RRepoGEO

REPOGEO REPORT · LITE

echonoshy/cgft-llm

Default branch master · commit d6531f8c · scanned 5/15/2026, 1:28:57 PM

GitHub: 2,400 stars · 323 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 echonoshy/cgft-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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Update the repository description for clarity

    Why:

    CURRENT
    Practice to LLM.
    COPY-PASTE FIX
    Hands-on series for building and deploying large language models, including AI agent systems and core LLM technologies.
  • mediumhomepage#2
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/echonoshy/cgft-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 echonoshy/cgft-llm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Hugging Face Transformers · recommended 1×
  4. Accelerate · recommended 1×
  5. Hugging Face Hub · recommended 1×
  • CATEGORY QUERY
    How can I get hands-on experience building and deploying large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Accelerate
    3. Hugging Face Hub
    4. PyTorch Lightning
    5. OpenAI API
    6. Azure OpenAI Service
    7. LangChain
    8. LlamaIndex
    9. Google Cloud Vertex AI
    10. AWS SageMaker

    AI recommended 10 alternatives but never named echonoshy/cgft-llm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some practical examples for implementing AI agent systems with LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Auto-GPT
    4. BabyAGI
    5. CrewAI
    6. AutoGen
    7. Haystack

    AI recommended 7 alternatives but never named echonoshy/cgft-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 echonoshy/cgft-llm?
    pass
    AI named echonoshy/cgft-llm explicitly

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

  • If a team adopts echonoshy/cgft-llm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named echonoshy/cgft-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 echonoshy/cgft-llm solve, and who is the primary audience?
    pass
    AI did not name echonoshy/cgft-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?

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echonoshy/cgft-llm — RepoGEO report