Agent skill · data analytics · nvidia
omniverse-usd-performance-tuning
Diagnose and optimize USD stages for slow loading, high memory, low FPS or validation; preserve asset boundaries and reuse shared definitions.
Why this skill is useful
Provides domain-specific knowledge and workflows for diagnosing and optimizing USD performance that the AI wouldn't reliably generate on its own.
What it needs
Requires omniverse installed locally. About 5k tokens when loaded. Last updated 2026-08-07. 2,816 stars on the source repository.
What this skill does
Omniverse USD Performance Tuning Purpose Improve loading, memory use or rendering for the requested workload. Preserve the prim paths, appearance, placement and behavior required by downstream applications. Follow the component/subcomponent model in NVIDIA's Factory-Level USD Structuring guide. Apply the relevant parts of that model; a static asset does not need new animation or physics. Inputs Required: the source USD stage. When no workload is specified, use factory layout planning and visualization and record that assumption in the request/report. Explicit workload and preservation requirements take precedence. Optional: an output workspace, preservation requirements, physical error budget, existing library indexes and recorded runtime evidence. Use values from the current user request; reuse recorded values only while they remain applicable. Follow setup when no output path is supplied. Prerequisites Verify the selected runtime and required capabilities using setup. Keep its preflight record with the run; installation and remote access are conditional steps described there. Instructions 1. Inspect. Establish the workload, preservation requirements and output workspace. Set up progress and dashboard access before assessment. Verify setup and inspect the selected source configuration. 2. Judge boundaries. Review equipment, service-system sections and architectural elements in the selected configuration, including animation and interiors. Record owners, editable interfaces, equipment categories and optional families using boundary guidance. 3. Classify and author. Classify accepted assets children before parents. Capture or reuse the original profile before authoring. Prepare reusable definitions, materials and occurrence opinions using asset authoring. 4. Optimize unique definitions. Run supported native operations concurrently on disjoint scopes with the recorded physical budget. 5. Publish semantic libraries. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/omniverse-usd-performance-tuning