RRepoGEO

REPOGEO REPORT · LITE

liguodongiot/llm-resource

Default branch main · commit 5be4067d · scanned 6/2/2026, 5:52:39 AM

GitHub: 715 stars · 83 forks

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 liguodongiot/llm-resource, 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
    Reposition README H1 and opening sentence to emphasize "curated collection"

    Why:

    CURRENT
    # llm-resource（LLM 百宝箱）

LLM全栈优质资源汇总
    COPY-PASTE FIX
    # llm-resource（LLM 百宝箱）- LLM 全栈优质资源精选集

一个全面、精选的LLM全栈优质资源汇总，涵盖算法、训练、推理、数据工程、LLMOps及应用开发等。
  • mediumtopics#2
    Expand repository topics with descriptive keywords

    Why:

    CURRENT
    llm, llmops
    COPY-PASTE FIX
    llm, llmops, awesome-list, resource-collection, llm-resources, ai-resources, deep-learning-resources, full-stack-llm
  • lowhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/liguodongiot/llm-resource

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 liguodongiot/llm-resource
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LLM University
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LLM University · recommended 1×
  2. Awesome LLM · recommended 1×
  3. LangChain · recommended 1×
  4. Full Stack Deep Learning · recommended 1×
  5. Hugging Face · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of high-quality resources for full-stack LLM development?
    you: not recommended
    AI recommended (in order):
    1. LLM University
    2. Awesome LLM
    3. LangChain
    4. Full Stack Deep Learning
    5. Hugging Face
    6. DeepLearning.AI
    7. OpenAI

    AI recommended 7 alternatives but never named liguodongiot/llm-resource. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for understanding and implementing LLM training, fine-tuning, and MLOps?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. Hugging Face Datasets Library
    3. Hugging Face Accelerate
    4. Hugging Face Hub
    5. Hugging Face Course
    6. PyTorch Lightning
    7. Weights & Biases (W&B)
    8. MLflow
    9. Ray Train
    10. Ray Tune
    11. DeepLearning.AI's "Generative AI with Large Language Models" Specialization
    12. "Designing Machine Learning Systems" by Chip Huyen

    AI recommended 12 alternatives but never named liguodongiot/llm-resource. 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 liguodongiot/llm-resource?
    pass
    AI named liguodongiot/llm-resource explicitly

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

  • If a team adopts liguodongiot/llm-resource in production, what risks or prerequisites should they evaluate first?
    pass
    AI named liguodongiot/llm-resource 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 liguodongiot/llm-resource solve, and who is the primary audience?
    pass
    AI did not name liguodongiot/llm-resource — 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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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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liguodongiot/llm-resource — RepoGEO report