RRepoGEO

REPOGEO REPORT · LITE

Ucas-HaoranWei/Vary-toy

Default branch main · commit c6e40597 · scanned 6/3/2026, 7:13:00 PM

GitHub: 628 stars · 43 forks

AI VISIBILITY SCORE
30 /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
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 Ucas-HaoranWei/Vary-toy, 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, explicit opening sentence to the README

    Why:

    CURRENT
    The README currently starts with an H3 and links, without an immediate, explicit statement of purpose.
    COPY-PASTE FIX
    Add the following sentence as the very first line of the README (after any badges/title): "Vary-toy is the official code implementation of 'Small Language Model Meets with Reinforced Vision Vocabulary,' a project focused on Vision-Language Models (VLMs) and multi-page document understanding."
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    vision-language-models, vlm, small-language-models, slm, document-understanding, multi-modal, computer-vision, deep-learning, pytorch, large-language-models, llm
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT or Apache-2.0) to the repository root to clearly state the project's licensing terms.

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 Ucas-HaoranWei/Vary-toy
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenCLIP
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenCLIP · recommended 1×
  2. BLIP · recommended 1×
  3. BLIP-2 · recommended 1×
  4. MiniGPT-4 · recommended 1×
  5. LLaVA · recommended 1×
  • CATEGORY QUERY
    How to integrate vision capabilities with small language models for specific tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenCLIP
    2. BLIP
    3. BLIP-2
    4. MiniGPT-4
    5. LLaVA
    6. Hugging Face Transformers Library
    7. PaddlePaddle
    8. ERNIE-ViLG
    9. ERNIE-VIL

    AI recommended 9 alternatives but never named Ucas-HaoranWei/Vary-toy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool for multi-page document understanding using vision-language models.
    you: not recommended
    AI recommended (in order):
    1. Azure Form Recognizer (now Azure AI Document Intelligence)
    2. Google Cloud Document AI
    3. Amazon Textract
    4. OpenAI GPT-4V (Vision)
    5. LayoutLMv3
    6. Donut (Document Understanding Transformer)

    AI recommended 6 alternatives but never named Ucas-HaoranWei/Vary-toy. 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 Ucas-HaoranWei/Vary-toy?
    pass
    AI named Ucas-HaoranWei/Vary-toy explicitly

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

  • If a team adopts Ucas-HaoranWei/Vary-toy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Ucas-HaoranWei/Vary-toy 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 Ucas-HaoranWei/Vary-toy solve, and who is the primary audience?
    pass
    AI named Ucas-HaoranWei/Vary-toy 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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Ucas-HaoranWei/Vary-toy — 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