RRepoGEO

REPOGEO REPORT · LITE

Intent-Lab/VisionClaw

Default branch main · commit 1d6ca077 · scanned 5/24/2026, 10:03:33 PM

GitHub: 2,313 stars · 431 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 Intent-Lab/VisionClaw, 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
  • highreadme#1
    Reposition README's opening to clarify application domain

    Why:

    CURRENT
    A real-time AI assistant for Meta Ray-Ban smart glasses. See what you see, hear what you say, and take actions on your behalf -- all through voice.
    COPY-PASTE FIX
    VisionClaw is a real-time AI assistant application for Meta Ray-Ban smart glasses, enabling voice, vision, and agentic actions directly from your eyewear. Unlike robotics frameworks, VisionClaw is purpose-built for wearable AI experiences. See what you see, hear what you say, and take actions on your behalf -- all through voice.
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    ## License

This project is released under [describe your specific license(s) here, e.g., 'a custom license combining elements of Apache 2.0 and MIT']. Please refer to the `LICENSE` file for full details.

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 Intent-Lab/VisionClaw
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow Lite
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow Lite · recommended 2×
  2. MediaPipe · recommended 2×
  3. PyTorch Mobile · recommended 2×
  4. OpenCV · recommended 2×
  5. Edge Impulse · recommended 2×
  • CATEGORY QUERY
    Seeking a framework to develop a real-time voice and vision AI assistant for smart glasses.
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. MediaPipe
    3. PyTorch Mobile
    4. ONNX Runtime
    5. OpenCV
    6. Kaldi
    7. Vosk
    8. NVIDIA JetPack SDK
    9. TensorRT
    10. Edge Impulse

    AI recommended 10 alternatives but never named Intent-Lab/VisionClaw. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement real-time multimodal AI with agentic actions on mobile or wearable devices?
    you: not recommended
    AI recommended (in order):
    1. MediaPipe
    2. TensorFlow Lite
    3. Core ML
    4. ML Kit
    5. PyTorch Mobile
    6. Flutter
    7. OpenCV
    8. Edge Impulse

    AI recommended 8 alternatives but never named Intent-Lab/VisionClaw. 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 Intent-Lab/VisionClaw?
    pass
    AI named Intent-Lab/VisionClaw explicitly

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

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

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

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Intent-Lab/VisionClaw — 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