Omniverse Usd Performance Tuning

NVIDIAOfficialCreated by NVIDIA Omniverse

Skill
Workflow
Software development
Apache-2.0
Medium risk
Has scripts

From the author

Diagnose and optimize USD stages for slow loading, high memory, low FPS or validation; preserve asset boundaries and reuse shared definitions.

— the description by NVIDIA Omniverse

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for diagnosing and optimizing USD stages. It focuses on improving performance metrics like load times, memory footprint, and frame rates by identifying and optimizing unique asset definitions, reusing shared definitions, and pruning unnecessary data. The process emphasizes preserving original asset boundaries, animation, and interface requirements, ensuring that downstream applications remain functional after optimization.

What it does

Inspects USD stages to identify performance bottlenecks and structural inefficiencies.
Classifies assets into atomic, package, or aggregate structures to guide optimization.
Performs native USD optimization operations on disjoint scopes.
Publishes semantic libraries to enable efficient asset reuse.
Validates composition, ownership, and interface accessibility of the optimized output.
Profiles the final output against the original baseline to report measured improvements.

When to use it

When a USD stage suffers from slow loading times or high memory consumption.
When rendering performance (FPS) needs improvement in a production environment.
Before finalizing a USD assembly for downstream consumption.
When you need to standardize asset structures according to factory-level guidelines.

Advantages

Maintains asset boundaries and critical metadata during optimization.
Reduces scene complexity through intelligent reuse of shared definitions.
Provides verifiable reports on performance gains and composition integrity.
Supports large-scale scene optimization by processing independent definition scopes.

Usage examples

“Inspect the USD stage at /data/factory.usdc for performance issues and prepare a review workspace.”: The agent initializes the workspace, runs the inspection script, and provides a summary of candidates for optimization.
“Submit the optimization decisions for the factory stage based on the generated JSON.”: The agent processes the boundary decisions, executes the optimization operations, and generates the final optimized USD assembly.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/nvidia/omniverse-usd-performance-tuning/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip omniverse-usd-performance-tuning.zip -d .agents/skills

Documentation by NVIDIA Omniverse

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

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.
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.
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.
Optimize unique definitions. Run supported native operations concurrently on disjoint scopes with the recorded physical budget.
Publish semantic libraries. Use one writer per category layer and remap consumer references.
Check composition. Check authored ownership, references, bindings, placement, animation and interface accessibility through the written-output checks.
Profile and report. Compare the final consumer with the original baseline under comparable conditions and report measured benefits, completion and operations by asset definition.

sequenceDiagram
    participant A as Agent
    participant T as USD tools
    participant W as Definition workers
    participant L as Library publisher
    participant D as Read-only progress dashboard
    Note over A,L: One compact progress state also renders text progress
    T-->>D: Recorded phase, assessment rounds, counters and decision reasons
    A->>T: Inspect original selected configuration
    T->>T: Collect cached child-to-parent summaries and repetition nominations
    T->>T: Load supplied indexes once and batch authored product clues
    T-->>A: Product review groups, member context, animation and reuse evidence
    loop Until boundaries and interiors are reviewed
        A->>A: Select asset boundaries, then identify required internal prims and properties
        A->>T: Submit boundary decisions with reviewed scope, required edits, category and optional family
        T->>T: Reuse unchanged source evidence, recompute boundary-dependent results
        opt Geometry ownership requires reconstruction
            T->>T: Regroup or native split, remap paths and reassess affected regions
        end
        T-->>A: Remaining candidates and member exceptions
    end
    T->>T: Classify selected child assets before parent assets, confirm reuse
    T->>T: Capture or reuse original baseline profile
    T->>T: Confirm accepted product identities from source and supplied indexes; reconcile complete parent-child groups
    T->>T: Skip worker inputs for confirmed groups; author remaining materials, editable prims and occurrence overrides
    T->>T: Determine merge groups on prepared interiors; preserve selected child assets and required prims
    T->>W: Read-only input USD layers for existing-library matching
    par Independent preparation jobs
        W->>W: Confirm remaining product, exact source or authorized normalized reuse; preserve occurrence placement
        W->>W: Consolidate accepted product or compatible exact/normalized leaf inputs; retain every occurrence
    end
    W-->>T: Confirmed library hits and definitions requiring optimization
    T->>W: Owned geometry prim paths in read-only input layers
    par Independent definition scopes
        W->>W: Remove small meshes when authorized; apply asset representation: reserve merge inputs or fit analytic prims; reduce, merge (native clustering if required), prune, flatten, prune
    end
    W->>L: Geometry outputs and assembly authoring outcomes
    L->>L: Share eligible static whole definitions within current category publication
    L->>L: Share remaining whole meshes; write USD reuse metadata and compact index
    L->>T: Output USD stage with rewritten references and dependencies
    T->>T: Check authored composition, ownership, animation and interfaces
    T->>T: Profile final output USD stage and report results by asset definition
    T-->>A: Measured changes, coverage and unresolved work
    T-->>D: Final verdict and report/library paths

Use the provided tools for traversal, native operations, authoring and checks; the agent supplies engineering judgments. Preserve current variant selections, authored animation, required materials and interfaces. Trust supported USD Optimize operations with valid settings and scopes. Deep geometric comparisons and whole-scene edit trials belong in development tests, not ordinary execution.

Complete when every unique definition has an executed or evidenced unchanged outcome, every asset has justified ownership and structure, and the written consumer passes composition checks. Retain native failures, unresolved judgments and missing required capabilities as incomplete work. Repeat only affected work when evidence changes.

Scope and authorization

Diagnosis and validation requests remain read-only. An optimization request authorizes work in a separate output workspace within its stated preservation limits.
Never overwrite source layers or inherited libraries without explicit authorization.
Reuse authorization already given. Ask only for a missing decision that changes identity, required appearance or a loss budget; explain the affected component and consequence.
Report only observed changes. Measure rendering before claiming higher FPS or lower GPU use.

Load only the relevant guidance

Request	Read
Validation only	Setup, then the validation section of operations
Approved operation chain	Setup, operations, verification
Existing or persistent asset library	Add the library index requirements to the assessment
Missing standalone runtime	Installation
Remote stage	Remote access before the first open
Report from completed evidence	Verification

Use upstream package guidance for selected operation mechanics and proxy workflows. Keep large logs on disk as specified in setup.

Limitations

Convert CAD input with the source converter's workflow and NVIDIA's CAD conversion guidance. Render profiling requires NVIDIA/omniperf or the user's available profiler; USD open and traversal timings alone do not establish rendering improvements.

Troubleshooting

For unavailable imports, operations or remote assets, follow setup. For incomplete execution or failed composition checks, follow verification; retain the failed artifacts and report the missing capability or failed check.

Examples

After runtime preflight, use the verified Python interpreter from setup to inspect a stage:

python scripts/successor_assessment.py inspect --source /data/factory.usdc --workspace /data/factory-review

Review the generated candidates using boundary guidance, fill the generated decision template, then submit it:

python scripts/successor_assessment.py decide --workspace /data/factory-review --decisions /data/factory-review/decisions.json

These commands perform assessment; continue through the instructions above only when review is complete. Run from the skill directory; generated data stays in the workspace.

Output Format

Maintain live progress and editable steering throughout execution.

For end-to-end optimization, provide the written USD assembly, validated report JSON, and generated Markdown and HTML reports. State the runtime, operations actually executed, preservation and coverage results, measured changes, source-write status, and artifact paths. Diagnosis-only work may return a findings summary stating that no optimized stage was written.

Files

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CHANGELOG.md2.4 KiB
LICENSELicence file added by AutoGineer11.2 KiB
SKILL.md10.2 KiB
agents/openai.yaml375 B
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evals/files/completed-run/after.usda399 B
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references/usd-structure-assessment/scripts/usd-structure-assessment-report.schema.json

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "$id": "usd-structure-assessment-report.schema.json",
  "title": "USD Structure Assessment Report",
  "description": "Umbrella schema for the usd-structure-assessment output. Routing-critical objects (summary_counts, validation_scope) are strict; structural reasoning objects (composition, instancing) are permissive to allow agent creativity.",
  "type": "object",
  "required": [
    "stage",
    "asset_physical_context",
    "summary_counts",
    "composition",
    "instancing",
    "hierarchy_dedupe",
    "validation_scope",
    "phase_recommendation"
  ],
  "additionalProperties": true,
  "properties": {
    "schemaVersion": {
      "type": "string",
      "description": "Schema version for forward compatibility"
    },
    "stage": {
      "type": "object",
      "description": "Stage identity and physical context metadata. metersPerUnit and upAxis are required so downstream tolerance-based operations can derive parameters without re-opening the stage.",
      "required": [
        "identifier",
        "rootLayer",
        "metersPerUnit",
        "upAxis"
      ],
      "additionalProperties": true,
      "properties": {
        "identifier": {
          "type": "string"
        },
        "rootLayer": {
          "type": "string"
        },
        "defaultPrim": {
          "type": "string"
        },
        "upAxis": {
          "type": "string",
          "enum": [
            "X",
            "Y",
            "Z"
          ]
        },
        "metersPerUnit": {
          "type": "number",
          "exclusiveMinimum": 0
        },
        "scale_hint": {
          "type": "string",
          "enum": [
            "meters",
            "centimeters",
            "millimeters",
            "other"
          ],
          "description": "Human-readable label derived from metersPerUnit (1.0=meters, 0.01=centimeters, 0.001=millimeters) for downstream branching"
        }
      }
    },
    "asset_physical_context": {
      "type": "object",
      "description": "Physical scale context for tolerance-based operations. Written during SA from stage metadata and prim-type traversal only \u2014 no geometry arrays read. metersPerUnit and upAxis are free stage metadata. mesh_count is a prim-type count (no geometry load).",
      "required": [
        "metersPerUnit",
        "upAxis"
      ],
      "additionalProperties": true,
      "properties": {
        "metersPerUnit": {
          "type": "number",
          "exclusiveMinimum": 0,
          "description": "Duplicated from stage for self-contained downstream consumption"
        },
        "upAxis": {
          "type": "string",
          "enum": [
            "X",
            "Y",
            "Z"
          ]
        },
        "scale_hint": {
          "type": "string",
          "enum": [
            "meters",
            "centimeters",
            "millimeters",
            "other"
          ],
          "description": "Human-readable scale label for agent prompts"
        },
        "mesh_count": {
          "type": "integer",
          "description": "Total meshes from prim-type traversal (no geometry arrays needed). Copied from summary_counts for self-contained downstream use."
        }
      }
    },
    "summary_counts": {
      "type": "object",
      "description": "Routing-critical counts consumed by usd-validation-runner policy and restructure-decision. Strict: typos rejected.",
      "required": [
        "prim_count",
        "mesh_count",
        "material_count",
        "prototype_count",
        "instance_count",
        "reference_count",
        "payload_count"
      ],
      "additionalProperties": false,
      "properties": {
        "prim_count": {
          "type": "integer"
        },
        "mesh_count": {
          "type": "integer"
        },
        "material_count": {
          "type": "integer"
        },
        "prototype_count": {
          "type": "integer"
        },
        "instance_count": {
          "type": "integer"
        },
        "reference_count": {
          "type": "integer",
          "description": "Prefer authored reference list-op item count. If the runtime can only report prims-with-authored-references, record that limitation in composition.counting_method."
        },
        "payload_count": {
          "type": "integer",
          "description": "Prefer authored payload list-op item count. If the runtime can only report prims-with-authored-payloads, record that limitation in composition.counting_method."
        }
      }
    },
    "composition": {
      "type": "object",
      "description": "Composition arc counts. Required fields route Phase 2a classification. Agents may add inherits, specializes, variants, sublayers, etc.",
      "required": [
        "layers",
        "references",
        "payloads",
        "counting_method"
      ],
      "additionalProperties": true,
      "properties": {
        "layers": {
          "type": "integer"
        },
        "references": {
          "type": "integer"
        },
        "payloads": {
          "type": "integer"
        },
        "counting_method": {
          "type": "string",
          "enum": [
            "authored_list_op_items",
            "prims_with_authored_arcs",
            "mixed_or_unknown"
          ],
          "description": "How reference/payload counts were computed. Authored list-op item counts are preferred; prim-level booleans are a fallback."
        },
        "inherits": {
          "type": "integer"
        },
        "specializes": {
          "type": "integer"
        },
        "variants": {
          "type": "integer"
        },
        "sublayers": {
          "oneOf": [
            {
              "type": "integer"
            },
            {
              "type": "array",
              "items": {
                "type": "string"
              }
            }
          ]
        }
      }
    },
    "instancing": {
      "type": "object",
      "description": "Instancing metrics for restructure-decision Phase 2d. Agents may add context about instancing readiness.",
      "required": [
        "instances",
        "prototypes",
        "candidates",
        "ratio"
      ],
      "additionalProperties": true,
      "properties": {
        "instances": {
          "type": "integer"
        },
        "prototypes": {
          "type": "integer"
        },
        "candidates": {
          "type": "integer"
        },
        "ratio": {
          "type": "number"
        }
      }
    },
    "hierarchy_dedupe": {
      "type": "object",
      "description": "Hierarchy deduplication gate signal for restructure-decision. 'recommended' is the boolean gate; top_candidates provides detail.",
      "required": [
        "recommended",
        "reason",
        "top_candidates"
      ],
      "additionalProperties": true,
      "properties": {
        "recommended": {
          "type": "boolean"
        },
        "reason": {
          "type": "string"
        },
        "top_candidates": {
          "type": "array",
          "items": {
            "type": "object",
            "required": [
              "path_pattern",
              "subtree_prims",
              "copies",
              "estimated_prim_savings"
            ],
            "additionalProperties": true,
            "properties": {
              "path_pattern": {
                "type": "string"
              },
              "subtree_prims": {
                "type": "integer"
              },
              "copies": {
                "type": "integer"
              },
              "estimated_prim_savings": {
                "type": "integer"
              }
            }
          }
        }
      }
    },
    "validation_scope": {
      "type": "object",
      "description": "Feeds directly into usd-optimize-run-validators. Strict: these arrays are the handoff contract.",
      "required": [
        "per_asset",
        "cross_component_pairs",
        "skip"
      ],
      "additionalProperties": false,
      "properties": {
        "per_asset": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "cross_component_pairs": {
          "type": "array",
          "description": "Enclosing/enclosed boundary pairs that scope the Tier-3 occlusion/overlap probe, referenced by boundary_id (see asset_boundary_suggestions.boundaries[] and usd-structure-assessment README §2.1 for how pairs are nominated and gated).",
          "items": {
            "type": "object",
            "required": [
              "enclosing_boundary_id",
              "enclosed_boundary_id"
            ],
            "additionalProperties": false,
            "properties": {
              "enclosing_boundary_id": {
                "type": "string",
                "description": "boundary_id of the enclosing boundary (spatial_role: enclosing)."
              },
              "enclosed_boundary_id": {
                "type": "string",
                "description": "boundary_id of the enclosed boundary (spatial_role: enclosed)."
              },
              "enclosure_opaque": {
                "type": "boolean",
                "description": "Optional opacity hint, not a required assertion. true = opaque enclosure (probe); false = transparent (skip — internals are visible); absent = unknown, in which case the pair is still probed and opacity is resolved during the Tier-3 material/geometry probe. SA must not assert this boolean when opacity is not determinable from material-binding metadata alone — omit it instead."
              },
              "probe": {
                "type": "string",
                "enum": ["spatial_occluded", "spatial_overlapping", "spatial_coinciding"],
                "description": "Which Tier-3 spatial concept this pair scopes. Defaults to spatial_occluded."
              },
              "bbox_confirmed": {
                "type": "boolean",
                "description": "Optional informational confirmation that authored-extent overlap corroborated the nomination. Never gates whether the probe runs; absence does not retract the nomination."
              },
              "notes": {
                "type": "string"
              }
            }
          }
        },
        "skip": {
          "type": "array",
          "items": {
            "type": "string"
          }
        }
      }
    },
    "phase_recommendation": {
      "type": "string",
      "enum": [
        "structuring",
        "optimization",
        "already_optimized"
      ],
      "description": "Legacy assessment recommendation: structuring, optimization, or already optimized. This field does not require a user approval pause."
    },
    "assets": {
      "type": "object",
      "additionalProperties": true
    },
    "asset_boundary_suggestions": {
      "type": "object",
      "description": "Candidate asset/sub-asset boundaries for restructuring AND the boundary records occlusion nomination keys off. candidate_levels[] stay permissive; boundaries[] carries the nominated enclosing/enclosed product boundaries cross_component_pairs references by id. See usd-structure-assessment README §2.1 for the nomination model.",
      "additionalProperties": true,
      "properties": {
        "boundaries": {
          "type": "array",
          "description": "Nominated boundaries (candidate_source 'hash' for repeated modules, 'semantics' for unique one-off enclosed products). Nomination is the primary occlusion signal; a hash nomination does NOT by itself create a pair — pairing requires an enclosing+enclosed spatial_role established from semantics/hierarchy (see README §2.1).",
          "items": {
            "type": "object",
            "required": ["boundary_id", "prim_path", "candidate_source"],
            "additionalProperties": true,
            "allOf": [
              {
                "if": {
                  "properties": { "candidate_source": { "const": "semantics" } },
                  "required": ["candidate_source"]
                },
                "then": { "required": ["semantic_label"] }
              }
            ],
            "properties": {
              "boundary_id": {
                "type": "string",
                "description": "Stable id referenced by cross_component_pairs[].enclosing_boundary_id / enclosed_boundary_id."
              },
              "prim_path": {
                "type": "string",
                "description": "USD prim path of the nominated boundary root."
              },
              "candidate_source": {
                "type": "string",
                "enum": ["hash", "semantics"],
                "description": "'hash' = subtree-hash dedupe group (duplicate-count >= 2). 'semantics' = kind/naming/discipline-container signal for a one-off enclosed product (requires semantic_label)."
              },
              "spatial_role": {
                "type": "string",
                "enum": ["enclosing", "enclosed", "standalone"],
                "description": "Containment role. Required on any boundary referenced by a cross_component_pair: 'enclosing' = shell/housing, 'enclosed' = interior product. 'standalone' = no containment relationship."
              },
              "enclosure_opaque": {
                "type": "boolean",
                "description": "Optional opacity hint for an enclosing boundary (true=opaque, false=transparent, absent=unknown). Omit when opacity is not determinable from material-binding metadata alone; the Tier-3 probe resolves unknown opacity."
              },
              "semantic_label": {
                "type": "string",
                "description": "The kind/name/discipline signal that drove a candidate_source: semantics nomination (e.g. 'Engine', 'pump_housing', 'HVAC'). Required when candidate_source is 'semantics'."
              }
            }
          }
        }
      }
    },
    "kind_hierarchy": {
      "type": "object",
      "additionalProperties": true
    },
    "prototype_library": {
      "type": "object",
      "additionalProperties": true
    },
    "findings": {
      "type": "array",
      "items": {
        "type": "object",
        "additionalProperties": true
      }
    }
  }
}

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: Requires a verified standalone Usd Optimize/OpenUSD runtime for operations, usd-validation-nvidia for supported checks, and a writable output workspace. Remote assets require a working resolver. Render profiling is an external handoff.

Security

What our scanner noticed· Medium risk

Large base64-encoded blobs
Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

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-usd-performance-tuning · commit fce3cca

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE-APACHE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

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-usd-performance-tuning.zip