RRepoGEO

REPOGEO REPORT · LITE

OSU-NLP-Group/Mind2Web

Default branch main · commit 33bd95ca · scanned 5/29/2026, 2:23:30 PM

GitHub: 998 stars · 124 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface OSU-NLP-Group/Mind2Web, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening to clearly state its purpose as an LLM web agent benchmark

    Why:

    CURRENT
    # Mind2Web: Towards a Generalist Agent for the Web

Dataset, code, and models for the paper "Mind2Web: Towards a Generalist Agent for the Web".
    COPY-PASTE FIX
    # Mind2Web: Towards a Generalist Agent for the Web

Mind2Web is the first LLM-based web agent benchmark and dataset, designed for developing and evaluating generalist agents that can navigate and complete complex tasks on any website. This repository provides the dataset, code, and models from our NeurIPS'23 Spotlight paper.
  • mediumreadme#2
    Add a 'Why Mind2Web?' or 'Comparison' section to differentiate from web automation tools

    Why:

    COPY-PASTE FIX
    ## Why Mind2Web? (Differentiating from Web Automation Tools)

Unlike traditional web automation frameworks (e.g., Playwright, Selenium, Puppeteer) that provide APIs for programmatic web interaction, Mind2Web is a *dataset and benchmark* specifically designed for training and evaluating *large language model (LLM)-based web agents*. Our focus is on enabling agents to understand natural language instructions and perform complex, open-ended tasks across diverse, real-world websites, rather than just scripting predefined actions. Mind2Web provides the structured data and evaluation framework necessary to advance research in generalist AI agents for the web.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface OSU-NLP-Group/Mind2Web
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
microsoft/playwright
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. microsoft/playwright · recommended 1×
  2. SeleniumHQ/selenium · recommended 1×
  3. puppeteer/puppeteer · recommended 1×
  4. Farama-Foundation/Gymnasium · recommended 1×
  5. pytorch/pytorch · recommended 1×
  • CATEGORY QUERY
    Looking for tools to train a large language model to navigate web interfaces.
    you: not recommended
    AI recommended (in order):
    1. Playwright (microsoft/playwright)
    2. Selenium WebDriver (SeleniumHQ/selenium)
    3. Puppeteer (puppeteer/puppeteer)
    4. Gymnasium (Farama-Foundation/Gymnasium)
    5. PyTorch (pytorch/pytorch)
    6. TensorFlow (tensorflow/tensorflow)
    7. Hugging Face Transformers (huggingface/transformers)

    AI recommended 7 alternatives but never named OSU-NLP-Group/Mind2Web. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks for creating general-purpose AI agents for web tasks?
    you: not recommended
    AI recommended (in order):
    1. Playwright
    2. Selenium WebDriver
    3. Puppeteer
    4. Beautiful Soup
    5. Requests
    6. HTTPX
    7. Scrapy

    AI recommended 7 alternatives but never named OSU-NLP-Group/Mind2Web. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of OSU-NLP-Group/Mind2Web?
    pass
    AI named OSU-NLP-Group/Mind2Web explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts OSU-NLP-Group/Mind2Web in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OSU-NLP-Group/Mind2Web explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo OSU-NLP-Group/Mind2Web solve, and who is the primary audience?
    pass
    AI named OSU-NLP-Group/Mind2Web explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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OSU-NLP-Group/Mind2Web — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite