RRepoGEO

REPOGEO REPORT · LITE

luban-agi/Awesome-Domain-LLM

Default branch main · commit 1b8d55a4 · scanned 6/22/2026, 7:37:48 PM

GitHub: 2,576 stars · 201 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
28 /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
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 luban-agi/Awesome-Domain-LLM, 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
    Strengthen README's opening to clarify its role as a curated resource hub.

    Why:

    CURRENT
    本项目旨在收集和梳理垂直领域的开源模型、数据集及评测基准。
    COPY-PASTE FIX
    本项目旨在收集和梳理垂直领域的**开源模型**、**数据集**及**评测基准**，致力于成为领域大模型研究与应用的一站式资源中心。
  • mediumtopics#2
    Expand repository topics to include more specific resource-related keywords.

    Why:

    CURRENT
    awesome-list, dataset, llm, nlp, paper-list
    COPY-PASTE FIX
    awesome-list, dataset, llm, nlp, paper-list, llm-resources, domain-llm, llm-benchmarks, llm-datasets, vertical-llm
  • mediumhomepage#3
    Add a homepage URL to the repository metadata.

    Why:

    COPY-PASTE FIX
    https://github.com/luban-agi/Awesome-Domain-LLM

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 luban-agi/Awesome-Domain-LLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Hub
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Hub · recommended 2×
  2. BioGPT · recommended 1×
  3. PubMedBERT · recommended 1×
  4. FinBERT · recommended 1×
  5. Legal-BERT · recommended 1×
  • CATEGORY QUERY
    Where can I find open-source large language models optimized for various vertical industry domains?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Hub
    2. BioGPT
    3. PubMedBERT
    4. FinBERT
    5. Legal-BERT
    6. BloombergGPT
    7. ClinicalBERT
    8. LLaMA 2
    9. Mistral
    10. Falcon
    11. EleutherAI
    12. GPT-J
    13. GPT-NeoX
    14. OpenAI
    15. GPT-3.5
    16. GPT-4
    17. arXiv
    18. ACL Anthology
    19. GitHub

    AI recommended 19 alternatives but never named luban-agi/Awesome-Domain-LLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources exist for domain-specific LLM development, including datasets and evaluation benchmarks?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Hub
    2. EleutherAI's LM Evaluation Harness
    3. Papers With Code
    4. OpenAI Evals
    5. BigCode Project
    6. BioASQ
    7. FinQA
    8. LegalBench
    9. Kaggle

    AI recommended 9 alternatives but never named luban-agi/Awesome-Domain-LLM. 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 luban-agi/Awesome-Domain-LLM?
    pass
    AI did not name luban-agi/Awesome-Domain-LLM — 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 luban-agi/Awesome-Domain-LLM in production, what risks or prerequisites should they evaluate first?
    pass
    AI named luban-agi/Awesome-Domain-LLM 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 luban-agi/Awesome-Domain-LLM solve, and who is the primary audience?
    pass
    AI named luban-agi/Awesome-Domain-LLM explicitly

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

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MARKDOWN (README)
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luban-agi/Awesome-Domain-LLM — 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