RRepoGEO

REPOGEO REPORT · LITE

Liquid4All/cookbook

Default branch main · commit 4b47035c · scanned 6/25/2026, 12:42:33 AM

GitHub: 2,093 stars · 342 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 Liquid4All/cookbook, 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
  • highabout#1
    Clarify the 'About' description to prevent miscategorization

    Why:

    CURRENT
    Examples, end-2-end tutorials and apps built using Liquid AI Foundational Models (LFM) and the LEAP SDK
    COPY-PASTE FIX
    Practical examples, end-to-end tutorials, and applications for deploying and integrating Liquid AI Foundational Models (LFM) and the LEAP SDK on mobile, edge, and desktop devices.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root, specifying the chosen open-source license (e.g., Apache-2.0, MIT).
  • mediumtopics#3
    Expand repository topics for better category visibility

    Why:

    CURRENT
    android, edge, ios, language-model, language-models, laptop
    COPY-PASTE FIX
    android, edge, ios, language-model, language-models, laptop, llm-deployment, mobile-ai, edge-ai, foundational-models, ai-examples, machine-learning-examples

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 Liquid4All/cookbook
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MediaTek NeuroPilot
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. MediaTek NeuroPilot · recommended 1×
  2. Qualcomm AI Engine Direct · recommended 1×
  3. Apple Core ML · recommended 1×
  4. Google TensorFlow Lite · recommended 1×
  5. ONNX Runtime · recommended 1×
  • CATEGORY QUERY
    How can I deploy large language models efficiently on mobile or edge devices?
    you: not recommended
    AI recommended (in order):
    1. MediaTek NeuroPilot
    2. Qualcomm AI Engine Direct
    3. Apple Core ML
    4. Google TensorFlow Lite
    5. ONNX Runtime
    6. NVIDIA JetPack SDK
    7. OpenVINO Toolkit

    AI recommended 7 alternatives but never named Liquid4All/cookbook. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking practical examples for integrating foundational AI models into desktop and mobile applications.
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Hugging Face Transformers Library
    3. Google Cloud AI Platform / Vertex AI
    4. Microsoft Azure AI Services
    5. TensorFlow Lite / PyTorch Mobile
    6. ML.NET
    7. Core ML

    AI recommended 7 alternatives but never named Liquid4All/cookbook. 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 Liquid4All/cookbook?
    pass
    AI did not name Liquid4All/cookbook — 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?

  • If a team adopts Liquid4All/cookbook in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Liquid4All/cookbook 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 Liquid4All/cookbook solve, and who is the primary audience?
    pass
    AI named Liquid4All/cookbook explicitly

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

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Liquid4All/cookbook — 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