RRepoGEO

REPOGEO REPORT · LITE

zevorn/rt-claw

Default branch main · commit 36d128f7 · scanned 6/17/2026, 10:52:12 AM

GitHub: 4 stars · 0 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 zevorn/rt-claw, 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
    Clarify the project's domain in the README's opening

    Why:

    CURRENT
    **RT-Claw** is an OpenClaw-inspired intelligent assistant for embedded devices.
    COPY-PASTE FIX
    **RT-Claw** is an OpenClaw-inspired intelligent assistant for embedded devices, *not* a Request Tracker (RT) system.
  • mediumreadme#2
    Integrate the 'low-cost hardware' value proposition into the README's main introduction

    Why:

    CURRENT
    > Deploy your own AI assistant on hardware that costs just one dollar — seamlessly integrated into your daily workflow, efficiently bridging the digital and physical worlds.
    COPY-PASTE FIX
    Add the following sentence to the introductory paragraph of the README, immediately after the first sentence: 'It enables you to deploy your own AI assistant on hardware that costs just one dollar, seamlessly integrating into your daily workflow and efficiently bridging the digital and physical worlds.'

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 zevorn/rt-claw
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Edge Impulse
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Edge Impulse · recommended 2×
  2. tensorflow/tensorflow · recommended 1×
  3. micropython/micropython · recommended 1×
  4. adafruit/circuitpython · recommended 1×
  5. vpatron/ulab · recommended 1×
  • CATEGORY QUERY
    How can I deploy an intelligent assistant on very low-cost embedded hardware?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite Micro (tensorflow/tensorflow)
    2. Edge Impulse
    3. MicroPython (micropython/micropython)
    4. CircuitPython (adafruit/circuitpython)
    5. ulab (vpatron/ulab)
    6. OpenCV Lite (opencv/opencv)

    AI recommended 6 alternatives but never named zevorn/rt-claw. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools support building AI assistants across various embedded operating systems?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow Lite
    2. PyTorch Mobile
    3. LibTorch
    4. ONNX Runtime
    5. Edge Impulse
    6. OpenVINO Toolkit
    7. Arm Ethos-U
    8. CMSIS-NN
    9. DeepSpeech
    10. Vosk

    AI recommended 10 alternatives but never named zevorn/rt-claw. 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 zevorn/rt-claw?
    pass
    AI named zevorn/rt-claw explicitly

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

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

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

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zevorn/rt-claw — 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