RRepoGEO

REPOGEO REPORT · LITE

jegly/Box

Default branch main · commit 705b1ef8 · scanned 6/4/2026, 5:22:07 PM

GitHub: 535 stars · 29 forks

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 jegly/Box, 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 clear, concise opening statement to the README

    Why:

    COPY-PASTE FIX
    Add the following sentence as the very first line of the README (after any badges/images): 'Box is a private on-device AI suite for Android, forked from Google AI Edge Gallery, featuring llama.cpp, whisper.cpp, stable-diffusion.cpp, GGUF import, voice chat, vision AI, on-device image generation, biometric lock, encrypted history, and CPU/NPU/GPU acceleration.'
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a line to the README, for example: 'This project is licensed under the terms found in the LICENSE file, which includes [mention specific licenses if known, e.g., Apache 2.0 and MIT].'
  • lowreadme#3
    Add a 'What is Box?' section to the README

    Why:

    COPY-PASTE FIX
    Add a new H2 section, `## What is Box?`, near the top of the README, immediately following the initial descriptive sentence. Populate it with a paragraph like: 'Box is designed to bring powerful, private AI capabilities directly to your Android device. It integrates leading open-source models like llama.cpp, whisper.cpp, and stable-diffusion.cpp, allowing for local LLM inference, voice chat, vision AI, and image generation without relying on cloud services. With features like GGUF import, biometric lock, and encrypted history, Box prioritizes user privacy and control.'

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 jegly/Box
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mlc-ai/mlc-llm
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. mlc-ai/mlc-llm · recommended 2×
  2. Termux · recommended 1×
  3. ggerganov/llama.cpp · recommended 1×
  4. Local LLM · recommended 1×
  5. KoboldAI Lite · recommended 1×
  • CATEGORY QUERY
    What are the best privacy-focused AI tools for running large language models locally on Android?
    you: not recommended
    AI recommended (in order):
    1. Termux
    2. llama.cpp (ggerganov/llama.cpp)
    3. MLC LLM (mlc-ai/mlc-llm)
    4. MLC Chat (mlc-ai/mlc-llm)
    5. Local LLM
    6. KoboldAI Lite
    7. PrivateGPT (imartinez/privateGPT)

    AI recommended 7 alternatives but never named jegly/Box. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate local LLMs, vision, and image generation into an Android app?
    you: not recommended
    AI recommended (in order):
    1. MediaPipe
    2. TensorFlow Lite
    3. ONNX Runtime Mobile
    4. Hugging Face Transformers
    5. Optimum
    6. ML Kit
    7. Pytorch Mobile
    8. Stable Diffusion
    9. KerasCV
    10. Diffusers

    AI recommended 10 alternatives but never named jegly/Box. 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 jegly/Box?
    pass
    AI named jegly/Box explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of jegly/Box. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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jegly/Box — 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