RRepoGEO

REPOGEO REPORT · LITE

google-gemini/computer-use-preview

Default branch main · commit ecec0410 · scanned 5/28/2026, 1:08:07 PM

GitHub: 2,945 stars · 377 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 google-gemini/computer-use-preview, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A framework for building AI agents that can interact with a computer's user interface using multimodal reasoning, powered by Gemini.
  • mediumreadme#2
    Reposition the README's opening to clearly state the project's purpose

    Why:

    CURRENT
    # Computer Use Preview

## Quick Start

This section will guide you through setting up and running the Computer Use Preview model, either the Gemini Developer API or Vertex AI. Follow these steps to get started.
    COPY-PASTE FIX
    # Computer Use Preview

This repository provides a framework for building AI agents that can autonomously interact with a computer's user interface. Powered by multimodal Gemini models, it enables agents to perceive screens and perform tasks, bridging the gap between AI and desktop automation.

## Quick Start

This section will guide you through setting up and running the Computer Use Preview model, either the Gemini Developer API or Vertex AI. Follow these steps to get started.

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 google-gemini/computer-use-preview
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AutoGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AutoGPT · recommended 1×
  2. LangChain · recommended 1×
  3. AgentGPT · recommended 1×
  4. Open Interpreter · recommended 1×
  5. BabyAGI · recommended 1×
  • CATEGORY QUERY
    Looking for a framework to build AI agents that interact with my computer.
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. LangChain
    3. AgentGPT
    4. Open Interpreter
    5. BabyAGI
    6. SuperAGI

    AI recommended 6 alternatives but never named google-gemini/computer-use-preview. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to programmatically control a browser and desktop using an AI model?
    you: not recommended
    AI recommended (in order):
    1. Playwright
    2. OpenAI GPT-4
    3. GPT-3.5 Turbo
    4. Selenium
    5. PyAutoGUI
    6. Llama 2
    7. Puppeteer
    8. UiPath
    9. Power Automate Desktop
    10. AutoHotkey
    11. AppleScript

    AI recommended 11 alternatives but never named google-gemini/computer-use-preview. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 google-gemini/computer-use-preview?
    pass
    AI named google-gemini/computer-use-preview explicitly

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

  • If a team adopts google-gemini/computer-use-preview in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google-gemini/computer-use-preview 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 google-gemini/computer-use-preview solve, and who is the primary audience?
    pass
    AI did not name google-gemini/computer-use-preview — likely talking about a different project

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

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google-gemini/computer-use-preview — RepoGEO report