看看这个项目
  • SKILL.md covers Workflow, Execution Notes, ⚠️ 输出自检清单(强制,每次输出前逐条核对) and Dependencies
  • Calls python3; reaches github.com

What it does

GitHub Explorer is an agent skill from nicepkg/auto-company. Deep-dive analysis of GitHub projects. Use when the user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like "帮我看看这个项目", "了解一下 XXX", "这个项目怎么样", "分析一下 repo", or any request to explore/evaluate a GitHub project. Covers architecture, community health, competitive landscape, and cross-platform knowledge sources.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files.

It sits in Development, covering Open source maintenance. It works with GitHub and Python. The repository describes itself as: 🤖 A fully autonomous AI company that runs 24/7. 14 AI agents (Bezos, Munger, DHH...) brainstorm ideas, write code, deploy products & make money — no human in the loop. Powered… The licence is MIT.

When your agent uses it

  • The user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like 帮我看看这个项目
  • Any request to explore/evaluate a GitHub project

Example prompts

  • “帮我看看这个项目”
  • “了解一下 XXX”
  • “这个项目怎么样”
  • “/github-explorer”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 定位 Repo
  2. 多源采集(并行)
  3. 分析研判
  4. 结构化输出

What it can do on your machine

Read from SKILL.md and the folder at commit 1252920. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

GitHub Explorer loads about 1.5k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 370 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from nicepkg/auto-company at commit 1252920, republished under its MIT licence (© nicepkg). 370 words, ~1,541 tokens.

Download SKILL.mdSave it as .claude/skills/github-explorer/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
github-explorer
description
Deep-dive analysis of GitHub projects. Use when the user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like "帮我看看这个项目", "了解一下 XXX", "这个项目怎么样", "分析一下 repo", or any request to explore/evaluate a GitHub project. Covers architecture, community health, competitive landscape, and cross-platform knowledge sources.

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:
    bash
    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)

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 Repogithub.com/{org}/{repo}README、About、Contributorsweb_fetch
GitHub Issuesgithub.com/{org}/{repo}/issues?q=sort:commentsTop 3-5 高质量 Issuebrowser
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:

  1. 域名限制: mp.weixin.qq.com, zhihu.com, xiaohongshu.com。
  2. 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。
  3. 内容缺失: web_fetch 因反爬返回空内容或 Challenge 页面。

调用方式:

bash
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)
Show full SKILL.md (159 more words)Show less
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)
  1. 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)
  2. 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)
  3. 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:
    - 列表最后一项
    
    ⠀
    **下一个标题**
    这确保在 Telegram 渲染时标题前的空行不被吞掉。
  4. 所有标题加粗(emoji + 粗体文字)
  5. 竞品对比必须附链接(GitHub / 官网 / 文档,至少一个)
  6. 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"
  7. 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
markdown
# [{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-layer v2 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-layerSkill多源搜索 + 意图感知评分(Brave + Exa + Tavily),v2 支持 --intent / --queries / --freshness
content-extractSkill高保真内容提取(反爬站点降级方案)

© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in .claude/skills/github-explorer of nicepkg/auto-company.

  • SKILL.md
  • .gitignore
  • LICENSE

Open the folder on GitHubat commit 1252920

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in nicepkg/auto-company, which our catalogue first saw on October 7, 2026.

Compare with similar skills

GitHub Explorer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

GitHub Explorer compared with similar skills
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Merge Dependabot PRsonyx-dot-app/onyx32k1 repos~2.2kAutomated safety check: PassMIT
Mole Release Notes Publishertw93/Mole69k—~1.9kAutomated safety check: PassGPL-3.0
Pre-Release PR Triagejamiepine/voicebox57k—~3.1kAutomated safety check: PassMIT
WinAppSDK Triage Meeting Prepmicrosoft/WindowsAppSDK4.7k—~2.8kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about GitHub Explorer

What does GitHub Explorer do?

Deep-dive analysis of GitHub projects. An agent skill from nicepkg/auto-company. GitHub Explorer is an agent skill from nicepkg/auto-company. Deep-dive analysis of GitHub projects.

When should I use GitHub Explorer?

GitHub Explorer fits situations like: the user mentions a GitHub repo/project name and wants to understand it — triggered by phrases like 帮我看看这个项目; any request to explore/evaluate a GitHub project.

How do I install GitHub Explorer in Claude Code?

Run `npx skills add nicepkg/auto-company --skill github-explorer -a claude-code`. Or copy the skill folder (.claude/skills/github-explorer in nicepkg/auto-company) into .claude/skills/github-explorer in your project. Claude Code loads it when a task matches its description.

How do I install GitHub Explorer in Codex?

Run `npx skills add nicepkg/auto-company --skill github-explorer -a codex`. Or copy the skill folder (.claude/skills/github-explorer in nicepkg/auto-company) into .agents/skills/github-explorer in your project. Codex loads it when a task matches its description.

Can I use GitHub Explorer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nicepkg/auto-company --skill github-explorer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/github-explorer, .gemini/skills/github-explorer, .github/skills/github-explorer and .opencode/skills/github-explorer in your project.

What does GitHub Explorer need to run?

Going by SKILL.md and its folder, GitHub Explorer needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does GitHub Explorer access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is GitHub Explorer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does GitHub Explorer use?

GitHub Explorer is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GitHub Explorer use?

About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to GitHub Explorer?

Skills that share tags, products or a category with GitHub Explorer: Contributor-First PR Merge (HKUDS/OpenHarness, 16k stars), Merge Dependabot PRs (onyx-dot-app/onyx, 32k stars), Mole Release Notes Publisher (tw93/Mole, 69k stars) and Pre-Release PR Triage (jamiepine/voicebox, 57k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GitHub Explorer?

nicepkg (a GitHub organization) maintains it in nicepkg/auto-company, which has 192 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on February 12, 2026.

Source: nicepkg/auto-company on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.