RRepoGEO

REPOGEO REPORT · LITE

nndl/llm-beginner

Default branch master · commit 5aadcadf · scanned 5/30/2026, 4:56:59 AM

GitHub: 6,308 stars · 1,301 forks

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 nndl/llm-beginner, 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
  • highlicense#1
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    (Create a LICENSE file in the repository root with your chosen open-source license, e.g., MIT or Apache-2.0.)
  • highhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    (Add the URL of the associated textbook or project website, e.g., 'https://nndl.github.io/llm-beginner' or 'https://github.com/nndl/llm-beginner' if it's self-contained, to the repository's 'About' section homepage field.)
  • mediumabout#3
    Update the GitHub 'About' description to emphasize hands-on implementation

    Why:

    CURRENT
    LLM、Agent上手教程
    COPY-PASTE FIX
    LLM、Agent上手教程：从零实现Transformer、RAG、Agent等核心组件的动手实践教程。

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 nndl/llm-beginner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepLearning.AI
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepLearning.AI · recommended 3×
  2. LangChain · recommended 2×
  3. LlamaIndex · recommended 2×
  4. AWS · recommended 1×
  5. OpenAI · recommended 1×
  • CATEGORY QUERY
    Seeking a structured tutorial to learn large language model and agent development hands-on.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. DeepLearning.AI
    3. AWS
    4. DeepLearning.AI
    5. OpenAI
    6. LlamaIndex
    7. Hugging Face

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

    Show full AI answer
  • CATEGORY QUERY
    Where can I find practical guides for implementing RAG and agent patterns with LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. DeepLearning.AI
    4. Hugging Face Transformers
    5. § Datasets
    6. sentence-transformers
    7. OpenAI Cookbook
    8. Microsoft Semantic Kernel

    AI recommended 8 alternatives but never named nndl/llm-beginner. 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 nndl/llm-beginner?
    pass
    AI named nndl/llm-beginner explicitly

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

  • If a team adopts nndl/llm-beginner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named nndl/llm-beginner 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 nndl/llm-beginner solve, and who is the primary audience?
    pass
    AI named nndl/llm-beginner explicitly

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

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nndl/llm-beginner — 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