RRepoGEO

REPOGEO REPORT · LITE

ziangcao0312/PhysX-Anything

Default branch main · commit e221826e · scanned 6/15/2026, 11:28:06 PM

GitHub: 887 stars · 57 forks

AI VISIBILITY SCORE
33 /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
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 ziangcao0312/PhysX-Anything, 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
    Add a concise introductory paragraph to the README

    Why:

    COPY-PASTE FIX
    Add the following paragraph immediately after the author list and before the 'News' section: "PhysX-Anything is a novel framework that generates high-quality, simulation-ready 3D assets with accurate physical properties directly from a single input image. Our method enables the creation of complex 3D objects suitable for physics simulation environments, bridging the gap between visual data and interactive physical worlds."
  • highreadme#2
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    Add a 'License' section to the README, stating: "This project is released under the specific terms outlined in the `LICENSE` file. Please refer to the `LICENSE` file for full details regarding usage, distribution, and modification."
  • mediumtopics#3
    Expand repository topics for better categorization

    Why:

    CURRENT
    3d, image-to-3d, physical-modeling
    COPY-PASTE FIX
    3d, image-to-3d, physical-modeling, physics-simulation, asset-generation, cvpr-2026, deep-learning, computer-vision

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 ziangcao0312/PhysX-Anything
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA/kaolin-wisp
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA/kaolin-wisp · recommended 1×
  2. NVlabs/instant-ngp · recommended 1×
  3. Luma AI · recommended 1×
  4. RealityCapture · recommended 1×
  5. alicevision/Meshroom · recommended 1×
  • CATEGORY QUERY
    How can I generate simulation-ready 3D models with physical properties from a single image?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Kaolin Wisp (NVIDIA/kaolin-wisp)
    2. Instant NeRF (NVlabs/instant-ngp)
    3. Luma AI
    4. RealityCapture
    5. Meshroom (alicevision/Meshroom)
    6. Blender (blender/blender)
    7. Adobe Substance 3D Sampler
    8. Google's Pixel Recursive Neural Network
    9. Maya
    10. 3ds Max
    11. Unity
    12. Unreal Engine
    13. Gazebo (osrf/gazebo)
    14. CoppeliaSim

    AI recommended 14 alternatives but never named ziangcao0312/PhysX-Anything. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to create physically accurate 3D assets for physics simulation environments.
    you: not recommended
    AI recommended (in order):
    1. Blender
    2. Autodesk Maya
    3. Autodesk 3ds Max
    4. SolidWorks
    5. Substance Painter
    6. Substance Designer
    7. Houdini

    AI recommended 7 alternatives but never named ziangcao0312/PhysX-Anything. 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 ziangcao0312/PhysX-Anything?
    pass
    AI named ziangcao0312/PhysX-Anything explicitly

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

  • If a team adopts ziangcao0312/PhysX-Anything in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ziangcao0312/PhysX-Anything 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 ziangcao0312/PhysX-Anything solve, and who is the primary audience?
    pass
    AI did not name ziangcao0312/PhysX-Anything — 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

Drop this badge into the README of ziangcao0312/PhysX-Anything. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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ziangcao0312/PhysX-Anything — 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