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Omniverse Realtime Viewer

OpenAIOfficialCreated by NVIDIA OmniverseDistributed by OpenAI

  • Skill
  • Meta (authoring, orchestration, planning, memory)
  • Software development
  • Apache-2.0
  • Medium risk
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From the author

Use as the top-level router for Omniverse Realtime Viewer USD app requests 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 orchestrator for developing USD-based viewer applications. It provides a structured approach to selecting implementation recipes, enforcing architectural conventions, and managing dependencies. By utilizing a set of focused reference documents, it guides developers through the lifecycle of building, configuring, and validating viewer applications, ensuring consistent behavior across different delivery paths such as local workstations or streaming environments.

What it does

  • Routes development requests to specific implementation recipes based on the target delivery path.
  • Enforces architectural rules for USD rendering, stage management, and UI integration.
  • Provides guidance on camera selection, input handling, and viewport interaction.
  • Standardizes the integration of AOV switching and render product configuration.
  • Facilitates the capture of validation evidence for viewer readiness.
  • Maintains separation between user-provided USD files and application-specific session state.

When to use it

  • When initiating the development of a new USD viewer application within the Omniverse ecosystem.
  • When determining the appropriate delivery path for a viewer, such as local native or streaming.
  • When needing to implement consistent camera, selection, or UI behavior across viewer projects.
  • When integrating advanced rendering features like AOV switching into an existing viewer.

Advantages

  • Ensures architectural consistency across diverse viewer implementations.
  • Provides a clear, modular path for adding specific capabilities like input routing or data display.
  • Promotes clean separation of concerns between stage data and viewer-owned state.
  • Standardizes the validation process for consistent delivery.

Usage examples

“I need to build a browser-based viewer for USD files.”
The agent will route you to the streaming viewer recipe, providing guidance on WebRTC stream setup, UI integration, and viewport interaction.
“How do I implement AOV switching in my local USD viewer?”
The agent will provide the AOV switching reference, detailing how to map render vars and update the display state on the server.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/openai/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

This is the top-level entry point for the Omniverse Realtime Viewer skill package. It is self-contained: all required routing, conventions, and validation guidance live in the selected references.

Use the focused reference documents as implementation recipes. This file chooses the right recipes and preserves the architectural rules that must hold across all generated viewer apps.

Instructions

Start by classifying the requested viewer, then read only the references needed for that delivery path and feature set. Implement the render path first, layer interaction and UI behavior on top of it, and finish by capturing validation evidence from references/validation.md.

Read Order

  1. Read references/routing.md to choose the delivery path and focused references.

  2. Read references/conventions.md before implementing camera, input, selection, viewport, streaming protocol, scene loading, or environment behavior.

  3. For broad viewer requests, read references/usd-viewer-app/README.md.

  4. If the delivery path is unclear, read references/streaming-vs-local/README.md.

  5. If the prompt includes layout, panels, controls, inspectors, status, or UX, read references/viewer-ux-workflow/README.md and then the focused viewer UI references. This applies to React/WebRTC, Tauri, Electron, ovui, ovwidgets, and Dear ImGui apps; "frontend" means user-facing UI, not only browser UI.

  6. For viewport interaction, read references/viewer-input-routing/README.md before references/camera-controls/README.md, references/native-picking-selection/README.md, or references/object-selection/README.md.

  7. Read only the focused capability references needed for the requested app.

  8. Use references/validation.md to capture review evidence before handoff.

Non-Negotiables

  • Use ovrtx for all USD and 3D rendering.

  • Browser apps display an ovstream WebRTC video stream plus UI. The browser does not render USD geometry.

  • Do not substitute WebGL, Three.js, Babylon.js, PlayCanvas, A-Frame, model-viewer, react-three-fiber, glTF browser viewers, or other client-side 3D renderers.

  • If local validation cannot run because the GPU/runtime environment is absent, scaffold the ovrtx path and document the runtime requirement. Do not add a browser-renderer fallback.

  • Keep user USD files unmodified. Viewer cameras, render products, render vars, settings, selection metadata, and runtime state belong in session/composite layers or app state.

  • Keep one owner for renderer.step(), stage mutation, native picking, selection writes, and live attribute writes.

  • Keep dependency acquisition in references/dependencies/README.md and deployment choices in references/cloud-deployment/README.md; do not duplicate package locations or deployment setup.

Focused Reference Families

  • Entry points and recipes: references/usd-viewer-app/README.md, references/streaming-viewer-recipe/README.md, references/ovui-local-viewer-recipe/README.md, references/streaming-vs-local/README.md, references/electron-shm-viewer/README.md, references/ovwidgets-editor-shell/README.md.

  • Rendering and stage: references/ovrtx-rendering/README.md, references/stage-loading/README.md, references/stage-management/README.md, references/render-settings/README.md, references/aov-switching/README.md, references/stage-hierarchy/README.md, references/stage-queries/README.md, references/stage-attribute-reads/README.md, references/prim-transform-safety/README.md, references/usd-sample-data/README.md.

  • Delivery and runtime: references/streaming-server/README.md, references/streaming-client/README.md, references/streaming-messages/README.md, references/streaming-lifecycle/README.md, references/local-viewer/README.md, references/tauri-local-viewer/README.md, references/cpp-native-viewer/README.md, references/headless-shm-cli/README.md, references/viewer-backend-interface/README.md, references/webgl-shm-transport/README.md.

  • Viewer UI/UX: references/viewer-ux-workflow/README.md, references/viewer-layout-patterns/README.md, references/viewer-control-patterns/README.md, references/viewer-data-view-patterns/README.md, references/viewer-feedback-status/README.md.

  • Interaction: references/viewer-input-routing/README.md, references/camera-controls/README.md, references/object-selection/README.md, references/native-picking-selection/README.md, references/selection-feedback/README.md, references/selection-animation/README.md, references/transform-manipulator/README.md, references/gl-viewport-overlay/README.md, references/ovui-library/README.md, references/prim-pick-effects/README.md, references/prim-info-display/README.md, references/viewport-overlays/README.md.

  • Infrastructure: references/dependencies/README.md, references/windows-native-setup/README.md, references/cloud-assets/README.md, references/cloud-deployment/README.md, references/troubleshooting/README.md.

Build Workflow

  1. Classify the prompt by delivery path, target user, required capabilities, runtime environment, validation needs, and explicit constraints.

  2. Select a small reference set. Start with the recipe or routing reference, then add focused capabilities such as camera, picking, hierarchy, properties, render settings, transform tools, cloud assets, or deployment.

  3. Read selected references before writing app code. Follow their build order, import order, data-channel contracts, and renderer ownership rules.

  4. Implement the core render path first, then input routing and camera, then selection and data panels, then scene/settings features, then packaging or deployment.

  5. Treat the selected references as the behavior contract for API shape, compatibility, and generated project structure.

  6. Capture validation evidence before calling the viewer ready.

Examples

  • For a browser viewer request, use the streaming recipe references plus camera, picking, hierarchy, properties, render settings, and stream-status references.

  • For a local workstation viewer request, use the local or native delivery references plus renderer setup, stage loading, viewport input, and validation.

Completion Checklist

  • Selected references match the user's intent and delivery path.

  • No code path uses a browser-side 3D renderer for USD.

  • The generated app has one clear owner for render stepping and stage mutation.

  • User USD files remain untouched by viewer-owned session data.

  • Camera, input, selection, scene loading, and stream behavior follow references/conventions.md.

  • Setup/build/run results and visual interaction evidence are captured with references/validation.md.

Files

references/selection-animation/README.md

Selection Animation

Triggers

Use this skill for selection animation, prim animation, hover animation, float selected object, animate selected, omni:xform animation, map_attribute, AttributeMapping, or transform not updating.

Use this when selected prims need optional renderer-visible motion feedback. It writes live omni:xform transforms to ovrtx without changing the source USD.

Key Rules

  • Attribute: omni:xform, not xformOp:transform or xformOp:translate.

  • Semantic: Semantic.XFORM_MAT4x4.

  • PrimMode: PrimMode.CREATE_NEW.

  • Matrix: float64, row-major, translation in row 3.

  • Call animator.update(dt) before renderer.step().

  • Bind attributes once at stage load and reuse the AttributeBinding handles. Use binding.map(), binding.write(), or renderer.map_attribute() for frame updates; do not recreate bindings every frame.

  • Preserve base transforms by reading them once and composing offsets with them.

  • Selection animation is driven by selected prim paths. It does not depend on EffectLayer materials, material maps, or segmentation IDs. Those belong to selection feedback, not motion.

  • Motion parameters are application choices. Derive direction, magnitude, duration, and easing from the product brief, stage units, asset scale, and active coordinate system.

State Machine

IDLE -> RISING -> HOVERING -> FALLING -> IDLE

Use a small state machine so selection and deselection are reversible. The specific motion can be lift, pulse, nudge, scale, or another non-destructive transform chosen by the app. The example below uses a configurable translation offset; replace its values for the target product.

ANIMATION = {
    "direction": np.array([0.0, 1.0, 0.0], dtype=np.float64),  # app-defined
    "distance": 0.05,      # stage units; choose from asset scale/bounds
    "oscillation": 0.0,    # optional additional stage-unit offset
    "frequency_hz": 1.5,
    "rise_seconds": 0.25,
    "fall_seconds": 0.25,
}

def ease_out_quint(t): return 1.0 - (1.0 - t) ** 5
def ease_in_out_sine(t): return -(math.cos(math.pi * t) - 1) / 2

Animator Construction

Initialize Warp once before constructing GPU/attribute helpers. Build fresh bindings after every scene switch.

import warp as wp
wp.init()

world_transforms = {}
for path in pickable_paths:
    prim = stage.GetPrimAtPath(path)
    if prim and prim.IsValid():
        m = UsdGeom.Xformable(prim).ComputeLocalToWorldTransform(Usd.TimeCode.Default())
        base = np.array(m, dtype=np.float64).reshape(4, 4)
        if np.isfinite(base).all():
            world_transforms[path] = base
animator = PrimAnimator(renderer, list(world_transforms), world_transforms)

Binding And Write Pattern

Pre-bind omni:xform attributes when the stage loads, then reuse the bindings. Use one batched binding when the animated set is stable; use a path-to-binding map when the selectable set changes frequently.

import numpy as np
import warp as wp
from ovrtx import BindingFlag, Device, PrimMode, Semantic

binding = renderer.bind_attribute(
    prim_paths=prim_paths,
    attribute_name="omni:xform",
    dtype="float64",
    shape=(4, 4),
    semantic=Semantic.XFORM_MAT4x4,
    prim_mode=PrimMode.CREATE_NEW,
    flags=BindingFlag.OPTIMIZE,
)

Immediately initialize the new live attribute from saved world transforms before any render step. CREATE_NEW can otherwise initialize omni:xform to identity.

initial = np.stack([base_xforms[path] for path in prim_paths]).astype(np.float64)
binding.write(initial)

Each frame, compose the saved base transform with the app-defined transform offset and write through the persistent binding:

def compose_offset_xforms(
    prim_paths: list[str],
    offsets: dict[str, np.ndarray],
) -> np.ndarray:
    out = np.empty((len(prim_paths), 4, 4), dtype=np.float64)
    for i, path in enumerate(prim_paths):
        base = base_xforms[path]
        offset = offsets.get(path)
        offset_mat = np.eye(4, dtype=np.float64)
        if offset is not None:
            offset_mat[3, 0:3] = offset
        out[i] = base @ offset_mat
    return out

def write_offsets_cpu(offsets: dict[str, np.ndarray]) -> None:
    xforms = compose_offset_xforms(prim_paths, offsets)
    binding.write(xforms)

For direct mapped writes, consume the mapped DLPack tensor with NumPy, Warp, or another DLPack-compatible library:

def write_offsets_mapped(offsets: dict[str, np.ndarray]) -> None:
    xforms = compose_offset_xforms(prim_paths, offsets)
    with binding.map(device=Device.CPU) as mapping:
        np.from_dlpack(mapping.tensor)[:] = xforms

ovrtx 0.3 Mapping And Async Writes

Renderer.write_attribute(), AttributeBinding.write(), and async variants accept CPU or GPU DLPack tensors. DataAccess.SYNC copies input immediately. DataAccess.ASYNC references the caller's buffer until the operation completes, so keep the source tensor alive and provide CUDA stream/event synchronization when writing GPU data.

from ovrtx import DataAccess

gpu_xforms = build_gpu_xform_tensor()  # Warp/CuPy/PyTorch object with __dlpack__()
op = binding.write_async(
    gpu_xforms,
    data_access=DataAccess.ASYNC,
    cuda_stream=cuda_stream_handle,
)
op.wait()

Use renderer.map_attribute() for by-name mapped writes when you do not need a long-lived binding object, or when a helper owns a short update batch:

mapping = renderer.map_attribute(
    prim_paths,
    "omni:xform",
    dtype="float64",
    shape=(4, 4),
    semantic=Semantic.XFORM_MAT4x4,
    device=Device.CPU,
    prim_mode=PrimMode.CREATE_NEW,
)
np.from_dlpack(mapping.tensor)[:] = compose_offset_xforms(prim_paths, offsets)
mapping.unmap()

For CUDA mapped writes, launch kernels into the mapped tensor and commit with explicit stream or event sync:

mapping = renderer.map_attribute(
    prim_paths,
    "omni:xform",
    dtype="float64",
    shape=(4, 4),
    semantic=Semantic.XFORM_MAT4x4,
    device=Device.CUDA,
    device_id=0,
    prim_mode=PrimMode.CREATE_NEW,
)
mapped_xforms = wp.from_dlpack(mapping.tensor)
# `cuda_stream_handle` must identify the same CUDA stream used by `wp_stream`.
wp.launch(
    fill_offset_xforms_kernel,
    dim=len(prim_paths),
    inputs=[mapped_xforms],
    device="cuda:0",
    stream=wp_stream,
)
unmap_op = mapping.unmap_async(stream=cuda_stream_handle)
unmap_op.wait()

AttributeMapping.unmap_async() marks the mapping as unmapped immediately and returns an operation for caller-managed completion. Wait before renderer.step() if the next frame must show the new transform.

Per-Path Binding Alternative

If the selected set is sparse and changes often, store one binding per path and keep those handles alive until the scene reloads:

bindings = {
    path: renderer.bind_attribute(
        prim_paths=[path],
        attribute_name="omni:xform",
        dtype="float64",
        shape=(4, 4),
        semantic=Semantic.XFORM_MAT4x4,
        prim_mode=PrimMode.CREATE_NEW,
    )
    for path in prim_paths
}

def _write_offset(path: str, offset: np.ndarray):
    bind = bindings.get(path)
    base = base_xforms.get(path)
    if bind is None or base is None:
        return
    offset_mat = np.eye(4, dtype=np.float64)
    offset_mat[3, 0:3] = offset
    mat = base @ offset_mat
    with bind.map(device=Device.CPU) as mapping:
        np.from_dlpack(mapping.tensor).reshape(1, 4, 4)[0] = mat

Frame Loop

now = time.monotonic()
dt = max(1.0 / 300.0, min(0.1, now - last_step))
last_step = now
if animator is not None:
    animator.update(dt)
products = renderer.step(render_products={RENDER_PRODUCT_PATH}, delta_time=dt)

Updating after step() renders the previous transform and makes animation lag or appear stuck.

Selection Lifecycle

def select_prim(path: str):
    if animator is not None:
        animator.deselect_all()
        animator.select(path)

def clear_selection():
    if animator is not None:
        animator.deselect_all()

Native picking, tree selection, marquee selection, or scripted selection can all call the same animation methods after they resolve selected prim paths. Native selection outlines and EffectLayer/material effects should be updated by their own managers in parallel.

On rapid select/deselect, record the current offset so falling reverses smoothly from the current transform state.

Generated Module Checklist - prim_animation.py

  • [ ] PrimAnimator.__init__(renderer, prim_paths, base_transforms)

  • [ ] PrimAnimator.select(path: str) -> None

  • [ ] PrimAnimator.deselect(path: str) -> None

  • [ ] PrimAnimator.deselect_all() -> None

  • [ ] PrimAnimator.update(dt: float) -> None

  • [ ] PrimAnimator.current_offset(path: str) -> np.ndarray

  • [ ] PrimAnimator.freeze(path: str) -> None and PrimAnimator.resume(path: str) -> None when transform tools can edit animated prims.

  • [ ] Base transforms are loaded before binding, using the app's transform-safe query path such as pxr_worker.get_world_transforms(paths) when native live attributes are not enough.

  • [ ] Attribute bindings are created once for omni:xform with PrimMode.CREATE_NEW.

  • [ ] Newly-created omni:xform attributes are initialized from base transforms before the first render step.

  • [ ] Writes use Semantic.XFORM_MAT4x4 semantics when calling write_attribute, bind_attribute, or map_attribute.

  • [ ] CPU writes use NumPy/DLPack with DataAccess.SYNC or mapped context managers.

  • [ ] GPU writes use DLPack tensors plus DataAccess.ASYNC and CUDA stream/event synchronization.

  • [ ] AttributeMapping.unmap_async() operations are waited before the next frame when the frame depends on them.

  • [ ] Falling state restores the saved base transform when complete.

See also: object-selection, selection-feedback, prim-transform-safety, stage-management, ovrtx-rendering.

Requirements and compatibility

Written for: OpenAI Codex

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.

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
OpenAI (Official)
Distributed by
OpenAI
Source
openai/plugins · plugins/nvidia/skills/omniverse-realtime-viewer · commit d420d13
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (written by AutoGineer)
  • ATTRIBUTION.md (written by AutoGineer)
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