Omniverse Realtime Viewer

NVIDIAOfficialCreated by NVIDIA Omniverse

Skill
Tool integration
Software development
Apache-2.0
Medium risk

From the author

Use as the top-level router for Omniverse Realtime Viewer USD apps, XR delivery, SPG GPU processing, stylized rendering, and focused viewer reference documents.

— the description by NVIDIA Omniverse

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Omniverse Realtime Viewer skill acts as a central routing and architectural framework for developing USD-based 3D viewer applications. It provides a structured approach to composing rendering, scene state, and delivery mechanisms, ensuring that developers can integrate OVRTX rendering, OVStage scene management, and various UI or streaming adapters effectively. The skill emphasizes a modular architecture where the viewer runtime, UI/input adapters, and delivery systems are decoupled, allowing for consistent behavior across local and streamed environments.

What it does

Provides a routing architecture for USD viewer apps, XR delivery, and GPU-accelerated rendering.
Defines the separation of concerns between viewer runtime, UI adapters, and delivery systems.
Offers guidance on integrating OVRTX for high-fidelity 3D rendering.
Establishes conventions for camera interaction, scene state management, and input handling.
Supports the implementation of specialized features like stylized rendering and CAE/CFD visualization.
Provides protocols for agent-to-UI communication and scene control.

When to use it

When starting the development of a new USD-based realtime viewer application.
When integrating advanced rendering features like stylized visualization or AOV switching.
When building XR or spatial editing capabilities into an existing Omniverse application.
When you need to standardize the architecture for local and streamed viewer deployments.
When implementing chat-driven scene control or agent-based inspection of a 3D scene.

Advantages

Promotes a clean, modular architecture that separates rendering logic from UI and transport.
Ensures consistent behavior across different delivery methods, such as local windows or WebRTC streaming.
Provides clear paths for extending functionality without disrupting the core viewer runtime.
Facilitates the integration of complex simulation and visualization data into the viewer.
Standardizes conventions for scene state, selection, and camera control.

Usage examples

“How do I set up a basic USD viewer application using the Omniverse Realtime Viewer architecture?”: The agent will guide you to start with the viewer app reference, resolve dependencies, and implement the core runtime owner to manage the OVStage and OVRTX renderer.
“I need to add stylized rendering to my existing viewer. Where should I start?”: The agent will direct you to the stylized visualization references to implement the required USD/Lua/CUDA nodes within your existing runtime owner.
“How can I enable an AI agent to control the viewer scene?”: The agent will point to the A2UI Scene Copilot reference to implement an operation interface that allows the agent to send commands through the existing runtime owner.
“How do I switch between different render outputs like beauty and depth in my viewer?”: The agent will explain how to use the AOV switching reference to map RenderVars and update the RenderProduct's orderedVars through the runtime owner.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/nvidia/omniverse-realtime-viewer/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip omniverse-realtime-viewer.zip -d .agents/skills

Documentation by NVIDIA Omniverse

Omniverse Realtime Viewer

Build responsive USD viewers by composing OVRTX rendering, OVStage scene state, and the delivery/UI libraries appropriate to the app. Use this package for viewer architecture and interaction; use each selected SDK's upstream guidance for installation and exact release-specific APIs.

Start With The App

When delivery is explicit, select its recipe through references/routing.md and follow its current phase. Otherwise start with references/usd-viewer-app/README.md. For an existing app, keep its architecture and read only the references for the requested change. Broad app, conventions and UI catalogs are lookups as needed.
Resolve the selected libraries through references/dependencies/README.md. Preserve the project's manifest unless an upgrade is requested.
Build a working frame and camera interaction in the chosen shell, then add the requested capabilities. Read references/conventions.md for shared input, camera, selection, and protocol conventions.
Use references/viewer-ux-workflow/README.md for broader interface design. Loading, selection feedback, errors, and input responsiveness belong in the first working app, alongside rendering.
Validate the actual delivery path with references/validation.md. A browser screenshot does not validate a native window or a different transport.

Architecture

Owner	Responsibility
Viewer runtime	Own the live OVStage, publication clock, OVRTX renderer, scene changes, and render stepping.
UI and input adapter	Display frames and copied app state; send user intent to the runtime owner.
Storage/query/simulation workers	Perform their assigned work and return results through the selected integration boundary.
Delivery adapter	Present locally or stream through ovstream; respect frame ownership and backpressure.

Use OVRTX for USD/3D rendering. Browser apps display its WebRTC video; local apps present its output through their native shell. A missing GPU means rendering is unverified, not a reason to substitute a browser 3D renderer.

Keep viewer cameras, settings, effects, and transient edits in app-owned session or runtime state so the source USD stays intact. Serialize scene mutation and render stepping through the runtime owner. Read references/ovstage-ovrtx-integration/README.md for that loop, then the population or data-plane references when implementing scene loading or attribute writes.

Keep expensive loading and metadata work off the UI and render threads. Keep transport details behind a delivery adapter so camera, selection, properties, and loading state can be reused across local and streamed shells.

Add Capabilities As Needed

Use references/routing.md to select camera/picking, scene management, render settings, cloud assets, simulation, editor tools, deployment, or CAE/CFD visualization. Read the selected capability's implementation flow and its linked contract; the full reference catalog is not a prerequisite for a first frame.

For simulation, use the routing reference's Simulation Ecosystem section plus references/realtime-sim-integration/README.md. For UI-driven forces or control, add references/interaction-round-trip/README.md.

For example scenes, use references/usd-sample-data/README.md. When a runtime failure needs diagnosis, use references/troubleshooting/README.md and the selected SDK's matching release guidance before changing the architecture.

Solid Modeling: Upstream First

For usd-brep, exact BRep, solid modeling, kernel failures, CAD topology, or BrepArray questions, first read references/dependencies/README.md → USD BRep. Follow the owning repository's current agent guidance, skills, operation docs, and package API before selecting local integration references. Discover the upstream router rather than assuming skill names or directory layouts remain fixed. Upstream owns modeling semantics, schema rules, tuning, and diagnostics; this package owns OVRTX display, worker handoff, selection mapping, and publication timing.

GPU Processing And Stylized Viewers

For custom GPU processing, chained outputs and lens sampling, read references/spg-processing/README.md. For toon, ink, technical/X-Ray styles, geometry strokes or full wireframe, continue to references/stylized-visualization/implementation.md. Its USD/Lua/CUDA starting node and geometry/depth/composite build sequence work with the selected viewer recipe; use references/stylized-visualization/style-recipes.md for the preset math and references/stylized-visualization/README.md for supporting contracts. Implement the result inside the existing OVRTX/runtime owner and deliver the published processed output. These instructions do not require a sample checkout or a prior stylized-rendering implementation.

For an optional usd-brep geometry source, first read references/dependencies/README.md → USD BRep and the owning repository's current agent guidance, skills, and operation docs; then read references/stylized-visualization/usd-brep-source.md for the display boundary.

XR Viewers

For headsets, immersive viewers, or spatial editors, start with references/xr-viewer-recipe/README.md. Resolve SDK setup and contracts through references/dependencies/ovxr.md; the library owns OpenXR lifecycle and frame submission. For controllers, hands, navigation, or scene tools, add references/xr-spatial-input/README.md and references/ovxr-python-interactions/README.md. For projection-integrated UI, read references/ovxr-composition-ui/README.md and references/ovxr-composition-ui-validation/README.md.

Files

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references/cae-cfd-visualization/cae-data-ingestion.md

Native CAE File Ingestion

Use this reference to read EnSight Gold .case series or CGNS .cgns files into Warp SimData datasets and fields. For arrays already supplied by a solver or converter, use the model factories in data-and-operators.md.

Reader and runtime boundary

Use the CAE OpenUSD Plugins native-file readers with warp_simdata.usd. Resolve the plugin, OpenUSD and Warp SimData combination through references/dependencies/README.md; its upstream OpenUSD API and reader guides own supported formats, schema layouts and compatibility.

Keep this source stage in the scientific ingestion worker when its OpenUSD runtime differs from the viewer's renderer runtime. The worker owns native-file reads and operators; return copied geometry, fields and provenance to the viewer owner for publication into its live OVStage. Retain the source stage and backing files while lazy array reads are outstanding.

Register plugins before importing scientific schema modules or opening a stage. Use registration failure as a setup error; do not silently substitute an empty dataset. Raw-array ingestion remains a separate route when the application already has a verified reader or solver output.

import cae_openusd_plugins

cae_openusd_plugins.register_usd_plugins()

from pxr import Usd
import warp_simdata.usd as simusd

stage = Usd.Stage.Open(asset_path)
if not stage:
    raise RuntimeError(f"Cannot open scientific asset: {asset_path}")

candidates = list(simusd.find_supported_prims(stage))
for prim in candidates:
    print(prim.GetPath())

Choose a dataset and field

Discovery returns adapter candidates, not disjoint blocks or a guarantee that conversion succeeds. Select the intended part, zone or section by path and inspect its fields. A CGNS zone may aggregate its section datasets; do not load the zone and concatenate those same sections again. Use the reader's zone/section relationships to select nonoverlapping data, rather than choosing every candidate or assuming the first prim represents a whole multiblock file. A conversion can return a Dataset or DatasetCollection; check the chosen operator's support.

prim = stage.GetPrimAtPath(dataset_prim_path)
if not prim:
    raise ValueError(f"Missing dataset: {dataset_prim_path}")

time_code = Usd.TimeCode.EarliestTime()
fields = {info.name: info for info in simusd.list_fields(prim, time_code=time_code)}
if field_name not in fields:
    raise ValueError(f"Missing field: {field_name}")

dataset = simusd.dataset_from_prim(prim, device="cpu", time_code=time_code)
field = simusd.field_from_prim(prim, field_name, device="cpu", time_code=time_code)
dataset.add_field(field_name, field)

Use FieldInfo.name as the loader key; its label is for display. Dataset loading does not attach fields automatically. Use the same device, time code and any adapter-specific representation for geometry and field loading. CPU execution is useful for source-value checks; select a supported CUDA device for GPU work.

Read transient samples together

Native-file arrays can be time sampled even for a single-state asset. Request EarliestTime() or an explicit Usd.TimeCode(sample_time) instead of relying on the loaders' Default() argument. Reload geometry and the selected fields at that same time: EnSight geometry can deform while connectivity stays fixed, and transient CGNS fields can change on a static grid.

Derive the timeline from the reader's time mapping and source metadata. CGNS and EnSight readers can map sample indices or source time values; an index with the default scale does not establish physical elapsed seconds. Do not infer a steady file merely from sparse lazy-array metadata. Check explicit first, middle and last samples against source values. Reuse topology only after verifying stable connectivity and node ordering, not just equal point counts.

Keep source values, association and units with each sample. Display units and colormap limits are application choices unless the source declares them; report those choices separately from the data range. Feed these matched samples to temporal-playback.md.

Preserve association through surface extraction

Compare field.association with warp_simdata.AssociationType.NODE or ELEMENT; these are scientific associations, not USD interpolation strings. Validate field length against the selected dataset's node or element count.

Use the operator result's topology rather than assuming every dataset has SIDS grid_coords and 1-based element_connectivity members. For an external surface, element_faces.compute(dataset, external_only=True) provides points and 0-based face indices plus node_idx and element_idx source provenance. Gather source field values through the corresponding provenance:

Source association	Gather by	Surface primvar interpolation
`NODE`	output `node_idx`	`vertex`, one value per output point
`ELEMENT`	output `element_idx`	`uniform`, one value per output face

For face-corner colors, expand the gathered face values by face counts or gather node values through face indices, and use faceVarying. Slice and iso-surface operators create new sample locations; use their supported field interpolation or explicit sampling contract rather than treating new vertices as source nodes. See data-and-operators.md for operator selection and usd-authoring-and-materials.md for publication.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python, Needs Node.js

The author says: Orchestrator skill. Downstream focused references may require NVIDIA GPUs, ovrtx, ovstream, ovui, OpenUSD, Python, Node/React, Tauri, Electron, C++, or cloud GPU deployment access depending on the selected viewer path.

Security

What our scanner noticed· Medium risk

Large base64-encoded blobs
Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

NVIDIA Omniverse

Publisher

NVIDIA (Official)

Source

NVIDIA/skills · skills/omniverse-realtime-viewer · commit fce3cca

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE-APACHE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

AutoGineer is not affiliated with or endorsed by NVIDIA Omniverse or NVIDIA.

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The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download omniverse-realtime-viewer.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by NVIDIA Omniverse

Omniverse Realtime Viewer

Start With The App

Architecture

Add Capabilities As Needed

Solid Modeling: Upstream First

GPU Processing And Stylized Viewers

XR Viewers

Files

references/cae-cfd-visualization/cae-data-ingestion.md

Native CAE File Ingestion

Reader and runtime boundary

Choose a dataset and field

Read transient samples together

Preserve association through surface extraction

Requirements and compatibility

Security

Attribution and licence

Related skills

Setup TS Deep Modules

To Spec

Improve Codebase Architecture

Domain Modeling

Codebase Design

Prototype

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