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://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

ATTRIBUTION.mdAdded by AutoGineer943 B
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references/cloud-deployment/nvcf-self-hosted.md

NVCF Self-Hosted Handoff

Triggers

Use this reference for NVCF self-hosted streaming, AWS, Azure, or customer-managed on-premises Kubernetes NVCF infrastructure, NVCF control plane, compute plane, LLS, TURN, streaming proxy, a self-hosted Omniverse Streaming stack, or an in-place stack upgrade.

Upstream Source Of Truth

For this path, use NVIDIA-Omniverse/streaming-self-hosted as the deployment source of truth. Before planning or changing infrastructure, read its root README and its root orchestration skill under .agents/skills/orchestrate-streaming-stack. Then read only the selected component skills for the target cloud provider and enabled services.

Do not copy upstream commands, manifests, chart versions, image-mirroring procedures, credential handling, port matrices, cache setup, storage-service setup, or cloud-provider recipes into this viewer skill package. The upstream repository owns those details.

Build A New Deployment

Start from the public upstream repository even when only this published skill folder is available. Read or clone it into the generated project's dependency workspace; do not require this staging repository, its templates, or an existing cluster. Read its root README and .agents/skills/orchestrate-streaming-stack/SKILL.md, then the selected provider and component skills. Resolve runtime acquisition through ../dependencies/README.md.

For a new deployment, start with the current supported upstream release unless the user specifies a version. Read the latest release notes, Artifact Manifest, and the linked NVCF compatibility matrix before selecting components. Keep the upstream skills, manifest, and documentation aligned to the chosen release; record the resolved versions in generated deployment artifacts rather than pinning them in this skill. Apply these checks:

AWS, Azure, and customer-managed on-premises Kubernetes are supported. For on-premises requests, use the upstream generic-kubernetes-provider skill and On-Premises Deployment Guide.
LLS Streaming Proxy, TURN service, and the LLS Helm chart are publicly available on NGC. Do not require early-access approval for these components. Public availability does not remove the selected platform's authentication, registry, or infrastructure prerequisites; follow the LLS deployment guide.
OVDC (Omniverse Derived Cache, formerly DDCS) replaces deprecated GXCache as the recommended shader cache; new deployments should not install GXCache. OVCC (Omniverse Content Cache, formerly UCC) is the current content-cache name. Resolve versions and any chart image overrides from the manifest, then verify running images against it. Do not follow stale cache names or chart defaults in older upstream examples.
NVCF control-plane, compute-plane, and observability stacks are independently versioned. Select a compatible combination from the NVCF compatibility matrix rather than giving every chart the platform documentation version.
Check whether the current upstream workflow deploys and enables the function autoscaler. If it does not, use the upstream NVCF guidance when autoscaling is requested. Do not promise capacity beyond the function's minimum instance count until scaling behavior is configured and validated.

Build and validate the viewer image using nvcf-viewer-container-contract.md, then let the upstream workflow provision the selected platform and register the streaming function. Require both platform readiness and decoded browser frames through the resolved endpoint before reporting the deployment ready.

For an explicitly requested existing-stack upgrade, use upstream streaming-inplace-upgrade-orchestrator and its component skills; that migration workflow is not a prerequisite for a fresh build.

Upstream platform support does not establish that Kit-specific cache settings or browser profiles apply to a standalone OVRTX viewer. Confirm the generated viewer's integration contract through the upstream workflow.

Fresh Kubernetes Bring-Up Checkpoints

Use these checkpoints to organize the generated project's runbook. Execute the platform phases through the upstream orchestration skill and its child skills; these checkpoints do not replace their commands or readiness gates.

Record the integration before writing code. Capture the chosen public release and compatibility sources, upstream checkout revision, selected provider/component skills, browser connection profile, signaling route, credential source, lifecycle contract, and expected validation evidence. Resolve dependencies through ../dependencies/README.md; do not combine individually newest components without checking compatibility. Record access prerequisites and unavailable artifacts explicitly rather than substituting private builds or declaring the whole platform unavailable.
Establish Kubernetes capabilities. Let the selected upstream provider skill verify GPU and encoder support, CNI, storage, registry trust/pulls, ingress/load balancing, and external media exposure. A raw VM running Kubernetes, including one hosted by Brev, follows the upstream generic Kubernetes provider path rather than inheriting managed EKS/AKS capabilities. Discover existing access and cluster state before provisioning replacements.
Bring up the platform in upstream order. Follow prerequisites, control and compute planes, LLS, and the workload-required services selected by the orchestrator. Save sanitized evidence at each gate. A healthy node alone does not establish registered, schedulable NVCF GPU capacity; use the upstream capacity checks before registering/deploying the viewer function.
Prove minimal video through NVCF first. Use a small OVRTX-rendered scene and the container contract below. Resolve the browser profile from upstream NVCF guidance and the released browser SDK's NVCF documentation/examples; the standalone Direct example is not an NVCF template. Validate the real signaling proxy, session credentials, and external media route with advancing decoded frames before adding the full viewer UI. Keep frontend/proxy changes independently deployable where practical so browser configuration fixes do not require rebuilding the GPU image and repeating renderer warmup.
Prove session recovery before expanding the app. Follow nvcf-viewer-container-contract.md for disconnect/resume, expiry, callback acknowledgement, and a stable fresh worker. Then validate viewer interaction and scene switching through the same deployed endpoint.

Keep four results distinct in the runbook: renderer ready, platform/function ready, browser decoding video, and a fresh session available after cleanup. Report the last completed checkpoint and its evidence when any later gate fails.

Boundary

Upstream owns cloud infrastructure, NVCF control and compute planes, media routing, caches, deployed storage services, and readiness gates.
This package owns the generated viewer application: OVRTX and OVStage runtime behavior, the selected viewer transport, UI, and app-level validation.
Standalone ovstream on Brev and OKAS remain alternatives in cloud-deployment/README.md. NVCF on a Brev-hosted Kubernetes cluster follows this handoff.

Do not assume a standalone ovstream Direct browser configuration applies to an NVCF deployment. Follow the upstream workflow to select and validate the exposed media and browser connection model.

Before handing an image to the upstream workflow, read nvcf-viewer-container-contract.md, gpu-container-runtime.md, and webrtc-network-diagnostics.md. These references cover only the application boundary and validation evidence; they do not replace the upstream deployment skills.

Return Contract

After the upstream workflow reaches its deployment and readiness gates, return to the selected viewer references with:

the resolved viewer endpoint and connection model;
deployment readiness status and the upstream validation evidence;
any viewer-container requirements that affect the generated app; and
sanitized app-level stream, input, reconnect, and shutdown evidence.

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

2026-11-09

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/cloud-deployment/nvcf-self-hosted.md

NVCF Self-Hosted Handoff

Triggers

Upstream Source Of Truth

Build A New Deployment

Fresh Kubernetes Bring-Up Checkpoints

Boundary

Return Contract

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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