RRepoGEO

REPOGEO REPORT · LITE

stsievert/swix

Default branch master · commit b3dbf29a · scanned 6/3/2026, 8:21:44 PM

GitHub: 586 stars · 51 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 stsievert/swix, 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 the README's opening to highlight Swix's value first

    Why:

    CURRENT
    ## Swift Matrix and Machine Learning Library

*Note: [tensorflow/swift][t4sw] and [apple/swift-numerics/issues/6][asn6] have or will have more complete support for NumPy-like ndarrays and autodiff. Fast AI has a good overview: https://www.fast.ai/2019/01/10/swift-numerics/*

*An alternate and much mature library is https://github.com/AlexanderTar/LASwift*

[t4sw]:https://github.com/tensorflow/swift
[asn6]:https://github.com/apple/swift-numerics/issues/6

Apple's Swift is a high level language that's *asking* for some numerical library to perform computation *fast* or at the very least *easily*. This is a bare-bones wrapper for that library.
    COPY-PASTE FIX
    ## Swift Matrix and Machine Learning Library

Swix is a bare-bones wrapper for Apple's Accelerate and OpenCV frameworks, providing a NumPy-like API for high-performance numerical computations in Swift. It aims to simplify the porting of complex signal processing algorithms and Python/MATLAB-based numerical models to mobile apps, making Swift a powerful language for data science and machine learning on iOS.

*Note: For more complete support for NumPy-like ndarrays and autodiff, consider [tensorflow/swift][t4sw] or [apple/swift-numerics/issues/6][asn6]. An alternate and much mature library is https://github.com/AlexanderTar/LASwift.*

[t4sw]:https://github.com/tensorflow/swift
[asn6]:https://github.com/apple/swift-numerics/issues/6
  • mediumtopics#2
    Expand repository topics to include specific use cases

    Why:

    CURRENT
    linear-algebra, math, swift
    COPY-PASTE FIX
    linear-algebra, math, swift, numpy-like, machine-learning, data-science, ios-development, numerical-computing
  • mediumreadme#3
    Add a dedicated 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with Alternatives

Swix differentiates itself by offering a direct, NumPy-like API for Swift, specifically leveraging Apple's Accelerate and OpenCV for performance. While libraries like `swift-numerics` and `tensorflow/swift` offer broader numerical capabilities or deep learning frameworks, Swix focuses on providing a familiar interface for developers transitioning from Python/MATLAB, making it particularly suitable for integrating existing numerical algorithms into iOS applications with ease. Unlike general-purpose libraries, Swix prioritizes a user experience that mirrors common scientific computing environments.

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 stsievert/swix
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Surge
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Surge · recommended 2×
  2. Accelerate Framework (vecLib) · recommended 1×
  3. Swift for TensorFlow (S4TF) · recommended 1×
  4. LAIK (Linear Algebra in Swift) · recommended 1×
  5. NDArray · recommended 1×
  • CATEGORY QUERY
    What are the best Swift libraries for performing fast matrix operations and linear algebra?
    you: not recommended
    AI recommended (in order):
    1. Accelerate Framework (vecLib)
    2. Surge
    3. Swift for TensorFlow (S4TF)
    4. LAIK (Linear Algebra in Swift)
    5. NDArray

    AI recommended 5 alternatives but never named stsievert/swix. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I efficiently implement numerical algorithms and machine learning models in Swift for iOS?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. vDSP
    3. BNNS
    4. Swift for TensorFlow
    5. Surge
    6. Swift Numerics
    7. Metal Performance Shaders

    AI recommended 7 alternatives but never named stsievert/swix. 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 stsievert/swix?
    pass
    AI named stsievert/swix explicitly

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

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite