nvidia-omniverse-blueprints/digital-twins-for-fluid-simulation/rtdt-customize

Claude Code and agent skill by nvidia-omniverse-blueprints/digital-twins-for-fluid-simulation

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Customize an RTDT workflow, AppState schema, USD stage, frontend control, or Kit-CAE 3.0 geometry/result wiring. Use when adding or changing controls, variants, bindings, output fields, visualization selections, or bring-your-own geometry. Read rtdt-core first; use rtdt-aero as the specialization-specific companion for the shipped wind tunnel.

Install

npx vskill@latest install nvidia-omniverse-blueprints/digital-twins-for-fluid-simulation/rtdt-customize

SKILL.md

RTDT Customize

Read rtdt-core before using this skill. Most workflow changes span four surfaces: typed AppState schema, workflow manifest, USD stage, and the hand-built Trame frontend. Changing only one surface is usually incomplete.

Classify the change

  • Backend-only control: schema + manifest + binding, used without a new shipped UI widget.
  • User-visible control: backend wiring plus the matching Trame widget and bridged state key.
  • Visual-only geometry: cosmetic USD composition and visibility/variant wiring; no new result.
  • Inference geometry: plugin-backed PLY surface, inference target wiring, model compatibility,

and cache consequences.

  • Output field: producer wire, stage result selection, result dataset APIs, manifest metadata,

and visualization selection must all agree.

Authoring loop

  1. Read the current schema, workflow.toml, stage, and frontend together.
  2. Add or update the AppState attribute. Preserve its USD type, allowedTokens, and authored default;

regenerate the specialization schema using the repository's verified codeless-schema workflow.

  1. Add or update [controls.<id>]. Keep the control ID equal to the schema attribute short key.
  2. Author only binding kinds implemented by the controller. Use

manifest-reference.md for exact semantics.

  1. Author the stage-side target: variant set, attribute, relationship, material, callback write, or

Kit-CAE 3.0 dataset/field APIs.

  1. For a visible control, update trame-app/app.py. The current UI does not generate widgets from

get_control_manifest. If an inference control participates in lite-cache restrictions, also map its <key>_options in pullAvailableOptionsFromKit() in trame-app/static/app_streamer.js.

  1. Validate the manifest/schema. Add a composed stage when checking targets, variants, outputs, or

colormap readouts:

``bash tools/validate/rtdt-validate.sh \ --manifest <workflow.toml> \ --schemas <AppStateAPI...> \ --stage <composed-stage.usda> ``

  1. Run the smallest relevant unit/static checks, then use the appropriate Compose profile for

runtime verification. A clean validator result is necessary but does not prove rendering, streaming, callback behavior, or model accuracy.

Bring-your-own geometry

Use geometry-and-inference.md for the Kit-CAE 3.0 pattern. tools/geometry/prepare_mesh.py remains useful for converting, fitting, centering, repairing, and writing the PLY surface. Treat its scaling notice as a required review item.

prepare_mesh.py emits the current Kit-CAE 3 plugin-backed recipe: an OmniSciDataset payload with OmniSciFileFormatArgsPythonAPI, RtwtModelAPI, and omni:rtwt:model:tag. Its output is ready-to-paste native USDA for a sibling model prim when the command supplies the required --model-tag and a --asset-path relative to the layer that will receive it. For a nested variant tree, apply the APIs once on the base dataset and move only the emitted payload and omni:rtwt:model:tag opinions into each variant leaf.

The directory source/specializations/auto-aero/examples/byo-geometry-cube/ is a static manifest/schema/stage validator fixture. It demonstrates control-to-variant wiring; it is not a runnable frontend, streaming application, or CAE inference example.

Output-field checklist

For every new field, verify all of the following:

  • producer tensor and Triton configuration;
  • RtwtResultFieldSelectionAPI:<wire-id> target and fieldName;
  • paired OmniSciArrayAPI:<Field> and OmniSciFieldAPI:<Field> on the one result dataset;
  • [outputs.<wire-id>] metadata;
  • cae:viz:field_selection:<role>:fieldNames on each consumer;
  • cache data and sidecars for lite mode.

Do not introduce a second result dataset merely to hold another field. Keep fields on the RtwtInferenceResultsAPI dataset unless the runtime contract itself is deliberately redesigned.

Resources

behavior.

schema regeneration commands and review gate.

result, visualization, and cache contracts.

  • rtdt-aero — exact auto-aero files and geometry recipe.

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
139
Repository forks
47
7-day trend score
25

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 11 Sep 2026, a month ago.

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