RRepoGEO

REPOGEO REPORT · LITE

Auromix/ROS-LLM

Default branch ros2-humble · commit c22f4483 · scanned 6/6/2026, 4:58:08 AM

GitHub: 799 stars · 97 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 Auromix/ROS-LLM, 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
  • highreadme#1
    Reposition the README's opening sentence to emphasize "robot control framework"

    Why:

    CURRENT
    The ROS-LLM project is a ROS framework for embodied intelligence applications. It enables natural language interactions and large model-based control of robot motion and navigation for any robot operating on ROS.
    COPY-PASTE FIX
    The ROS-LLM project is a **ROS framework for natural language robot control**, enabling embodied intelligence applications through large model-based decision-making and navigation for any ROS-compatible robot.
  • mediumhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    Add the official documentation or project website URL (e.g., `https://docs.auromix.com/ros-llm` or similar) to the 'Homepage' field in the repository's 'About' section.
  • mediumreadme#3
    Add a 'Comparison' or 'Why ROS-LLM?' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, under a heading like '## 💡 Why ROS-LLM? (vs. Generic LLM Libraries)', with text such as: 'Unlike general LLM libraries such as LangChain or LlamaIndex, ROS-LLM is purpose-built as a comprehensive framework for direct integration with the Robot Operating System (ROS). It provides specific tools and interfaces for natural language robot control, decision-making, and navigation, rather than just general LLM orchestration.'

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 Auromix/ROS-LLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
openai/openai-python
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/openai-python · recommended 2×
  2. ros/ros_comm · recommended 2×
  3. langchain-ai/langchain · recommended 2×
  4. google/generative-ai-python · recommended 2×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    How to integrate large language models for robot control in a ROS environment?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API (openai/openai-python)
    2. openai (openai/openai-python)
    3. rospy (ros/ros_comm)
    4. LangChain (langchain-ai/langchain)
    5. langchain (langchain-ai/langchain)
    6. transformers (huggingface/transformers)
    7. pytorch (pytorch/pytorch)
    8. tensorflow (tensorflow/tensorflow)
    9. Google Gemini API (google/generative-ai-python)
    10. google-generativeai (google/generative-ai-python)
    11. NVIDIA Jetson
    12. TensorRT-LLM (NVIDIA/TensorRT-LLM)
    13. roscpp (ros/ros_comm)
    14. Microsoft Azure OpenAI Service

    AI recommended 14 alternatives but never named Auromix/ROS-LLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a quick integration framework for LLM-driven robot behavior in ROS.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. ros_langchain
    3. LlamaIndex
    4. Robotics Transformer (RT-1/RT-2)
    5. OpenAI Function Calling/Tools
    6. Hugging Face Transformers

    AI recommended 6 alternatives but never named Auromix/ROS-LLM. 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 Auromix/ROS-LLM?
    pass
    AI named Auromix/ROS-LLM explicitly

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

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

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

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Auromix/ROS-LLM — 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