omniverse-usd-performance-tuning

Files (143)

• BENCHMARK.md
• SKILL.md
• openai.yaml · agents/
• evals.json · evals/
• README.md · references/cad-conversion/
• conversion-report.schema.json · references/cad-conversion/scripts/
• compare-profiles.md · references/
• README.md · references/compare-profiles/
• README.md · references/omniverse-authentication/
• CLASSIFICATION.md · references/operations/
• EXECUTION.md · references/operations/
• README.md · references/operations/
• _curation.json · references/operations/
• _template.md · references/operations/
• boxClip.md · references/operations/
• computeExtents.md · references/operations/
• countVertices.md · references/operations/
• decimateMeshes.md · references/operations/
• deduplicateGeometry.md · references/operations/
• deduplicateHierarchies.md · references/operations/
• deleteHiddenPrims.md · references/operations/
• deletePrims.md · references/operations/
• diceMeshes.md · references/operations/
• editStageMetrics.md · references/operations/
• findCoincidingGeometry.md · references/operations/
• findFlatHierarchies.md · references/operations/
• findOccludedMeshes.md · references/operations/
• findOverlappingMeshes.md · references/operations/
• fitPrimitives.md · references/operations/
• flattenHierarchy.md · references/operations/
• generateAtlasUVs.md · references/operations/
• generateNormals.md · references/operations/
• generateProjectionUVs.md · references/operations/
• generateScene.md · references/operations/
• manifest.json · references/operations/
• manifoldMeshes.md · references/operations/
• merge.md · references/operations/
• mergeVertices.md · references/operations/
• meshCleanup.md · references/operations/
• optimizeMaterials.md · references/operations/
• optimizePrimvars.md · references/operations/
• optimizeSkelRoots.md · references/operations/
• optimizeTimeSamples.md · references/operations/
• organizePrototypes.md · references/operations/
• pivot.md · references/operations/
• primitivesToMeshes.md · references/operations/
• printStats.md · references/operations/
• so-110.0.4.json · references/operations/probe-snapshots/
• pruneLeaves.md · references/operations/
• pythonScript.md · references/operations/
• remeshMeshes.md · references/operations/
• removeAttributes.md · references/operations/
• removePrims.md · references/operations/
• removeSmallGeometry.md · references/operations/
• removeUntypedPrims.md · references/operations/
• removeUnusedUVs.md · references/operations/
• rtxMeshCount.md · references/operations/
• operation-curation.schema.json · references/operations/scripts/
• operation-manifest.schema.json · references/operations/scripts/
• shrinkwrap.md · references/operations/
• …and 83 more

SKILL.md (first lines)

# Omniverse USD Performance Tuning

<!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->
<!-- SPDX-License-Identifier: Apache-2.0 -->

## When to Use

Use this workflow for broad performance asks such as slow loading, high memory, low FPS, GPU crashes, conversion-quality triage, or generic requests to optimize a USD scene.

## Instructions

1. Start from the mandatory runtime context gate before producing tuning output, unless the prompt is only asking for a static classification test.
2. Classify broad optimization requests as `ready_to_plan`; reserve `approval_required` for prompts that explicitly name a destructive operation to execute before planning.
3. Plan the full canonical chain through `optimization-report`, preserving the structured milestone order and the `profile-stage:baseline` / `profile-stage:after` labels when listing milestones. For broad optimization, default to 3 scoped iterations unless the user opts out, asks for a quick pass, or stop criteria apply.
4. Invoke downstream skill bodies only when their phase is reached, and keep raw runtime artifacts on disk while reading compact summaries.

Frontmatter keeps `version` and `tools` at top level for agentskills.io runtime
compatibility. NVCARPS discoverability fields live under `metadata`.

## Output Format

Return a plan or status summary that names the selected entry skill, uses `ready_to_plan` for generic optimization requests, includes the full milestone chain through `optimization-report`, and labels profile phases as `profile-stage:baseline` and `profile-stage:after`. For structured outputs, the broad-optimization milestone subsequence is `omniverse-usd-performance-tuning` -> `profile-stage:baseline` -> `usd-structure-assessment` -> `usd-validation-runner` -> `restructure-decision` -> `apply-restructure` -> `so-run-validators` -> `so-interpret-validators` -> `so-run-operations` -> `profile-stage:after` -> `compare-profiles` -> `optimization-report`. End-to-end execution should produce an optimized stage when mutation runs and a report conforming to the `optimization-report` reference's schema (`scripts/optimization-report.schema.json` within that reference). Broad optimization should plan 3 scoped iterations by default; each iteration writes an interim report/update and later passes reuse prior evidence instead of restarting the full workflow.

Use this workflow for broad performance asks such as slow loading, low FPS,
high memory, GPU crashes, conversion quality, or "optimize my scene."

## Entry skill rule

This skill is the named entry point for broad performance work whenever the
agent has any verified way to do that work. Runtime probing details live in
`setup-usd-performance-tuning`; this rule only decides which skill owns the
user-facing performance request.

- If the setup probe shows **any** verified runtime path - Kit, standalone, or
  even a partial stack such as Asset Validator only - enter here. If the
  user's requested tool is missing, return the specific `blocked_code`
  (`blocked_missing_scene_optimizer`, `blocked_missing_so_operation`, etc.)
  instead of substituting another workflow.
- Enter at `setup-usd-performance-tuning` only when **no** runtime path is
  verified and runtime choice/setup is the first unresolved problem.
- For `omniverse://` assets, enter at `omniverse-authentication` first.
  Authentication precedes setup and triage for remote assets.

The decision is about ownership, not order. Setup, authentication, and triage all run in their normal phase order; this rule only fixes which skill the agent **names as the entry skill** in its response.

## Runtime context — session-start gate (mandatory)

**Before any other tuning output**, follow the mandatory session-start gate in
`skills/omniverse-usd-performance-tuning/references/setup-usd-performance-tuning/references/runtime-context-header.md`.
That reference owns `output_path`, the canonical `setup-preflight.json`
location, Format A/Format B, and the "do not improvise a silent probe"
anti-pattern.

Required outcomes:

- Missing or unreadable preflight: invoke `setup-usd-performance-tuning`.
- Present preflight: print Format A and wait for the user to choose Continue,
  Change Kit, Switch to standalone, or Re-run probe.
- Confirmed runtime in the same session: use compact Format B for follow-up
  status.

```
[Kit: {runtime_context.kit.application} {runtime_context.kit.version}  |  SO: {runtime_context.sceneOptimizer.version}  |  AV: {runtime_context.assetValidator.version}]
```

## Runtime artifact token budget

Before reading Kit logs, Asset Validator CSVs, Scene Optimizer logs, Tracy CSVs,
or other runtime output, follow
`references/runtime-artifact-token-budget.md`. Keep raw artifacts on disk, read
summary JSON first, and use bounded log snapshots instead of full dumps or live
streams.

## Plan-time vs execution-time approval

`approval_required` at planning time is reserved for requests that explicitly name a destructive operation. Use the following rule when deciding between `ready_to_plan` and `approval_required`:

- **`approval_required` at planning time** — the user's request itself names a destructive operation: "flatten this stage", "decimate the meshes", "merge prototypes", "delete unused prims", or any specific named mutation that cannot be undone within the same workflow. In this case the agent's first response must be an approval prompt that names the operation, before the agent commits to a plan that executes it.
- **`ready_to_plan` at planning time** — the user's request is general: "optimize this scene", "make it load faster", "reduce GPU memory", "improve interactivity". The agent lays out the full plan, including any destructive operations the plan would invoke (for example `so-run-operations` with `mergeMaterials`), without withholding the plan itself. **Approval for each destructive operation is requested alongside plan approval**.

The distinction is between **authorising a plan** and **authorising a destructive action**. A general optimisation request authorises planning; it does not authorise execution of specific destructive operations.

For structured runtime-test responses and similar planning summaries:

- A future `restructure-decision` prompt is a planned user-decision gate, not a reason to set the top-level response `decision` to `approval_required` for a generic optimization request.
- For a generic optimization request, set `decision: "ready_to_plan"` and include the full intended chain in both `committed_milestones` and `planned_phases`, through `optimization-report`.
- It is valid for `gates_observed` to include `asks_user_for_restructure_decision` while the top-level `decision` remains `ready_to_plan`.
- Whenever a chain names profile phases, use the exact labels `profile-stage:baseline` and `profile-stage:after`; do not emit the ambiguous bare `profile-stage` token.
- Start structured milestone lists with `omniverse-usd-performance-tuning` as the owning entry skill. Include `setup-usd-performance-tuning` only as additional Phase 0 context, not as a replacement for the entry skill milestone.
- For broad optimization requests, preserve the milestone subsequence from *Output Format* above exactly, with optional extra analysis steps inserted only where they do not reorder it.
- Do not list `so-run-validators` or `so-interpret-validators` before `restructure-decision` in broad optimization milestone summaries. Phase-aware validator routing still happens through `usd-validation-runner`; the SO validator executor/interpreter milestones appear after the restructure decision path in the structured plan contract.

## Output expectation

End-to-end optimization work should produce both an optimized USD stage, when
mutation is executed, and a structured optimization report conforming to
the `optimization-report` reference's `scripts/optimization-report.schema.json`. The HTML report must be rendered
from `references/report-templates/optimization-report.html.template` via
`render_preview.py` — never hand-write HTML. Diagnosis-only work should still
end with a report or summary that states no optimized stage was written.

## Purpose

Route digital twin USD performance requests into the right diagnostic and
optimization workflow while preserving evidence before mutation.

## Prerequisites

- Stage path or enough context to identify the target asset.
- User goal: diagnosis only, validation, profiling, or processor execution.
- Runtime availability status from `setup-usd-performance-tuning` when not already known.
- Permission status for in-place mutation vs writing a separate optimized output.

## Examples

- "This USD loads slowly; triage what to check first."
- "Route a low-FPS CAD scene through the performance workflow."

## Triage order

From sayalinvidia/sayali-skills-test, Apache-2.0.

More from sayalinvidia/sayali-skills-test