RRepoGEO

REPOGEO REPORT · LITE

TommyZihao/vlm_arm

Default branch main · commit 230a9bbc · scanned 6/24/2026, 8:43:29 AM

GitHub: 1,215 stars · 199 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)

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

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 TommyZihao/vlm_arm, 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:

    COPY-PASTE FIX
    ["robotic-arm", "large-language-models", "multimodal-ai", "embodied-ai", "vlm", "gpt4o", "mycobot", "raspberry-pi", "human-robot-interaction", "agent"]
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file (e.g., MIT License) in the repository root to clearly state the terms of use.
  • highreadme#3
    Add a concise project statement to the README introduction

    Why:

    CURRENT
    作者：同济子豪兄
    COPY-PASTE FIX
    本项目是一个开源实现，展示如何将大型语言模型（LLM）和多模态视觉模型（VLM）集成到机械臂控制中，以实现人机协作的具身智能体。它提供了一个将自然语言指令和视觉感知转化为机械臂动作的完整解决方案。

作者：同济子豪兄

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 TommyZihao/vlm_arm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ROS (Robot Operating System)
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ROS (Robot Operating System) · recommended 2×
  2. NVIDIA Isaac Sim · recommended 2×
  3. MoveIt! · recommended 1×
  4. LangChain · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How can I integrate large language models to control a robotic arm with natural language?
    you: not recommended
    AI recommended (in order):
    1. ROS (Robot Operating System)
    2. MoveIt!
    3. LangChain
    4. LlamaIndex
    5. OpenAI API
    6. Anthropic API
    7. Hugging Face Transformers
    8. vLLM
    9. Google Robotics Transformer (RT-X)
    10. Open X-Embodiment
    11. RT-1
    12. RT-2
    13. Microsoft's RoboGen
    14. Azure OpenAI Service
    15. GPT-4
    16. NVIDIA Isaac Sim
    17. Omniverse Code
    18. ChatRTX
    19. T5
    20. BART
    21. Llama 3
    22. Mistral
    23. Ollama
    24. Gemma
    25. PyRobot
    26. URScript

    AI recommended 26 alternatives but never named TommyZihao/vlm_arm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for embodied AI that combines vision, voice, and robotic arm control.
    you: not recommended
    AI recommended (in order):
    1. ROS (Robot Operating System)
    2. MoveIt! (ros-planning/moveit)
    3. OpenCV (opencv/opencv)
    4. TensorFlow (tensorflow/tensorflow)
    5. PyTorch (pytorch/pytorch)
    6. DeepSpeech (mozilla/DeepSpeech)
    7. Kaldi (kaldi-asr/kaldi)
    8. Picovoice (Picovoice/picovoice)
    9. Google Cloud Speech-to-Text
    10. AWS Transcribe
    11. NVIDIA Isaac Sim
    12. Isaac SDK
    13. OpenAI Gym (openai/gym)
    14. Stable Baselines3 (DLR-RM/stable-baselines3)
    15. RLlib (ray-project/ray)
    16. Google Robotics
    17. Microsoft AirSim (microsoft/AirSim)

    AI recommended 17 alternatives but never named TommyZihao/vlm_arm. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 TommyZihao/vlm_arm?
    pass
    AI named TommyZihao/vlm_arm explicitly

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

  • If a team adopts TommyZihao/vlm_arm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TommyZihao/vlm_arm 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 TommyZihao/vlm_arm solve, and who is the primary audience?
    pass
    AI did not name TommyZihao/vlm_arm — 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?

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TommyZihao/vlm_arm — 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