RRepoGEO

REPOGEO REPORT · LITE

droidrun/mobilerun

Default branch main · commit bbb4048a · scanned 5/23/2026, 10:22:03 PM

GitHub: 8,395 stars · 875 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 droidrun/mobilerun, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's core value proposition as an LLM agent framework

    Why:

    CURRENT
    <p align="center">
      <strong>Mobilerun is an open-source framework for controlling Android and iOS devices with LLM agents.</strong><br>
      It gives agents mobile-native tools to inspect UI state, understand screenshots, tap, swipe, type, plan multi-step workflows, and return results through a CLI or Python API.
    </p>
    COPY-PASTE FIX
    # Mobilerun: An LLM Agent Framework for Android and iOS Automation
    
    Mobilerun is an open-source framework designed to empower Large Language Model (LLM) agents to control Android and iOS devices with natural language commands. It provides agents with mobile-native tools to inspect UI state, understand screenshots, tap, swipe, type, plan multi-step workflows, and return results through a CLI or Python API.
  • mediumcomparison#2
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives
    
    Unlike traditional mobile automation tools such as Appium, UI Automator, or XCUITest, Mobilerun is specifically built as an **LLM agent framework**. While these tools provide programmatic control, Mobilerun focuses on enabling AI agents to understand and interact with mobile devices using natural language and high-level reasoning. Compared to general-purpose LLMs like GPT-4o or GPT-4V, Mobilerun provides specialized, mobile-native tools and a structured environment for agents to execute complex, multi-step workflows directly on Android and iOS devices, bridging the gap between AI intelligence and mobile interaction.
  • lowabout#3
    Expand the 'About' description with more keywords

    Why:

    CURRENT
    Automate your mobile devices with natural language commands - an LLM agnostic mobile Agent 🤖
    COPY-PASTE FIX
    Automate Android and iOS mobile devices with natural language commands using an LLM-agnostic agent framework. Empower your AI agents to interact with mobile apps, inspect UI, and execute complex workflows for testing, research, and more. 🤖

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 droidrun/mobilerun
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Appium
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Appium · recommended 2×
  2. UI Automator · recommended 2×
  3. OpenAI GPT-4o · recommended 1×
  4. GPT-4V · recommended 1×
  5. XCUITest · recommended 1×
  • CATEGORY QUERY
    How can I automate mobile app interactions using a large language model agent?
    you: not recommended
    AI recommended (in order):
    1. Appium
    2. OpenAI GPT-4o
    3. GPT-4V
    4. UI Automator
    5. XCUITest
    6. Adb
    7. Google Gemini
    8. Microsoft Playwright
    9. YOLO
    10. DETR
    11. GPT-3.5
    12. Llama 2

    AI recommended 12 alternatives but never named droidrun/mobilerun. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a framework to control Android devices with natural language commands for testing.
    you: not recommended
    AI recommended (in order):
    1. Appium
    2. UI Automator
    3. Robot Framework
    4. Espresso
    5. TestProject.io

    AI recommended 5 alternatives but never named droidrun/mobilerun. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 droidrun/mobilerun?
    pass
    AI named droidrun/mobilerun explicitly

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

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

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

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droidrun/mobilerun — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite