RRepoGEO

REPOGEO REPORT · LITE

microsoft/RecAI

Default branch main · commit 0959ecb0 · scanned 5/22/2026, 9:47:41 AM

GitHub: 1,130 stars · 119 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /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
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 microsoft/RecAI, 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
    Add a sentence to the README clarifying the project's specific niche

    Why:

    COPY-PASTE FIX
    Add this sentence to the second paragraph of the README: "Unlike general-purpose LLMs or foundational models, RecAI specifically focuses on the unique challenges and opportunities of integrating LLMs into recommender systems (LLM4Rec), providing practical techniques and methodologies."
  • hightopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    llm, recommender
    COPY-PASTE FIX
    llm, recommender, llm4rec, recsys, ai-agents, personalized-recommendations, deep-learning-recommendations, fine-tuning, model-explainability
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/microsoft/RecAI

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/RecAI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Vertex AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Vertex AI · recommended 2×
  2. OpenAI GPT · recommended 1×
  3. Hugging Face Transformers · recommended 1×
  4. Llama 2 · recommended 1×
  5. Mistral · recommended 1×
  • CATEGORY QUERY
    How can I leverage large language models to build more interactive recommender systems?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT
    2. Hugging Face Transformers
    3. Llama 2
    4. Mistral
    5. T5
    6. LangChain
    7. LlamaIndex
    8. Cohere
    9. Google Cloud Vertex AI
    10. Amazon SageMaker

    AI recommended 10 alternatives but never named microsoft/RecAI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective strategies for integrating LLMs into existing recommendation engines?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Hugging Face Transformers (huggingface/transformers)
    3. Cohere Embed
    4. Google Cloud Vertex AI
    5. Anthropic Claude
    6. Google Cloud Dialogflow
    7. Amazon Lex
    8. TensorFlow Recommenders (tensorflow/recommenders)
    9. PyTorch-Lightning (Lightning-AI/pytorch-lightning)
    10. Scikit-learn (scikit-learn/scikit-learn)

    AI recommended 10 alternatives but never named microsoft/RecAI. 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/RecAI?
    pass
    AI named microsoft/RecAI explicitly

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

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

    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 microsoft/RecAI. 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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microsoft/RecAI — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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