RRepoGEO

REPOGEO REPORT · LITE

google-research/android_world

Default branch main · commit d9c569f7 · scanned 6/4/2026, 9:08:00 PM

GitHub: 782 stars · 156 forks

AI VISIBILITY SCORE
28 /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
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-research/android_world, 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 sentence to clarify its purpose for AI agents

    Why:

    CURRENT
    AndroidWorld is an environment for building and benchmarking autonomous computer control agents.
    COPY-PASTE FIX
    AndroidWorld is a **research environment and benchmark specifically designed for training and evaluating autonomous AI agents** on live Android emulators.
  • mediumhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://google-research.github.io/android_world/

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-research/android_world
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
UI Automator
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. UI Automator · recommended 2×
  2. appium/appium · recommended 2×
  3. Android Studio Emulator · recommended 1×
  4. Espresso · recommended 1×
  5. Genymotion Desktop · recommended 1×
  • CATEGORY QUERY
    What are good environments for benchmarking autonomous AI agents on Android emulators?
    you: not recommended
    AI recommended (in order):
    1. Android Studio Emulator
    2. Espresso
    3. UI Automator
    4. Appium (appium/appium)
    5. Genymotion Desktop
    6. Google Cloud Device Farm / Firebase Test Lab
    7. Robot Framework (robotframework/robotframework)
    8. Appium Library (serhatbolsu/robotframework-appiumlibrary)
    9. Frida (frida/frida)

    AI recommended 9 alternatives but never named google-research/android_world. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a robust platform to evaluate AI agents on real-world mobile application tasks.
    you: not recommended
    AI recommended (in order):
    1. Appium (appium/appium)
    2. Maestro (mobile-dev-inc/maestro)
    3. Detox (wix/Detox)
    4. UI Automator
    5. XCUITest
    6. SeeTest
    7. BrowserStack App Automate
    8. Sauce Labs Mobile App Testing

    AI recommended 8 alternatives but never named google-research/android_world. 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 google-research/android_world?
    pass
    AI did not name google-research/android_world — 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?

  • If a team adopts google-research/android_world in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google-research/android_world 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-research/android_world solve, and who is the primary audience?
    pass
    AI named google-research/android_world explicitly

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

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google-research/android_world — 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