RRepoGEO

REPOGEO REPORT · LITE

Woolverine94/biniou

Default branch main · commit a276f589 · scanned 5/10/2026, 4:13:41 PM

GitHub: 1,127 stars · 131 forks

AI VISIBILITY SCORE
35 /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
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 Woolverine94/biniou, 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
    Fill the main README H1 with a clear project title

    Why:

    CURRENT
    <h1 align="center">
<p align="center">

</p>
</h1>
    COPY-PASTE FIX
    <h1 align="center">biniou: Self-Hosted Web UI for 30+ Generative AI Models</h1>
  • highhomepage#2
    Add the project wiki as the homepage URL in the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/Woolverine94/biniou/wiki

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 Woolverine94/biniou
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LM Studio
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LM Studio · recommended 2×
  2. Ollama · recommended 1×
  3. Open WebUI · recommended 1×
  4. Chatbot UI · recommended 1×
  5. Jan · recommended 1×
  • CATEGORY QUERY
    What are good self-hosted web UIs for running multiple generative AI models locally?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Open WebUI
    4. Chatbot UI
    5. Jan
    6. Text Generation WebUI (oobabooga/text-generation-webui)
    7. InvokeAI
    8. ComfyUI

    AI recommended 8 alternatives but never named Woolverine94/biniou. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I run generative AI models locally without a powerful GPU and offline?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. LM Studio
    3. Jan (janhq/jan)
    4. llama.cpp (ggerganov/llama.cpp)
    5. Hugging Face `transformers` library (huggingface/transformers)
    6. ONNX Runtime (microsoft/onnxruntime)

    AI recommended 6 alternatives but never named Woolverine94/biniou. 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 Woolverine94/biniou?
    pass
    AI named Woolverine94/biniou explicitly

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

  • If a team adopts Woolverine94/biniou in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Woolverine94/biniou 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 Woolverine94/biniou solve, and who is the primary audience?
    pass
    AI named Woolverine94/biniou explicitly

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

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MARKDOWN (README)
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Woolverine94/biniou — 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