RRepoGEO

REPOGEO REPORT · LITE

nasa-jpl/rosa

Default branch main · commit e7e53754 · scanned 5/16/2026, 11:06:35 AM

GitHub: 1,515 stars · 161 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 nasa-jpl/rosa, 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 statement to clarify ROSA's specific role in robotics.

    Why:

    CURRENT
    The ROS Agent (ROSA) is designed to interact with ROS-based<br>robotics systems using natural language queries. 🗣️🤖
    COPY-PASTE FIX
    ROSA is an AI Agent specifically designed for robot developers to inspect, diagnose, understand, and operate ROS1- and ROS2-based robotics systems using natural language queries. 🗣️🤖
  • mediumreadme#2
    Add a dedicated section to the README explaining the problem ROSA solves for robot developers.

    Why:

    COPY-PASTE FIX
    ## What Problem Does ROSA Solve?
Robot developers often spend significant time on manual inspection, diagnosis, and operation of complex ROS1 and ROS2 systems. ROSA streamlines this process by enabling natural language interaction, allowing for faster debugging, deeper system understanding, and intuitive command execution without needing to write code or use complex command-line tools.
  • lowtopics#3
    Add more granular topics to GitHub to further specify ROSA's application.

    Why:

    CURRENT
    agents, ai, developer-tools, jpl, llm, nasa, robotics, ros, ros2
    COPY-PASTE FIX
    agents, ai, developer-tools, jpl, llm, nasa, robotics, ros, ros2, robot-diagnostics, robot-operation, natural-language-robotics-interface

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 nasa-jpl/rosa
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amazon Lex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amazon Lex · recommended 2×
  2. Rasa NLU · recommended 1×
  3. Google Cloud Speech-to-Text API · recommended 1×
  4. Mozilla DeepSpeech · recommended 1×
  5. OpenAI GPT-3 · recommended 1×
  • CATEGORY QUERY
    How can I control ROS-based robots using natural language commands?
    you: not recommended
    AI recommended (in order):
    1. Rasa NLU
    2. Google Cloud Speech-to-Text API
    3. Mozilla DeepSpeech
    4. OpenAI GPT-3
    5. OpenAI GPT-4
    6. Azure Speech-to-Text
    7. Snips NLU
    8. Google Dialogflow
    9. Amazon Lex
    10. Mycroft AI
    11. CMU Sphinx
    12. Pocketsphinx

    AI recommended 12 alternatives but never named nasa-jpl/rosa. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI agents help diagnose and operate robotics systems with natural language queries?
    you: not recommended
    AI recommended (in order):
    1. ROS
    2. OpenAI GPT
    3. GPT-4
    4. Llama 3
    5. Mistral
    6. ros_comm
    7. OpenAI API
    8. Google DeepMind's Robotics Transformer
    9. RT-1
    10. RT-2
    11. NVIDIA Isaac Sim
    12. NVIDIA Omniverse
    13. Omniverse ACE
    14. Riva
    15. Audio2Face
    16. LangChain
    17. LlamaIndex
    18. AWS RoboMaker
    19. Amazon Lex
    20. Amazon Comprehend
    21. Google Cloud AI Platform

    AI recommended 21 alternatives but never named nasa-jpl/rosa. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 nasa-jpl/rosa?
    pass
    AI named nasa-jpl/rosa explicitly

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

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

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

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