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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

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/nvidia/omniverse-realtime-viewer/download
  2. 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

<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->

<!-- SPDX-License-Identifier: Apache-2.0 -->

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

  1. 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.

  2. Resolve the selected libraries through references/dependencies/README.md. Preserve the project's manifest unless an upgrade is requested.

  3. 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.

  4. 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.

  5. Validate the actual delivery path with references/validation.md. A browser screenshot does not validate a native window or a different transport.

Architecture

OwnerResponsibility
Viewer runtimeOwn the live OVStage, publication clock, OVRTX renderer, scene changes, and render stepping.
UI and input adapterDisplay frames and copied app state; send user intent to the runtime owner.
Storage/query/simulation workersPerform their assigned work and return results through the selected integration boundary.
Delivery adapterPresent 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

references/tauri-local-viewer/README.md

Tauri + Rust OVRTX Viewer

Use this path for a desktop app with a React WebView and a Rust-owned OVRTX renderer. Share UI components through viewer-backend-interface; keep native handles and frame transport inside the Tauri backend. For Python desktop apps use local-viewer; for a remote renderer use streaming-viewer-recipe.

Ownership and frame flow

React controls -> Tauri commands -> render-owner queue
                                      |
                           OVStage edits + publication
                                      |
                              OVRTX step + CPU map
                                      |
React canvas <- Tauri Channel <- owned RGBA frame

One Rust thread owns the renderer, attached OVStage, publication ordinals, camera, and selection. Tauri commands enqueue work; they do not call renderer APIs from the IPC thread. Coalesce continuous pointer motion so old input does not delay the next frame. Preserve button transitions and discrete actions. Use request IDs or reply channels for operations that need a result.

This presentation path copies pixels to the CPU and across IPC. Start with it for a simple desktop implementation; measure readback, transport, and paint cost before choosing a different presentation architecture. Send raw binary frames rather than JPEG or base64 on this local path.

Runtime and stage setup

Acquire matching SDK binaries and headers through dependencies. Generate Rust C bindings from those headers and use the package's runtime loader setup. Use windows-native-setup for Windows packaging. Keep strings, config arrays, and tensor storage alive for the native operation that borrows them.

For attached mode, follow stage-loading and stage-management:

  1. Populate an inline root that sublayers the user's USD and authors the app camera, RenderProduct, and RenderVars.

  2. Complete population, advance and wait for its write floor, then attach the renderer to that stage.

  3. Write camera and feature changes through OVStage; complete and publish them before ovrtx_update_from_stage() and ovrtx_step_with_stage() at that ordinal.

Use ovstage-data-plane for matrix semantics and column layout. A standalone OVRTX backend instead uses its own reset/load/write/step APIs; keep that mode separate from attached-stage mutation. Its camera input descriptor is:

ovrtx_write_attribute:
  attribute:     "omni:xform"
  semantic:      XFORM_MAT4X4
  binding dtype: float64, lanes=16
  input tensor:  (1,4,4) float64, lanes=1, ndim=3, strides=NULL, CPU
  prim_mode:     CREATE_NEW
  access:        SYNC

Choose prim paths once and share them across authoring, camera writes, render requests, and output lookup. For example:

/Session/Cameras/Main       camera
/Session/Render/Viewport    display RenderProduct
/Session/Render/Vars/...    authored RenderVars

On scene replacement, stop stepping, finish outstanding work, release old results, and replace the attached stage through the render owner. Invalidate pending picks, hierarchy caches, and selection by stage generation. Show loading until the new stage produces a displayable frame; preserve the last good frame with a loading indicator while work is pending.

Frame delivery

Map LdrColor to CPU, read its tensor dimensions and strides, and copy RGBA rows into an owned buffer. Use RAII for map and result cleanup on both display and pick paths. No mapped tensor view may outlive its native result.

Register a Tauri Channel<InvokeResponseBody> for binary frame delivery. One possible app payload is:

[u32 width LE][u32 height LE][u64 sequence LE][tightly packed RGBA8 pixels]

The WebView decodes the ArrayBuffer and displays it with ImageData and canvas.putImageData. Bound queued frames and prefer the latest completed frame when presentation falls behind. A new subscriber can receive the cached latest frame immediately. Use ordinary events for lifecycle, errors, and selection.

Keep render resolution independent of window size. Letterbox the image and map input through its content rectangle. If the product needs dynamic resolution, update the RenderProduct through the stage owner, preserve camera state, and reallocate presentation storage from the next frame's dimensions.

Interaction and UI

Implement the shared ViewerBackend operations for scene loading, camera input, picking, selection, hierarchy, properties, and exposed render settings. Advertise only implemented capabilities; route real hierarchy and property queries through stage-hierarchy instead of parsing USD text or returning placeholder values. Cache query results for UI reads and refresh them on stage changes.

Follow viewer-input-routing for gestures and pointer capture. Pointer release or cancellation ends the gesture even outside the viewport. Write finite camera changes before the next render step; derive animation delta from elapsed time and cap catch-up work so a stalled frame does not create an input backlog.

For a click:

  1. Map the click through the displayed image rectangle.

  2. Queue its request ID, stage generation, and displayed RenderProduct.

  3. On the render thread, enqueue the normalized native pick query and step that product at the committed ordinal.

  4. Decode its synthetic ovrtx_pick_hit output and return the canonical path.

  5. Ignore stale-generation results; update the outliner, properties, and native selection outline together.

See native-picking-selection for result decoding and outline groups. Keep optional material effects, animation, and physics behind the same runtime owner; use prim-pick-effects, selection-animation, or physics-simulation when the feature is requested.

Errors and shutdown

Distinguish a pending frame from a failed render. Keep the UI responsive and show the last good frame with an error state when rendering fails. Allow scene reload or an explicit retry to recover; do not report readiness before a frame arrives.

On close, stop accepting commands, finish native operations, release mappings and results, detach the stage, and destroy the renderer on its owner thread. Validate the packaged app through first frame, camera interaction, picking, scene replacement, and close. Include a screenshot from the real WebView path; a Rust build alone does not exercise SDK loading or presentation.

Separate-process SHM variant

For a Tauri shell consuming a separate renderer, use the unified client and ownership contract. Generate complete repr(C) structs and tagged unions from the matching headers; validate layout on the target platform. Stop and join frame waits before client destruction, and keep callback data alive until destruction completes.

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

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Download ZIP

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