RRepoGEO

REPOGEO REPORT · LITE

kbressem/medAlpaca

Default branch main · commit 63448c57 · scanned 6/3/2026, 1:32:59 AM

GitHub: 559 stars · 73 forks

AI VISIBILITY SCORE
47 /100
Critical
Category recall
1 / 2
Avg rank #7.0 when recommended
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 kbressem/medAlpaca, 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
  • highreadme#1
    Strengthen the README's opening to highlight unique differentiators

    Why:

    CURRENT
    # medAlpaca: Finetuned Large Language Models for Medical Question Answering
    
    ## Project Overview
    MedAlpaca expands upon both Stanford Alpaca and 
    AlpacaLoRA to offer an advanced suite of large language 
    models specifically fine-tuned for medical question-answering and dialogue applications. 
    Our primary objective is to deliver an array of open-source language models, paving the way for 
    seamless development of medical chatbot solutions.
    COPY-PASTE FIX
    # medAlpaca: Finetuned Large Language Models for Medical Question Answering
    
    ## Project Overview
    MedAlpaca is an advanced suite of open-source large language models, building on Stanford Alpaca and AlpacaLoRA, specifically fine-tuned for medical question-answering and dialogue applications. Unlike many general-purpose LLMs, medAlpaca leverages a unique training dataset, including synthetically generated medical Q&A pairs, to deliver highly specialized performance for medical chatbot solutions.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [URL to project website or relevant documentation, e.g., a Hugging Face model card or project page]

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
1 / 2
50% of queries surface kbressem/medAlpaca
Avg rank
#7.0
Lower is better. #1 = top recommendation.
Share of voice
7%
Of all named tools, what % are you?
Top rival
Med-PaLM 2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Med-PaLM 2 · recommended 2×
  2. BioGPT · recommended 2×
  3. LLaMA 2 · recommended 2×
  4. PubMedGPT · recommended 1×
  5. Mistral 7B / Mixtral 8x7B · recommended 1×
  • CATEGORY QUERY
    What open-source large language models are best for medical question answering applications?
    you: not recommended
    AI recommended (in order):
    1. Med-PaLM 2
    2. BioGPT
    3. PubMedGPT
    4. LLaMA 2
    5. Mistral 7B / Mixtral 8x7B
    6. Guanaco

    AI recommended 6 alternatives but never named kbressem/medAlpaca. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for finetuned LLMs to develop a medical chatbot or dialogue system.
    you: #7
    AI recommended (in order):
    1. Med-PaLM 2
    2. GPT-4
    3. BioGPT
    4. ClinicalBERT
    5. Med-BERT
    6. LLaMA 2
    7. MedAlpaca ← you
    8. GatorTron
    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 kbressem/medAlpaca?
    pass
    AI did not name kbressem/medAlpaca — 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 kbressem/medAlpaca in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kbressem/medAlpaca 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 kbressem/medAlpaca solve, and who is the primary audience?
    pass
    AI named kbressem/medAlpaca 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 kbressem/medAlpaca. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/kbressem/medAlpaca.svg)](https://repogeo.com/en/r/kbressem/medAlpaca)
HTML
<a href="https://repogeo.com/en/r/kbressem/medAlpaca"><img src="https://repogeo.com/badge/kbressem/medAlpaca.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

kbressem/medAlpaca — 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