RRepoGEO

REPOGEO REPORT · LITE

openai/mujoco-py

Default branch master · commit a13903b8 · scanned 6/27/2026, 10:31:58 AM

GitHub: 3,141 stars · 823 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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-py, 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
  • hightopics#1
    Add relevant topics for physics simulation and Python bindings

    Why:

    COPY-PASTE FIX
    physics-engine, mujoco, python-bindings, robotics, simulation, reinforcement-learning, deprecated
  • highhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://openai.github.io/mujoco-py/build/html/index.html
  • mediumreadme#3
    Clarify the license information in the README

    Why:

    COPY-PASTE FIX
    ## License
This project uses a custom license, as detailed in the [LICENSE](LICENSE) file. It is not a standard SPDX-compliant license.

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-py
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
bulletphysics/bullet3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. bulletphysics/bullet3 · recommended 2×
  2. deepmind/mujoco · recommended 2×
  3. viblo/pymunk · recommended 2×
  4. sofa-framework/sofa · recommended 2×
  5. ODE · recommended 1×
  • CATEGORY QUERY
    What are the best Python libraries for rigid body physics simulation?
    you: not recommended
    AI recommended (in order):
    1. PyBullet (bulletphysics/bullet3)
    2. MuJoCo (deepmind/mujoco)
    3. Pymunk (viblo/pymunk)
    4. ODE
    5. SOFA (sofa-framework/sofa)

    AI recommended 5 alternatives but never named openai/mujoco-py. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I efficiently simulate complex physical interactions with contacts in Python?
    you: not recommended
    AI recommended (in order):
    1. PyBullet (bulletphysics/bullet3)
    2. MuJoCo (deepmind/mujoco)
    3. Drake (RobotLocomotion/drake)
    4. Pymunk (viblo/pymunk)
    5. SOFA (sofa-framework/sofa)
    6. FEniCS Project (FEniCS/dolfin)
    7. Siconos (siconos/siconos)

    AI recommended 7 alternatives but never named openai/mujoco-py. 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-py?
    pass
    AI named openai/mujoco-py 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-py in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/mujoco-py 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-py solve, and who is the primary audience?
    pass
    AI named openai/mujoco-py explicitly

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

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openai/mujoco-py — 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