NVIDIA/simready-foundation

NVIDIA/simready-foundation

Description: SimReady Foundation is a central repository for defining simulation content specifications based on various runtime use cases.

Language: Python

License: Apache-2.0

Stars: 40

Forks: 6

Open issues: 15

Created: 2026-03-03T18:16:59Z

Pushed: 2026-05-27T18:17:33Z

Default branch: main

Fork: no

Archived: no

README:

SimReady Foundation

Getting the repository

This repository uses Git LFS to track binary and USD asset files (.usda, .usdc, .usd, .usdz, images, and others). You must have Git LFS installed before cloning, otherwise those files will check out as tiny pointer files instead of the real content.

1. Install Git LFS (once per machine)

Windows (PowerShell)

winget install GitHub.GitLFS

If winget is not recognized, run these first:

Add-AppxPackage -RegisterByFamilyName -MainPackage "Microsoft.DesktopAppInstaller_8wekyb3d8bbwe"
Install-Module -Name Microsoft.WinGet.Client -Force -Repository PSGallery
Repair-WinGetPackageManager

Linux (Ubuntu / Debian)

sudo apt-get install git-lfs

After installing, run the one-time setup:

git lfs install

2. Clone the repository

git clone https://github.com/NVIDIA/simready-foundation.git
cd simready-foundation

Git LFS files are fetched automatically during clone when git lfs install has been run. If you already cloned without LFS, pull the real file contents with:

git lfs pull

3. Verify LFS files

You can confirm that LFS-tracked files were downloaded correctly:

git lfs ls-files

If any files still show as pointer files, re-run git lfs pull.

Environment setup

4. Install Python

The product requires **Python >=3.10, Windows

Download from python.org/downloads and run the installer. Check "Add Python to PATH" during installation. If you already have multiple Python versions, you can use the py -3.12 launcher.

Linux (Ubuntu / Debian)

sudo apt-get install python3.12

Verify the installation:

python --version

5. Create a virtual environment

> [!IMPORTANT] > Use a dedicated virtual environment for SimReady validation. The simready-validate tool and its dependencies (omniverse-asset-validator, usd-core) can conflict with other packages. A clean venv avoids hard-to-debug import errors.

Windows (PowerShell)

python -m venv .venv
.venv\Scripts\activate

Linux

python -m venv .venv
source .venv/bin/activate

6. Install dependencies

From the repository root, install the SimReady validation library:

pip install -r nv_core/validator_sample/requirements.txt

This installs simready-validate (which pulls in omniverse-asset-validator and usd-core) and omniverse-usd-profiles.

You're now ready to go. See [Next steps](#next-steps) for guides on validation, profiles, and more.

About SimReady Foundation

SimReady Foundation defines guidelines and requirements for OpenUSD content so that assets work reliably across rendering, simulation, robotics, and AI training workflows within NVIDIA Omniverse.

The framework is built around a layered hierarchy:

| Layer | Purpose | Example | |-------|---------|---------| | Requirement | A single, testable rule an asset must satisfy | *"The stage must define a default prim"* (SAMP.001) | | Capability | A category that groups related requirements | *Sample* (SAMP), *Visualization/Geometry* (VG), *Units* (UN) | | Feature | A set of requirements that together describe a queryable property of an asset | *Minimal Placeable Visual*, *RBD Physics*, *Driven Joints* | | Profile | A bundle of features that defines what an asset must satisfy for a given use case | *Prop-Robotics-Neutral*, *Robot-Body-Isaac* |

Profiles

Profiles are the top-level contracts between asset creators and consumers. Each profile targets a specific simulation scenario and lists the features (and their versions) that an asset must pass. Production profiles in nv_core/sr_specs/ include:

| Profile | Description | |---------|-------------| | Prop-Robotics-Neutral | Neutral-format props suitable for robotics pipelines | | Prop-Robotics-Physx | Props with PhysX rigid-body physics | | Robot-Body-Neutral | Neutral robot body with physics | | Robot-Body-Runnable | PhysX robot body, runnable in simulation |

Use cases

• Static validation — check USD assets against a profile's requirements using the simready-validate CLI or the simready.validate Python API.
• Asset transformation — convert assets between profiles (e.g. Neutral to PhysX to Isaac).
• CI / CD — automate validation in Jenkins or local runners.

Where the specs live

The full SimReady specifications—capabilities, features, profiles, and guides—are in nv_core/sr_specs/docs/.

Next steps

Once you have the environment set up, explore the guides in [nv_core/sr_specs/docs/guides/](nv_core/sr_specs/docs/guides/guides.md):

| Guide | Description | |-------|-------------| | [SimReady Validation Workflow](nv_core/sr_specs/docs/guides/validate_workflow.md) | Run your first validation — commands, expected output, stamping, and troubleshooting | | [Getting Started](nv_core/sr_specs/docs/guides/getting_started.md) | Orientation — who SimReady is for, choosing a profile, and where to go next | | [SimReady Acceptance Workflow](nv_core/sr_specs/docs/guides/acceptance_workflow.md) | How new requirements, features, and profiles move through review | | [Features Expansion Workflow](nv_core/sr_specs/docs/guides/features_expansion_workflow.md) | Create technology-specific feature variants (e.g. neutral to PhysX) | | [Profiles Validation Workflow](nv_core/sr_specs/docs/guides/profiles_validation_workflow.md) | Create, version, and validate assets against profiles | | [Naming Conventions](nv_core/sr_specs/docs/guides/naming_conventions.md) | Asset and prim naming standards |

Agent skills

Repo-local agent skills live under skills//SKILL.md at the repository root. The .agents/skills, .codex/skills, and .claude/skills compatibility links point back to ../skills, so update the skills/ source of truth first.

Use the skills as the first stop when an agent is asked to add, update, validate, package, or conform SimReady content. The guides in nv_core/sr_specs/docs/guides/…