RRepoGEO

REPOGEO REPORT · LITE

jonyzhang2023/awesome-humanoid-learning

Default branch main · commit 6a1b8818 · scanned 6/16/2026, 2:53:02 AM

GitHub: 929 stars · 43 forks

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 jonyzhang2023/awesome-humanoid-learning, 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
  • highabout#1
    Update 'About' description to clarify repo type

    Why:

    CURRENT
    Humanoid Robots Resources
    COPY-PASTE FIX
    A curated awesome list of resources for humanoid robot learning, locomotion, and control.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    humanoid-robots, robot-learning, locomotion, manipulation, whole-body-control, physics-based-animation, awesome-list, robotics
  • highlicense#3
    Add a LICENSE file and declare it in README

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root, choosing an appropriate open-source license (e.g., MIT, Apache-2.0, or GPL-3.0). Then, add a new section to your README, for example: `## License

This project is licensed under the [Your Chosen License Name] - see the [LICENSE](LICENSE) file for details.`

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 jonyzhang2023/awesome-humanoid-learning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Humanoids Lab at the Karlsruhe Institute of Technology (KIT)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Humanoids Lab at the Karlsruhe Institute of Technology (KIT) · recommended 1×
  2. MIT Biomimetic Robotics Lab (Sangbae Kim's Lab) · recommended 1×
  3. Honda Research Institute (HRI) - ASIMO Project · recommended 1×
  4. Boston Dynamics (Atlas Robot) · recommended 1×
  5. Robot Operating System (ROS) · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources for learning humanoid robot locomotion and control?
    you: not recommended
    AI recommended (in order):
    1. Humanoids Lab at the Karlsruhe Institute of Technology (KIT)
    2. MIT Biomimetic Robotics Lab (Sangbae Kim's Lab)
    3. Honda Research Institute (HRI) - ASIMO Project
    4. Boston Dynamics (Atlas Robot)
    5. Robot Operating System (ROS)
    6. Gazebo Simulators
    7. ros_control
    8. Humanoid Robotics: A Design and Control Perspective
    9. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    10. IEEE International Conference on Robotics and Automation (ICRA)

    AI recommended 10 alternatives but never named jonyzhang2023/awesome-humanoid-learning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good resources for physics-based animation techniques applied to humanoid robot development?
    you: not recommended
    AI recommended (in order):
    1. MuJoCo (deepmind/mujoco)
    2. PyBullet (bulletphysics/bullet3)
    3. Gazebo (osrf/gazebo)
    4. ROS (Robot Operating System) (ros/ros)
    5. Isaac Sim
    6. DART (Dynamic Animation and Robotics Toolkit) (dartsim/dart)
    7. ODE (Open Dynamics Engine) (odephysics/ode)
    8. Unity

    AI recommended 8 alternatives but never named jonyzhang2023/awesome-humanoid-learning. 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 jonyzhang2023/awesome-humanoid-learning?
    pass
    AI named jonyzhang2023/awesome-humanoid-learning explicitly

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

  • If a team adopts jonyzhang2023/awesome-humanoid-learning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jonyzhang2023/awesome-humanoid-learning 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 jonyzhang2023/awesome-humanoid-learning solve, and who is the primary audience?
    pass
    AI did not name jonyzhang2023/awesome-humanoid-learning — 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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  • Brand-free category queries5 vs 2 in Lite
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