RRepoGEO

REPOGEO REPORT · LITE

gzxiong/MedRAG

Default branch main · commit 7599a728 · scanned 6/4/2026, 9:12:55 PM

GitHub: 560 stars · 81 forks

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 gzxiong/MedRAG, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Update the repository description for clarity

    Why:

    CURRENT
    Code for the MedRAG toolkit
    COPY-PASTE FIX
    A systematic toolkit for Retrieval-Augmented Generation (RAG) on medical question answering (QA).
  • mediumreadme#2
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    Add a section to your README, for example: '## License 
 This project is licensed under [describe the specific license terms, e.g., 'a custom license combining MIT and Apache-2.0 terms']. Please refer to the [LICENSE](LICENSE) file for full details on the applicable terms and conditions.'

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 gzxiong/MedRAG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Pinecone · recommended 2×
  3. Weaviate · recommended 2×
  4. Chroma · recommended 2×
  5. Hugging Face Transformers · recommended 2×
  • CATEGORY QUERY
    What are the best toolkits for building retrieval-augmented generation systems in healthcare?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Weaviate
    4. Chroma
    5. LlamaIndex
    6. Haystack
    7. Hugging Face Transformers
    8. FAISS
    9. Elasticsearch
    10. Gradio
    11. Streamlit
    12. OpenAI API

    AI recommended 12 alternatives but never named gzxiong/MedRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement and evaluate RAG models for medical information retrieval?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LangSmith
    3. Hugging Face Transformers
    4. Hugging Face Datasets
    5. Pinecone
    6. Weaviate
    7. Chroma
    8. Ragas
    9. Elasticsearch
    10. OpenSearch
    11. MRKL

    AI recommended 11 alternatives but never named gzxiong/MedRAG. 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 gzxiong/MedRAG?
    pass
    AI named gzxiong/MedRAG explicitly

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

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

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

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gzxiong/MedRAG — 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