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Gs Search

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cookjohn
gs-search

Search Google Scholar for academic papers by keywords. Returns results with title, authors, journal, year, citation count, and full-text links. Use when the user wants to search Google Scholar.

Overview

Publishercookjohn
Repositorygs-skills
Skill namegs-search
Stars
529
Forks
26
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 cookjohn on GitHub. Read the source before you install it.

Installation

Install the Gs Search 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/cookjohn/gs-skills/tree/master/skills/gs-search
  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/cookjohn/gs-skills.git /tmp/gs-skills
mkdir -p .claude/skills
cp -r /tmp/gs-skills/skills/gs-search .claude/skills/gs-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gs Search 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 Gs Search 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 Gs Search 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.

Google Scholar Basic Search

Search Google Scholar for papers using keyword(s). Returns structured result list via DOM scraping.

Arguments

$ARGUMENTS contains the search keyword(s).

Steps

1. Navigate

Use mcp__chrome-devtools__navigate_page:

  • url: https://scholar.google.com/scholar?q={URL_ENCODED_KEYWORDS}&hl=en&num=10

2. Extract results (evaluate_script)

Wait for results to load, check for CAPTCHA, then scrape the DOM:

javascript
async () => {
  // Wait for results or CAPTCHA
  for (let i = 0; i < 20; i++) {
    if (document.querySelector('#gs_res_ccl') || document.querySelector('#gs_captcha_ccl')) break;
    await new Promise(r => setTimeout(r, 500));
  }

  // CAPTCHA check
  if (document.querySelector('#gs_captcha_ccl') || document.body.innerText.includes('unusual traffic')) {
    return { error: 'captcha', message: 'Google Scholar requires CAPTCHA verification. Please complete it in your browser, then tell me to continue.' };
  }

  const items = document.querySelectorAll('#gs_res_ccl .gs_r.gs_or.gs_scl');
  const results = Array.from(items).map((item, i) => {
    const titleEl = item.querySelector('.gs_rt a');
    const meta = item.querySelector('.gs_a')?.textContent || '';
    // Parse "Author1, Author2 - Journal, Year - publisher"
    const parts = meta.split(' - ');
    const authors = parts[0]?.trim() || '';
    const journalYear = parts[1]?.trim() || '';
    const citedByEl = item.querySelector('.gs_fl a[href*="cites"]');
    const relatedEl = item.querySelector('.gs_fl a[href*="related"]');
    const versionsEl = item.querySelector('.gs_fl a[href*="cluster"]');

    return {
      n: i + 1,
      title: titleEl?.textContent?.trim() || item.querySelector('.gs_rt')?.textContent?.trim() || '',
      href: titleEl?.href || '',
      authors,
      journalYear,
      citedBy: citedByEl?.textContent?.match(/\d+/)?.[0] || '0',
      citedByUrl: citedByEl?.href || '',
      dataCid: item.getAttribute('data-cid') || '',
      fullTextUrl: (item.querySelector('.gs_ggs a') || item.querySelector('.gs_or_ggsm a'))?.href || '',
      snippet: item.querySelector('.gs_rs')?.textContent?.trim()?.substring(0, 200) || '',
      relatedUrl: relatedEl?.href || '',
      versionsUrl: versionsEl?.href || '',
      versions: versionsEl?.textContent?.match(/\d+/)?.[0] || ''
    };
  });

  const totalText = document.querySelector('#gs_ab_md')?.textContent?.trim() || '';
  const currentUrl = window.location.href;
  return { total: totalText, resultCount: results.length, currentUrl, results };
}

3. Report

Present results as a numbered list:

Searched Google Scholar for "$ARGUMENTS": {total}

1. {title}
   Authors: {authors} | {journalYear}
   Cited by: {citedBy} | [Full text]({fullTextUrl})
   Data-CID: {dataCid}

2. ...

Always show the dataCid — it's the unique identifier used for citation export and "cited by" tracking.

If fullTextUrl is available, highlight it (means open-access PDF/HTML).

4. Follow-up

When the user wants to:

  • See more results: use gs-navigate-pages to go to next page
  • See who cited a paper: use gs-cited-by with the data-cid
  • Export to Zotero: use gs-export with the data-cid(s)

CAPTCHA Handling

If the result contains {error: 'captcha'}:

  1. Tell the user: "Google Scholar is requesting CAPTCHA verification. Please complete it in your browser."
  2. Wait for user confirmation
  3. Retry the evaluate_script extraction

Notes

  • This skill uses 2 tool calls: navigate_page + evaluate_script
  • Google Scholar has NO public API — all data extraction is via DOM scraping
  • data-cid is the primary identifier (cluster ID) — used across all GS skills
  • Keep request frequency low to avoid triggering CAPTCHA
  • Default num=10 results per page (max 20)

Frequently asked questions

What does the Gs Search AI skill do?

Search Google Scholar for academic papers by keywords. Returns results with title, authors, journal, year, citation count, and full-text links. Use when the user wants to search Google Scholar.

Why use Gs Search on TypingMind?

Because you install it once and use it with any model. Gs Search 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 Gs Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cookjohn/gs-skills/tree/master/skills/gs-search. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gs Search?

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 Gs Search?

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

Is the Gs Search AI skill free?

Yes. It is published on GitHub by cookjohn 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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