RRepoGEO

REPOGEO REPORT · LITE

AetherCortex/Llama-X

Default branch main · commit 5a823351 · scanned 5/29/2026, 12:23:12 AM

GitHub: 1,605 stars · 103 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 AetherCortex/Llama-X, 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 to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ["llama", "llm", "large-language-models", "sota", "academic-research", "open-source", "fine-tuning", "model-improvement"]
  • highhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Add the official project homepage URL (e.g., a project website, a dedicated research page, or a relevant academic publication link) to the repository settings.
  • mediumreadme#3
    Add a concise sentence to the README clarifying Llama-X's unique positioning

    Why:

    CURRENT
    ## Llama-X: Open Academic Research on Improving LLaMA to SOTA LLM
    COPY-PASTE FIX
    ## Llama-X: Open Academic Research on Progressively Improving LLaMA to SOTA LLM

Unlike foundational models or general-purpose libraries, Llama-X is a continuous academic research project dedicated to advancing LLaMA to state-of-the-art performance through open-source collaboration.

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 AetherCortex/Llama-X
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 1×
  2. facebookresearch/llama · recommended 1×
  3. mistralai/mistral-src · recommended 1×
  4. EleutherAI/ · recommended 1×
  5. openai/ · recommended 1×
  • CATEGORY QUERY
    What open-source projects are actively improving large language models to state-of-the-art?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Meta Llama (facebookresearch/llama)
    3. Mistral AI (mistralai/mistral-src)
    4. EleutherAI (EleutherAI/)
    5. OpenAI (openai/)
    6. Triton (openai/triton)
    7. vLLM (vllm-project/vllm)
    8. DeepSpeed (microsoft/DeepSpeed)

    AI recommended 8 alternatives but never named AetherCortex/Llama-X. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find open academic research projects enhancing general-purpose large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Hub
    2. arXiv
    3. GitHub
    4. Papers With Code
    5. Google AI Blog
    6. Meta AI Blog
    7. Microsoft Research Blog
    8. MLCommons

    AI recommended 8 alternatives but never named AetherCortex/Llama-X. 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 AetherCortex/Llama-X?
    pass
    AI named AetherCortex/Llama-X explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of AetherCortex/Llama-X. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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AetherCortex/Llama-X — 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