AutoGineer
Generated banner for Omniverse Realtime Viewer
Generated logo for Omniverse Realtime Viewer

Omniverse Realtime Viewer

NVIDIAOfficialCreated by NVIDIA Omniverse

  • Skill
  • Tool integration
  • Software development
  • Apache-2.0
  • Medium risk
Download ZIP

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://mp-staging.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/navigation-presets/preset-camera-ops.md

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

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

Preset Camera Operations

These operations extend the shared camera state and matrix/commit rules in camera-controls. Use radians, render-pixel coordinates after letterbox mapping, camera.world_up, MAX_ELEVATION, and MIN_DISTANCE from that reference. Run sanitize_camera before input and matrix generation.

The snippets use application helpers, not SDK APIs: eye(cam) returns the current world-space eye, eye_offset(cam) is (eye - target) / distance, and camera_basis(cam) returns (right, up, forward) using the row-major camera basis in camera-controls. orbit updates the shared angles and clamps elevation. Commit the resulting pose through the runtime camera adapter.

Cursor-locked pan and zoom

On a plane through the target perpendicular to the view, one pixel maps to:

def units_per_pixel(cam, fov_y_rad, render_h):
    return 2.0 * cam.distance * math.tan(fov_y_rad * 0.5) / max(1, render_h)

def pan_locked(cam, dx, dy, fov_y_rad, render_h):
    upp = units_per_pixel(cam, fov_y_rad, render_h)
    right, up = camera_basis(cam)[:2]
    cam.target = cam.target - right * (dx * upp) + up * (dy * upp)

Do not multiply the horizontal factor by aspect ratio; square pixels use the same world-units-per-pixel scale in both directions.

For zoom toward a cursor, compute the target-plane point p under the cursor, then scale both the target offset and camera distance by the same factor:

def zoom_at_cursor(cam, notches, px, py, fov_y_rad, render_w, render_h,
                   per_notch=0.90):
    n = max(-6.0, min(6.0, float(notches)))
    new_distance = max(MIN_DISTANCE, cam.distance * (per_notch ** n))
    f = new_distance / cam.distance
    p = point_at_target_plane(cam, px, py, fov_y_rad, render_w, render_h)
    cam.target = p + (cam.target - p) * f
    cam.distance = new_distance

point_at_target_plane intersects the cursor ray with the plane through the target. The shared camera basis supplies right, up, and forward; screen Y must be inverted when creating the ray. The construction preserves the cursor point because the new eye is p + f * (old_eye - p).

For a perspective camera, implement the target-plane helper as follows:

def point_at_target_plane(cam, px, py, fov_y_rad, render_w, render_h):
    right, up, forward = camera_basis(cam)
    half_h = cam.distance * math.tan(fov_y_rad * 0.5)
    x = (2.0 * px / render_w - 1.0) * half_h * render_w / render_h
    y = (1.0 - 2.0 * py / render_h) * half_h
    return cam.target + right * x + up * y

Require positive render dimensions. These formulas assume perspective projection; orthographic navigation uses aperture-based scaling instead.

Eye-fixed look and focus

For first-person look, capture the eye before changing azimuth/elevation, then re-pivot the target to that same eye:

def look(cam, dx, dy, sens_rad_per_px=0.0045):
    e = eye(cam)
    orbit(cam, dx, dy, sens_rad_per_px)
    cam.target = e - cam.distance * eye_offset(cam)

Double-click focus can set a new target to a picked point while retaining the eye. Prefer native pick depth when the delivery path provides it; otherwise use the target-plane approximation. Do not intersect a sphere centered on the target—the eye is already on that sphere and the near root is zero.

Axis views and fly

Blender-style views set azimuth/elevation directly, using the existing elevation clamp: front (0, 0), back (pi, 0), right (pi/2, 0), left (-pi/2, 0), and top/bottom (0, +/-MAX_ELEVATION). These angle labels assume the controller's matching front-axis convention; map named views to the active stage up-axis and application front direction. Step-orbit keys use pi/12. If axis snapping is added, latch it once per gesture after a clear movement threshold and release the latch with the gesture.

Fly movement is frame-rate independent and gravity-aligned:

def fly_move(cam, held, speed, dt):
    right, up, fwd = camera_basis(cam)
    w_up = cam.world_up
    fwd_h = fwd - np.dot(fwd, w_up) * w_up
    right_h = right - np.dot(right, w_up) * w_up
    if np.linalg.norm(fwd_h) > 1e-3: fwd_h /= np.linalg.norm(fwd_h)
    if np.linalg.norm(right_h) > 1e-3: right_h /= np.linalg.norm(right_h)
    move = (fwd_h * (('w' in held) - ('s' in held))
            + right_h * (('d' in held) - ('a' in held))
            + w_up * (('e' in held) - ('q' in held)))
    length = np.linalg.norm(move)
    if length < 1e-6: return False
    cam.target += move / length * (speed * dt)
    return True

def fly_speed(state, notches):
    n = max(-6.0, min(6.0, float(notches)))
    state.speed = min(1e6, max(1e-3, state.speed * (1.25 ** n)))

Initialize speed relative to the fitted scene, for example 0.1 * distance, and apply any boost as a documented multiplier. Clear the held-key set on focus loss, disconnect, viewport deactivation, and preset switch.

Tests should assert cursor fixed points and eye preservation to numerical tolerance, exact speed * dt displacement for a single axis, and zero world-up component for planar fly motion.

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

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

Download ZIP

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