RRepoGEO

REPOGEO REPORT · LITE

alexsosn/iOS_ML

Default branch master · commit 655cfdcc · scanned 5/15/2026, 5:08:20 AM

GitHub: 1,429 stars · 150 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 alexsosn/iOS_ML, 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 emphasize 'curated list'

    Why:

    CURRENT
    # Machine Learning for iOS
    COPY-PASTE FIX
    # Awesome Machine Learning for iOS: A Curated List of Resources
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Choose and add a standard open-source license file, e.g., MIT, Apache-2.0, to the repository root.)
  • mediumabout#3
    Update repository description to emphasize 'curated list'

    Why:

    CURRENT
    List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.
    COPY-PASTE FIX
    A curated list of Machine Learning, AI, and NLP resources and solutions specifically for iOS developers. The most recent version of this article can be found on my blog.

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 alexsosn/iOS_ML
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Core ML
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Core ML · recommended 2×
  2. Create ML · recommended 2×
  3. Vision Framework · recommended 2×
  4. Natural Language Framework · recommended 2×
  5. TensorFlow Lite · recommended 2×
  • CATEGORY QUERY
    How can I integrate machine learning and AI capabilities into my iOS applications?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. Create ML
    3. Vision Framework
    4. Natural Language Framework
    5. TensorFlow Lite
    6. PyTorch Mobile
    7. Firebase ML

    AI recommended 7 alternatives but never named alexsosn/iOS_ML. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for computer vision and NLP in Swift iOS development?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. Vision Framework
    3. Natural Language Framework
    4. Create ML
    5. Turi Create
    6. OpenCV
    7. TensorFlow Lite

    AI recommended 7 alternatives but never named alexsosn/iOS_ML. 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 alexsosn/iOS_ML?
    pass
    AI named alexsosn/iOS_ML explicitly

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

  • If a team adopts alexsosn/iOS_ML in production, what risks or prerequisites should they evaluate first?
    pass
    AI named alexsosn/iOS_ML 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 alexsosn/iOS_ML solve, and who is the primary audience?
    pass
    AI did not name alexsosn/iOS_ML — 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?

Embed your GEO score

Drop this badge into the README of alexsosn/iOS_ML. 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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MARKDOWN (README)
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HTML
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alexsosn/iOS_ML — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite