RRepoGEO

REPOGEO REPORT · LITE

JHubi1/ollama-app

Default branch main · commit 3759d320 · scanned 5/13/2026, 9:51:53 PM

GitHub: 1,750 stars · 212 forks

AI VISIBILITY SCORE
28 /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
2 / 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 JHubi1/ollama-app, 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 README H1 to specify 'cross-platform desktop client'

    Why:

    CURRENT
    A modern and easy-to-use client for Ollama.
    COPY-PASTE FIX
    Ollama App: A modern, cross-platform desktop client for Ollama.
  • mediumhomepage#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/JHubi1/ollama-app#readme
  • mediumtopics#3
    Refine topics to include 'desktop-app' and 'cross-platform'

    Why:

    CURRENT
    ai, android, app, linux, llama, localai, ollama, ollama-client, windows
    COPY-PASTE FIX
    ai, android, app, linux, llama, localai, ollama, ollama-client, windows, desktop-app, cross-platform

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 JHubi1/ollama-app
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 2×
  3. GPT4All · recommended 2×
  4. Jan AI · recommended 1×
  5. KoboldCpp · recommended 1×
  • CATEGORY QUERY
    How to easily interact with local large language models on my desktop?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Jan AI
    4. GPT4All
    5. KoboldCpp
    6. Text Generation WebUI (oobabooga/text-generation-webui)

    AI recommended 6 alternatives but never named JHubi1/ollama-app. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good cross-platform clients for local large language model inference?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. Jan
    4. LocalAI
    5. GPT4All

    AI recommended 5 alternatives but never named JHubi1/ollama-app. 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 JHubi1/ollama-app?
    pass
    AI named JHubi1/ollama-app explicitly

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

  • If a team adopts JHubi1/ollama-app in production, what risks or prerequisites should they evaluate first?
    pass
    AI named JHubi1/ollama-app 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 JHubi1/ollama-app solve, and who is the primary audience?
    pass
    AI did not name JHubi1/ollama-app — likely talking about a different project

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

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  • Brand-free category queries5 vs 2 in Lite
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