RRepoGEO

REPOGEO REPORT · LITE

chaoyi-wu/PMC-LLaMA

Default branch main · commit 54fc0d4d · scanned 6/4/2026, 10:12:29 AM

GitHub: 676 stars · 62 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 chaoyi-wu/PMC-LLaMA, 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 relevant topics for medical LLMs

    Why:

    COPY-PASTE FIX
    ["medical-llm", "large-language-model", "biomedical-nlp", "llama", "instruction-tuning", "healthcare-ai", "pubmed"]
  • highlicense#2
    Add a LICENSE file and declare the license in README

    Why:

    COPY-PASTE FIX
    (Create a LICENSE file in the repository root, e.g., with the Apache-2.0 license text. Add a line to the README: "This project is licensed under the Apache-2.0 License. Please refer to the LICENSE file for details, and note that usage of LLaMA models may be subject to additional terms.")
  • mediumreadme#3
    Strengthen README's opening statement for core differentiator

    Why:

    CURRENT
    The official codes for "PMC-LLaMA: Towards Building Open-source Language Models for Medicine".
    COPY-PASTE FIX
    PMC-LLaMA is an open-source large language model specifically designed and instruction-tuned for the medical domain, built upon LLaMA and extensively trained on PubMed Central articles.

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 chaoyi-wu/PMC-LLaMA
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
BioGPT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. BioGPT · recommended 2×
  2. PubMedBERT · recommended 2×
  3. ClinicalBERT · recommended 2×
  4. GatorTron · recommended 2×
  5. Med-PaLM 2 · recommended 2×
  • CATEGORY QUERY
    What open-source language models are best for medical domain applications?
    you: not recommended
    AI recommended (in order):
    1. BioGPT
    2. PubMedBERT
    3. BioMed-RoBERTa
    4. ClinicalBERT
    5. GatorTron
    6. Med-PaLM 2
    7. Llama 2
    8. Mixtral

    AI recommended 8 alternatives but never named chaoyi-wu/PMC-LLaMA. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a large language model specifically trained on medical data for instruction following.
    you: not recommended
    AI recommended (in order):
    1. Med-PaLM 2
    2. BioGPT
    3. GatorTron
    4. ClinicalBERT
    5. PubMedBERT

    AI recommended 5 alternatives but never named chaoyi-wu/PMC-LLaMA. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 chaoyi-wu/PMC-LLaMA?
    pass
    AI did not name chaoyi-wu/PMC-LLaMA — 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 chaoyi-wu/PMC-LLaMA in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chaoyi-wu/PMC-LLaMA 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 chaoyi-wu/PMC-LLaMA solve, and who is the primary audience?
    pass
    AI did not name chaoyi-wu/PMC-LLaMA — 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?

Embed your GEO score

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chaoyi-wu/PMC-LLaMA — 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