RRepoGEO

REPOGEO REPORT · LITE

Atome-FE/llama-node

Default branch main · commit 3ad64d0a · scanned 6/15/2026, 1:33:16 PM

GitHub: 863 stars · 64 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 Atome-FE/llama-node, 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
  • mediumtopics#1
    Add more specific topics for local and JavaScript LLM inference

    Why:

    CURRENT
    ai, embeddings, gpt, langchain, large-language-models, llama, llama-node, llama-rs, llamacpp, llm, napi, napi-rs, nodejs, rwkv
    COPY-PASTE FIX
    ai, embeddings, gpt, langchain, large-language-models, llama, llama-node, llama-rs, llamacpp, llm, napi, napi-rs, nodejs, rwkv, local-llm, offline-llm, javascript-llm, electron-llm
  • lowreadme#2
    Add a 'Comparison' or 'Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., `## Comparison with Alternatives` or `## Why LLaMA Node?` that briefly explains how `llama-node` relates to `llama.cpp` (as a Node.js binding) and highlights its unique features or design choices compared to other Node.js LLM wrappers like `node-llama-cpp`.

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 Atome-FE/llama-node
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ggerganov/llama.cpp
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ggerganov/llama.cpp · recommended 2×
  2. ollama/ollama · recommended 1×
  3. axios/axios · recommended 1×
  4. node-fetch/node-fetch · recommended 1×
  5. withcatai/node-llama-cpp · recommended 1×
  • CATEGORY QUERY
    How can I integrate local large language models into a Node.js application?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. axios (axios/axios)
    3. node-fetch (node-fetch/node-fetch)
    4. Llama.cpp (ggerganov/llama.cpp)
    5. node-llama-cpp (withcatai/node-llama-cpp)
    6. LM Studio
    7. LocalAI (go-skynet/LocalAI)
    8. OpenAI (openai/openai-node)

    AI recommended 8 alternatives but never named Atome-FE/llama-node. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the options for running open-source LLMs directly on a laptop CPU with JavaScript?
    you: not recommended
    AI recommended (in order):
    1. Transformers.js (huggingface/transformers.js)
    2. Web LLM (mlc-ai/web-llm)
    3. ONNX Runtime Web (microsoft/onnxruntime-web)
    4. llama.cpp (ggerganov/llama.cpp)
    5. TensorFlow.js (tensorflow/tfjs)

    AI recommended 5 alternatives but never named Atome-FE/llama-node. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 Atome-FE/llama-node?
    pass
    AI named Atome-FE/llama-node explicitly

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

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

    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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Atome-FE/llama-node — 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