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Github Explorer

CommunityPopular
MaxMiksa
github-explorer

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 "help me look at this project", "learn about XXX", "what is this project like", "analyze this repo", or any request to explore/evaluate a GitHub project. Covers architecture, community health, competitive landscape, and cross-platform knowledge sources.

Overview

PublisherMaxMiksa
RepositoryAuto-Company
Skill namegithub-explorer
Stars
3.1K
Forks
493
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by MaxMiksa on GitHub. Read the source before you install it.

Installation

Install the Github Explorer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/MaxMiksa/Auto-Company/tree/main/.claude/skills/github-explorer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MaxMiksa/Auto-Company.git /tmp/Auto-Company
mkdir -p .claude/skills
cp -r /tmp/Auto-Company/.claude/skills/github-explorer .claude/skills/github-explorer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Explorer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Github Explorer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Github Explorer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GitHub Explorer — In-Depth Project Analysis

Philosophy: The README is only the storefront; the real value lies in Issues, Commits, and community discussions.

Workflow

[Project name] → [1. Locate Repo] → [2. Gather Multiple Sources] → [3. Analyze and Assess] → [4. Structured Output]

Phase 1: Locate Repo

  • Use web_search to search site:github.com <project_name> and confirm the full org/repo
  • Use an available search tool to find additional community links and non-GitHub resources with queries such as <project_name> review and <project_name> 评测 使用体验.
  • Use web_fetch to fetch the repo homepage for basic information (README, Stars, Forks, License, last update)

Phase 2: Gather Multiple Sources (In Parallel)

Check the following sources as needed; collect what exists and skip what does not:

SourceURL patternWhat to collectSuggested tool
GitHub Repogithub.com/{org}/{repo}README, About, Contributorsweb_fetch
GitHub Issuesgithub.com/{org}/{repo}/issues?q=sort:commentsTop 3-5 high-quality Issuesbrowser
Chinese-language communitiesWeChat / Zhihu / XiaohongshuIn-depth reviews, usage experiencesAvailable platform tool or browser
Technical blogsMedium / Dev.toTechnical architecture analysesweb_fetch / browser
Discussion forumsV2EX / RedditUser feedback, complaintsAvailable search or platform tool
Search Tools and Queries

This repository does not include the search-layer or content-extract skills or their scripts. web_search, web_fetch, and browser mean the corresponding capabilities in the current environment; use the tool names actually available. If enhancement skills are separately installed, read their own instructions and confirm dependencies and invocation paths first. Otherwise, run the following searches directly without those scripts.

ScenarioExample queriesNotes
Project research (default)<project> review, <project> 评测Cross-check independent sources
Latest developments<project> latest releaseCheck the official release page and dates
Competitor comparison<project> vs <competitor>, <project> alternativesVerify differences and applicable conditions
Quick link lookup<project> official docsConfirm the official domain
Community discussion<project> discussion experience, restricted to community domainsDistinguish user experiences from verified facts

If a source or enhancement tool fails, continue with available sources and state the coverage limitations in the report. Without search capability, analyze only the readable repository and user-provided material; do not claim that community research was completed.


Extraction Fallback and Upgrade Protocol (Extraction Upgrade)

In these situations, switch to an available browser or platform reader, or use an installed content-extraction skill:

  1. Restricted domains: mp.weixin.qq.com, zhihu.com, xiaohongshu.com.
  2. Complex structure: The page contains many formulas (LaTeX), complex tables, or extremely messy Markdown returned by web_fetch.
  3. Missing content: Anti-scraping defenses cause web_fetch to return empty content or a challenge page.

If reading still fails, retain the URL, mark it as "Could not read," and seek independent sources. Do not treat search snippets as full text that was read, or count inaccessible discussions as verified evidence.

Phase 3: Analyze and Assess

Make judgments based on the collected data:

  • Project stage: Early experiment / rapid growth / mature and stable / maintenance mode / stalled, based on commit frequency and content
  • Featured Issue criteria: Many comments, maintainer participation, exposure of architectural problems, or valuable technical discussion
  • Competitor identification: Extract from README "Comparison"/"Alternatives" sections, Issues discussions, and web searches

Phase 4: Structured Output

Follow the template below strictly, translating its headings, labels, and status messages into the selected output language. Every section must contain substantive content or explicitly say "Not found" in that language.

Formatting Rules (Mandatory)
  1. The title must link to the GitHub repository (format: # [Project Name](https://github.com/org/repo), ensuring it is clickable)
  2. Put a blank line both before and after every heading (end of previous section → blank line → heading → blank line → content, for clear visual separation)
  3. Telegram blank-line fix (mandatory): Telegram swallows blank lines after list items (lines starting with -). To fix this, insert a line containing a braille blank ⠀ (U+2800) between the end of the list and the next heading, as follows:
    - Last list item
    
    ⠀
    **Next heading**
    This ensures Telegram preserves the blank line before the heading when rendering.
  4. Make all headings bold (emoji + bold text)
  5. Competitor comparisons must include links (at least one of GitHub / official website / documentation)
  6. Community discussion must be specific: Summarize concrete posts, tweets, or discussions and link to the originals. Do not write generalities such as "highly rated" or "very popular"; state who said what or which specific problem a post discussed
  7. Source traceability: All external information cited should include the original link so readers can trace it to the source
markdown
# [{Project Name}]({GitHub Repo URL})

**🎯 One-Sentence Positioning**

{What it is and what problem it solves}

**⚙️ Core Mechanism**

{Explain the technical principles / architecture in plain language, without copying the README. Include the key technology stack.}

**📊 Project Health**

- **Stars**: {Count}  |  **Forks**: {Count}  |  **License**: {Type}
- **Team / Author**: {Background}
- **Commit trend**: {Recent activity + assessment of project stage}
- **Latest developments**: {Summary of the latest important commits}

**🔥 Featured Issues**

{Top 3-5 high-quality Issues, each with a title, link, and key discussion points. State explicitly if there are no high-quality Issues.}

**✅ Suitable Use Cases**

{When to use it and which specific problems it solves}

**⚠️ Limitations**

{When to avoid it; known problems}

**🆚 Competitor Comparison**

{Compare projects in the same space and their differences. Every competitor must have a GitHub or official website link. Example format:}
- **vs [GraphRAG](https://github.com/microsoft/graphrag)** — Description of differences
- **vs [RAGFlow](https://github.com/infiniflow/ragflow)** — Description of differences

**🌐 Knowledge Graph**

- **DeepWiki**: {Link or "Not indexed"}
- **Zread.ai**: {Link or "Not indexed"}

**🎬 Demo**

{Live demo link or "None"}

**📄 Related Papers**

{arXiv link or "None"}

**📰 Community Discussion**

**X/Twitter**

{Summaries of specific tweets + links. Example format:}
- [@user](link): "What they specifically said..."
- [Discussion thread](link): The specific problem discussed...
{If nothing is found, state "No relevant discussion found"}

**Chinese-Language Communities**

{Specific post titles / content summaries + links. Example format:}
- [Zhihu: Post title](link) — What was discussed
- [V2EX: Post title](link) — What was discussed
{If nothing is found, state "No relevant discussion found"}

**💬 My Assessment**

{Subjective evaluation: whether it is worth the time, what experience level it suits, and how to use it}

Execution Notes

  • Prefer web_search + web_fetch, with browser as a fallback
  • Search enhancement: Use available search sources; use extra skills only after confirming their installation and reading their instructions. One source failing must not block the main workflow; disclose insufficient coverage
  • Extraction fallback: If web_fetch fails or returns incomplete content, switch to an available browser, platform reader, or installed extraction skill. If the content remains unreadable, mark it and seek other sources
  • Collect different sources in parallel for efficiency
  • All links must be real and accessible; do not invent URLs
  • Follow the runtime product Language instruction for the report throughout the current product, including pauses and restarts. A requested language change applies to the next product. If no product language is assigned, follow explicit human language instructions or the user's language. Keep technical terms in English. The English skill source and template do not set the output language
  • Leave language preference changes to the human-operated settings interface; do not edit saved language configuration or the current product's language state

⚠️ Output Self-Check (Mandatory Before Every Response)

Before sending a report, you must check every item below, and send it only when all pass:

  • Title link: Uses # [Project Name](GitHub URL) and is clickable
  • Heading spacing: A blank line before and after every bold heading (**🎯 ...**)
  • Telegram blank lines: A braille blank ⠀ line between the end of each list block and the next heading, preventing Telegram from swallowing blank lines
  • Issue links: Every featured Issue uses the full [#number Title](full URL) format
  • Competitor links: Every competitor has [Name](GitHub / official website URL)
  • Community discussion links: Every citation uses [Source: Title](URL)
  • No vague descriptions: The community section contains no generalities such as "highly rated" or "very popular"
  • Source traceability: All external citations include original links

Dependencies

These names describe required capabilities and optional enhancements; they do not mean Auto-Company has installed or configured these tools:

DependencyTypePurpose
web_searchEnvironment-provided toolSearch queries
web_fetchEnvironment-provided toolWeb content retrieval
browserEnvironment-provided toolDynamic page rendering (fallback)
search-layerOptional skill, not bundledUse for search enhancement only after separate installation and checking its instructions; otherwise use available search tools
content-extractOptional skill, not bundledUse for extraction only after separate installation and checking its instructions; otherwise use a browser or platform tool

Frequently asked questions

What does the Github Explorer AI skill do?

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 "help me look at this project", "learn about XXX", "what is this project like", "analyze this repo", or any request to explore/evaluate a GitHub project. Covers architecture, community health, competitive landscape, and cross-platform knowledge sources.

Why use Github Explorer on TypingMind?

Because you install it once and use it with any model. Github Explorer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Github Explorer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MaxMiksa/Auto-Company/tree/main/.claude/skills/github-explorer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Github Explorer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Github Explorer?

As many as you like. As long as a model supports skills, you can use Github Explorer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Github Explorer AI skill free?

Yes. It is published on GitHub by MaxMiksa under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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