RRepoGEO

REPOGEO REPORT · LITE

microsoft/ai-dev-gallery

Default branch main · commit 89031ceb · scanned 5/12/2026, 3:57:02 AM

GitHub: 1,448 stars · 215 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 microsoft/ai-dev-gallery, 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 opening to emphasize "gallery of applications"

    Why:

    CURRENT
    Designed for Windows developers, the AI Dev Gallery helps integrate AI capabilities into apps and projects. It includes: Explore over 25 interactive samples powered by local AI modelsEasily browse, download, and run models from Hugging Face and GitHubView the C# source code and export standalone Visual Studio projects with a single click
    COPY-PASTE FIX
    The AI Dev Gallery is a collection of interactive, runnable sample applications designed for Windows developers to learn how to add AI with local models and APIs to Windows apps. It provides over 25 complete C# projects demonstrating AI capabilities, allowing you to browse, download, and run models from Hugging Face and GitHub, view source code, and export standalone Visual Studio projects.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    http://aka.ms/ai-dev-gallery-store
  • lowtopics#3
    Add more descriptive topics to reinforce "samples" and "applications"

    Why:

    CURRENT
    ai, csharp, developer-tools, directml, dotnet, genai, mistral, npu, onnx, onnxruntime, onnxruntime-genai, phi3, qnn, stable-diffusion, visual-studio, whisper, winappsdk, windows, winui3, wpf
    COPY-PASTE FIX
    ai, csharp, developer-tools, directml, dotnet, genai, mistral, npu, onnx, onnxruntime, onnxruntime-genai, phi3, qnn, stable-diffusion, visual-studio, whisper, winappsdk, windows, winui3, wpf, samples, applications, desktop-apps, ai-apps

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 microsoft/ai-dev-gallery
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
dotnet/machinelearning
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. dotnet/machinelearning · recommended 2×
  2. microsoft/onnxruntime · recommended 2×
  3. dotnet/TorchSharp · recommended 1×
  4. SciSharp/TensorFlow.NET · recommended 1×
  5. emgucv/emgucv · recommended 1×
  • CATEGORY QUERY
    How can I integrate local AI models into my C# Windows desktop applications?
    you: not recommended
    AI recommended (in order):
    1. ML.NET (dotnet/machinelearning)
    2. ONNX Runtime (microsoft/onnxruntime)
    3. TorchSharp (dotnet/TorchSharp)
    4. TensorFlow.NET (SciSharp/TensorFlow.NET)
    5. OpenCV (with Emgu CV) (emgucv/emgucv)
    6. llama.cpp (ggerganov/llama.cpp)
    7. Intel OpenVINO Toolkit (openvinotoolkit/openvino)

    AI recommended 7 alternatives but never named microsoft/ai-dev-gallery. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find C# examples for adding generative AI features to WinUI apps?
    you: not recommended
    AI recommended (in order):
    1. Microsoft.SemanticKernel (microsoft/semantic-kernel)
    2. Azure OpenAI Service SDK for .NET (Azure/azure-sdk-for-net)
    3. OpenAI .NET Library (OkGoDoIt/OpenAI-API-dotnet)
    4. Hugging Face Transformers (huggingface/transformers)
    5. ONNX Runtime (microsoft/onnxruntime)
    6. Hugging Face Inference API
    7. ML.NET (dotnet/machinelearning)

    AI recommended 7 alternatives but never named microsoft/ai-dev-gallery. 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 microsoft/ai-dev-gallery?
    pass
    AI did not name microsoft/ai-dev-gallery — 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?

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

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

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