RRepoGEO

REPOGEO REPORT · LITE

zchoi/Awesome-Embodied-Robotics-and-Agent

Default branch main · commit d3ba025d · scanned 5/13/2026, 10:38:31 PM

GitHub: 1,784 stars · 96 forks

AI VISIBILITY SCORE
22 /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
1 / 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 zchoi/Awesome-Embodied-Robotics-and-Agent, 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 README H1 to explicitly state it's an 'Awesome List'

    Why:

    CURRENT
    # 🤖 Awesome Embodied Robotics and Agent
    COPY-PASTE FIX
    # 🤖 Awesome Embodied Robotics and Agent: A Curated List of Research
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/zchoi/Awesome-Embodied-Robotics-and-Agent
  • lowabout#3
    Refine the repository description for conciseness and keyword reinforcement

    Why:

    CURRENT
    This is a curated list of "Embodied AI or robot with Large Language Models" research. Watch this repository for the latest updates! 🔥
    COPY-PASTE FIX
    A curated list of cutting-edge research on Embodied AI and robotics, specifically focusing on integration with Large Language Models (LLMs) and Vision-Language Models (VLMs).

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 zchoi/Awesome-Embodied-Robotics-and-Agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv · recommended 1×
  2. Google Scholar · recommended 1×
  3. NeurIPS · recommended 1×
  4. ICML · recommended 1×
  5. ICLR · recommended 1×
  • CATEGORY QUERY
    Where can I find recent research on integrating large language models with embodied AI?
    you: not recommended
    AI recommended (in order):
    1. arXiv
    2. Google Scholar
    3. NeurIPS
    4. ICML
    5. ICLR
    6. RSS
    7. CoRL
    8. ICRA
    9. IROS
    10. Science Robotics
    11. Nature Machine Intelligence
    12. IEEE Transactions on Robotics (T-RO)
    13. Journal of Field Robotics
    14. Google DeepMind Blog
    15. Meta AI Blog
    16. Stanford AI Lab
    17. UC Berkeley BAIR Blog
    18. Twitter/X
    19. Hugging Face

    AI recommended 19 alternatives but never named zchoi/Awesome-Embodied-Robotics-and-Agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest advancements in using LLMs for robotic navigation and planning?
    you: not recommended
    AI recommended (in order):
    1. PaLM-E
    2. CLIP
    3. DINOv2
    4. SayCan
    5. Inner Monologue
    6. Code as Policies
    7. ChatGPT
    8. GPT-4

    AI recommended 8 alternatives but never named zchoi/Awesome-Embodied-Robotics-and-Agent. 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 zchoi/Awesome-Embodied-Robotics-and-Agent?
    pass
    AI did not name zchoi/Awesome-Embodied-Robotics-and-Agent — 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?

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

Embed your GEO score

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zchoi/Awesome-Embodied-Robotics-and-Agent — 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