RRepoGEO

REPOGEO REPORT · LITE

wildminder/AI-windows-whl

Default branch main · commit 1295fa84 · scanned 5/29/2026, 1:03:05 PM

GitHub: 662 stars · 43 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 wildminder/AI-windows-whl, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    ai, comfyui, python
    COPY-PASTE FIX
    python, windows, ai, deep-learning, machine-learning, pre-compiled, wheels, installation, gpu, cuda
  • mediumreadme#3
    Strengthen the 'About The Project' section with problem-solution framing

    Why:

    CURRENT
    (content of 'About The Project' section, not provided)
    COPY-PASTE FIX
    Ensure the 'About The Project' section clearly states: "This project addresses the significant challenge of installing complex, GPU-accelerated AI/ML Python libraries on Windows. By providing a comprehensive collection of pre-compiled wheel files, wildminder/AI-windows-whl eliminates compilation errors and dependency headaches, enabling Windows users to quickly leverage cutting-edge AI tools like Flash Attention and xFormers without extensive setup."

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 wildminder/AI-windows-whl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Miniconda
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Miniconda · recommended 2×
  2. pytorch/pytorch · recommended 2×
  3. tensorflow/tensorflow · recommended 2×
  4. Anaconda Distribution · recommended 1×
  5. Intel Distribution for Python · recommended 1×
  • CATEGORY QUERY
    Struggling to install complex Python AI libraries on Windows; need pre-compiled binaries.
    you: not recommended
    AI recommended (in order):
    1. Anaconda Distribution
    2. Miniconda
    3. Intel Distribution for Python
    4. PyTorch (pytorch/pytorch)
    5. TensorFlow (tensorflow/tensorflow)
    6. Christoph Gohlke's Unofficial Windows Binaries for Python Extension Packages

    AI recommended 6 alternatives but never named wildminder/AI-windows-whl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find pre-built Python wheels for GPU-accelerated deep learning on Windows?
    you: not recommended
    AI recommended (in order):
    1. PyTorch (pytorch/pytorch)
    2. TensorFlow (tensorflow/tensorflow)
    3. NVIDIA NGC
    4. Anaconda
    5. Miniconda
    6. Microsoft's Windows Subsystem for Linux (WSL 2)
    7. NVIDIA CUDA on WSL
    8. Gohlke's Unofficial Windows Binaries for Python

    AI recommended 8 alternatives but never named wildminder/AI-windows-whl. 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 wildminder/AI-windows-whl?
    pass
    AI named wildminder/AI-windows-whl explicitly

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

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

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