RRepoGEO

REPOGEO REPORT · LITE

HKUDS/OpenPhone

Default branch main · commit aff6dea3 · scanned 6/10/2026, 9:18:12 PM

GitHub: 826 stars · 169 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 HKUDS/OpenPhone, 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
    Add a concise, direct problem/solution statement at the top of the README

    Why:

    COPY-PASTE FIX
    OpenPhone is an open-source framework providing mobile agentic foundation models specifically designed for building autonomous AI assistants that operate directly on smartphones. It enables researchers and developers to create intelligent agents that interact with mobile environments.
  • mediumtopics#2
    Expand and refine repository topics for better AI categorization

    Why:

    CURRENT
    ai-phone, mobile-agents, phone-agent
    COPY-PASTE FIX
    ai-phone, mobile-agents, phone-agent, llm-agents, mobile-llm, on-device-ai, autonomous-agents, mobile-ai-framework
  • mediumreadme#3
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## 💡 Comparison with Alternatives

Unlike general-purpose mobile development frameworks (e.g., Flutter, TensorFlow Lite) or large language models (e.g., GPT-4o, Llama 3), OpenPhone is specifically engineered as a foundation model and framework for building **agentic AI assistants that operate autonomously on mobile phones**. We focus on on-device execution, privacy-preserving features, and deep integration with smartphone functionalities, distinguishing us from broader AI platforms or generic mobile OS projects.

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 HKUDS/OpenPhone
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Flutter
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Flutter · recommended 1×
  2. TensorFlow Lite · recommended 1×
  3. PyTorch Mobile · recommended 1×
  4. TensorFlow · recommended 1×
  5. PyTorch · recommended 1×
  • CATEGORY QUERY
    How to develop an AI assistant that operates autonomously on a mobile phone?
    you: not recommended
    AI recommended (in order):
    1. Flutter
    2. TensorFlow Lite
    3. PyTorch Mobile
    4. TensorFlow
    5. PyTorch
    6. React Native
    7. ONNX Runtime Mobile
    8. ONNX
    9. SwiftUI
    10. UIKit
    11. Core ML
    12. Kotlin
    13. Java
    14. Android Jetpack Compose
    15. XML layouts
    16. ML Kit
    17. Voiceflow
    18. Botpress
    19. OpenAI API
    20. GPT-4

    AI recommended 20 alternatives but never named HKUDS/OpenPhone. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a foundation model or framework for building agentic mobile phone applications.
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4o / GPT-4 Turbo
    2. Google Gemini (Pro/Flash)
    3. Llama 3 (Meta) (meta-llama/llama3)
    4. Anthropic Claude 3 Opus / Sonnet
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)

    AI recommended 6 alternatives but never named HKUDS/OpenPhone. 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 HKUDS/OpenPhone?
    pass
    AI named HKUDS/OpenPhone explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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HKUDS/OpenPhone — 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