RRepoGEO

REPOGEO REPORT · LITE

Azure-Samples/azure-search-openai-demo-csharp

Default branch main · commit 7d702a68 · scanned 6/6/2026, 12:11:52 PM

GitHub: 834 stars · 689 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Azure-Samples/azure-search-openai-demo-csharp, 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
  • highabout#1
    Refine repository description to emphasize C# reference application

    Why:

    CURRENT
    A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
    COPY-PASTE FIX
    A C# reference application demonstrating the Retrieval-Augmented Generation (RAG) pattern in Azure, using Azure Cognitive Search for data retrieval and Azure OpenAI large language models for ChatGPT-style and Q&A experiences.
  • mediumhomepage#2
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    Add a URL to the repository's homepage field, ideally linking to a live demo or a dedicated documentation site for the sample application.
  • mediumtopics#3
    Add more specific topics for RAG and C# applications

    Why:

    CURRENT
    ai-azd-templates, azd-templates, azure, chatgpt, csharp, dotnet, openai
    COPY-PASTE FIX
    ai-azd-templates, azd-templates, azure, chatgpt, csharp, dotnet, openai, retrieval-augmented-generation, rag, qna-application, conversational-ai-sample, enterprise-data-chat

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 Azure-Samples/azure-search-openai-demo-csharp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 2×
  2. Pinecone · recommended 2×
  3. Weaviate · recommended 2×
  4. Hugging Face Transformers · recommended 2×
  5. Azure OpenAI Service · recommended 1×
  • CATEGORY QUERY
    How to build a C# application for Q&A and conversational AI with private data?
    you: not recommended
    AI recommended (in order):
    1. Azure OpenAI Service
    2. Azure AI Search
    3. Semantic Kernel
    4. Microsoft Bot Framework
    5. Bot Framework Composer
    6. OpenAI API
    7. Faiss
    8. Pinecone
    9. Weaviate
    10. Hugging Face Transformers
    11. ONNX Runtime
    12. LLamaSharp

    AI recommended 12 alternatives but never named Azure-Samples/azure-search-openai-demo-csharp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking example architecture for building intelligent chat experiences from internal business documents.
    you: not recommended
    AI recommended (in order):
    1. Apache NiFi
    2. Apache Kafka
    3. Elasticsearch Ingest Pipelines
    4. Logstash
    5. Elasticsearch
    6. Pinecone
    7. Weaviate
    8. Milvus
    9. Hugging Face Transformers
    10. OpenAI Embeddings API
    11. LangChain
    12. LlamaIndex
    13. OpenAI API
    14. Anthropic Claude API
    15. Hugging Face Inference Endpoints
    16. Llama 2
    17. Mistral
    18. Streamlit
    19. Gradio
    20. React
    21. Vue.js
    22. Angular

    AI recommended 22 alternatives but never named Azure-Samples/azure-search-openai-demo-csharp. 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 Azure-Samples/azure-search-openai-demo-csharp?
    pass
    AI did not name Azure-Samples/azure-search-openai-demo-csharp — 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 Azure-Samples/azure-search-openai-demo-csharp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Azure-Samples/azure-search-openai-demo-csharp 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 Azure-Samples/azure-search-openai-demo-csharp solve, and who is the primary audience?
    pass
    AI did not name Azure-Samples/azure-search-openai-demo-csharp — 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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