RRepoGEO

REPOGEO REPORT · LITE

openai/mujoco-worldgen

Default branch master · commit 39f52b1b · scanned 6/14/2026, 3:32:19 AM

GitHub: 587 stars · 117 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 openai/mujoco-worldgen, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening paragraph for RL context

    Why:

    CURRENT
    # Worldgen: Randomized MuJoCo environments
    
    Worldgen allows users to generate complex, heavily randomized environments environments. Examples of such environments can be found in the `examples` folder.
    COPY-PASTE FIX
    # Worldgen: Procedural MuJoCo Environment Generation for Reinforcement Learning and Robotics Simulation
    
    Worldgen is a library for programmatically generating complex, heavily randomized MuJoCo environments, specifically designed to facilitate reinforcement learning research, agent training, and domain randomization.
  • mediumabout#2
    Update repository description for clarity on RL use case

    Why:

    CURRENT
    Automatic object XML generation for Mujoco
    COPY-PASTE FIX
    Programmatic generation of diverse and randomized MuJoCo environments for reinforcement learning and agent training.

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 openai/mujoco-worldgen
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Unity
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Unity · recommended 2×
  2. PyBullet · recommended 2×
  3. MuJoCo · recommended 2×
  4. Isaac Sim · recommended 2×
  5. Gazebo · recommended 2×
  • CATEGORY QUERY
    How to programmatically generate diverse physics simulation environments for agent training?
    you: not recommended
    AI recommended (in order):
    1. Unity
    2. ML-Agents
    3. PyBullet
    4. MuJoCo
    5. Isaac Gym
    6. Isaac Sim
    7. Gazebo
    8. Gymnasium

    AI recommended 8 alternatives but never named openai/mujoco-worldgen. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for automating the creation of randomized 3D scenes for robotic simulation?
    you: not recommended
    AI recommended (in order):
    1. Isaac Sim
    2. Blender
    3. Unity
    4. Gazebo
    5. MuJoCo
    6. PyBullet

    AI recommended 6 alternatives but never named openai/mujoco-worldgen. 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 openai/mujoco-worldgen?
    pass
    AI named openai/mujoco-worldgen explicitly

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

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

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

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