RRepoGEO

REPOGEO REPORT · LITE

FudanDISC/DISC-MedLLM

Default branch main · commit 7e84ece9 · scanned 6/9/2026, 8:37:27 PM

GitHub: 565 stars · 53 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 FudanDISC/DISC-MedLLM, 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
  • hightopics#1
    Add specific topics for medical LLM categorization

    Why:

    COPY-PASTE FIX
    medical-llm, healthcare-ai, large-language-model, conversational-ai, medical-chatbot, chinese-llm, sft-dataset, fudan-disc
  • highreadme#2
    Add a concise English summary at the top of the README

    Why:

    COPY-PASTE FIX
    DISC-MedLLM is an open-source medical large language model (LLM) designed for conversational healthcare AI, providing accurate and truthful responses for disease inquiry and treatment consultation.
  • mediumhomepage#3
    Add the Hugging Face demo link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://huggingface.co/Flmc/DISC-MedLLM

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 FudanDISC/DISC-MedLLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 1×
  2. Mistral 7B Instruct · recommended 1×
  3. Mixtral 8x7B Instruct · recommended 1×
  4. Gemma · recommended 1×
  5. Falcon · recommended 1×
  • CATEGORY QUERY
    What open-source large language models are available for building conversational healthcare AI?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mistral 7B Instruct
    3. Mixtral 8x7B Instruct
    4. Gemma
    5. Falcon
    6. Med-PaLM 2
    7. BioGPT

    AI recommended 7 alternatives but never named FudanDISC/DISC-MedLLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an LLM that provides accurate and reliable medical advice in a chat interface.
    you: not recommended
    AI recommended (in order):
    1. Mayo Clinic
    2. WebMD
    3. National Institutes of Health (NIH)
    4. MedlinePlus
    5. Cleveland Clinic

    AI recommended 5 alternatives but never named FudanDISC/DISC-MedLLM. 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 FudanDISC/DISC-MedLLM?
    pass
    AI named FudanDISC/DISC-MedLLM explicitly

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

  • If a team adopts FudanDISC/DISC-MedLLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named FudanDISC/DISC-MedLLM 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 FudanDISC/DISC-MedLLM solve, and who is the primary audience?
    pass
    AI named FudanDISC/DISC-MedLLM 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 FudanDISC/DISC-MedLLM. 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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FudanDISC/DISC-MedLLM — 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