Google Social Media Finder logo

Google Social Media Finder

OrganizationPopular
browser-act
google-social-media-finder

Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and follower count across X, Instagram, Facebook, LinkedIn, TikTok, YouTube, Pinterest, Reddit, Snapchat, Threads, and more. Use when user wants to find someone's social media accounts, look up social profiles, discover where a person is active online, find brand social media pages, search social accounts by name, track digital footprint, find influencer profiles, check a company's social presence, locate a public figure's profiles, social media lookup, social media finder, find accounts across platforms, social profile search, online presence discovery, who is this person on social media, what social media does X use, find username across platforms.

Overview

Publisherbrowser-act
Repositoryskills
Skill namegoogle-social-media-finder
Stars
5.9K
Forks
295
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by browser-act on GitHub. Read the source before you install it.

Installation

Install the Google Social Media Finder 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.
  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/browser-act/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/solutions/lead-generation/google-social-media-finder .claude/skills/google-social-media-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Social Media Finder 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 Google Social Media Finder 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 Google Social Media Finder 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 — Social Media Finder

Name or brand → all social media profiles found on Google (platform, URL, username, bio, followers)

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Given a person's name, brand name, or username, search Google and return all matching social media profile results from known platforms.

Prerequisites

  • No login required — Google search is publicly accessible

Pre-execution Checks

1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

Capability Components

This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})". $(...) is bash syntax; it is recommended to use the bash tool for execution.

Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read scripts/*.py source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.

DOM: social media profile results (data extraction type)

Navigate to the Google search page for the target name, then extract all social media profile results.

Step 1 — Navigate:

navigate https://www.google.com/search?q={name}+social+media

Replace {name} with the person's or brand's name, using + in place of spaces (e.g., Taylor+Swift, Elon+Musk, Nike).

Step 2 — Wait for page:

wait stable

Step 3 — Extract:

bash
eval "$(python scripts/extract-social-profiles.py)"

Output example:

json
{
  "error": false,
  "count": 5,
  "results": [
    {
      "platform": "Instagram",      // social media platform name
      "username": "taylorswift",    // handle or page name shown alongside platform
      "url": "https://www.instagram.com/taylorswift/",  // direct profile URL
      "title": "Taylor Swift (@taylorswift) • Instagram photos and videos",  // page title
      "snippet": "274M followers · 0 following · 706 posts ...",  // bio/description snippet from search result
      "followers": "超过 2.7亿位关注者"  // follower count as displayed (language depends on browser locale)
    }
  ]
}

On error: {"error": true, "message": "..."} — check that the browser navigated to a Google search page and .tF2Cxc result containers are present.

Pagination

URL Pagination: URL pattern https://www.google.com/search?q={name}+social+media&start={offset}, where offset = (page - 1) * 10 (page 1 → start=0 or omit, page 2 → start=10, page 3 → start=20). Next page link: a#pnnext. Termination: a#pnnext is absent (last page reached) or no social media results returned.

Success Criteria

result count >= 1 and platform and url fields are non-null for every item

Known Limitations

  • Results depend on Google's index — newly created or low-traffic profiles may not appear
  • Follower count text is localized to the browser's display language (e.g., Chinese characters for a Chinese-locale stealth browser)
  • Google may show sub-pages of the same profile as separate results (e.g., both /elonmusk and /elonmusk/with_replies from X); deduplicate by base URL if needed
  • Google SERP layout changes occasionally; if .tF2Cxc stops matching, inspect page HTML for updated container class names

Execution Efficiency

  • Batch orchestration: Write a bash script to loop through the command templates serially within a single session; do not parallelize within one browser (prone to triggering anti-scraping restrictions). Refer to rate information in "Known Limitations" above to add appropriate intervals. To increase throughput, open multiple stealth browser sessions and distribute work across them — each session has an independent fingerprint so rate limits apply per session
  • Test before batch execution: After writing a batch script, you must first test with 1-2 items to verify the script runs correctly; only then run the full batch. Never skip testing and execute in batch directly
  • Reduce redundant pre-operations: When multiple steps depend on the same prerequisite state, complete them in batch under that state to avoid repeatedly establishing the same state
  • Error resumption: Save results item by item during batch processing; on failure, resume from the breakpoint rather than starting over

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/social-media-finder-google-social-media-finder.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)

Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.

After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line: {YYYY-MM-DD}: {what happened} → {conclusion}

Normal execution does not write to the file. Do not record what keywords were used or how many results were returned — those are task outputs, not experience.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Google Social Media Finder AI skill do?

Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and follower count across X, Instagram, Facebook, LinkedIn, TikTok, YouTube, Pinterest, Reddit, Snapchat, Threads, and more. Use when user wants to find someone's social media accounts, look up social profiles, discover where a person is active online, find brand social media pages, search social accounts by name, track digital footprint, find influencer profiles, check a company's social presence, locate a public figure's profiles, socia...

Why use Google Social Media Finder on TypingMind?

Because you install it once and use it with any model. Google Social Media Finder 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 Google Social Media Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browser-act/skills/tree/main/solutions/lead-generation/google-social-media-finder. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Google Social Media Finder?

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 Google Social Media Finder?

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

Is the Google Social Media Finder AI skill free?

Yes. It is published on GitHub by browser-act 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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