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Omniverse Cad To Simready

NVIDIAOfficialCreated by OmniverseDistributed by NVIDIA

  • Skill
  • Workflow
  • Software development
  • Apache-2.0
  • Medium risk
  • Has scripts

From the author

Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references.
— the description by Omniverse

AutoGineer summary

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

This skill acts as an orchestrator for the CAD to SimReady pipeline, coordinating a series of specialized stages including asset conversion, material and physics assignment via Content Agents, validation, and final packaging. It is designed to manage the flow between discrete tools rather than replacing them, ensuring that assets meet specific simulation requirements through a structured, documentation-driven process.

What it does

  • Coordinates end-to-end conversion from source CAD or mesh assets to SimReady USD.
  • Manages property assignment for materials and physics using Content Agents.
  • Performs multi-stage validation gates to ensure asset viability and conformance.
  • Automates the assembly of deliverable packages including thumbnails and USD dependencies.
  • Provides consolidated reporting on workflow status, validation findings, and stage outputs.
  • Supports flexible execution modes including conversion-only and validation-only paths.

When to use it

  • When you need to transform raw CAD or source assets into simulation-ready USD files.
  • When you require automated material and physics assignment for 3D assets.
  • When you need to validate assets against SimReady conformance profiles.
  • When you are preparing assets for packaging and distribution in a simulation environment.

Advantages

  • Provides a structured, repeatable pipeline for complex asset preparation.
  • Integrates multiple specialized stages into a cohesive workflow.
  • Ensures consistent validation and conformance across the asset lifecycle.
  • Supports modular execution by allowing specific stages to be skipped or isolated.

Usage examples

“Convert my CAD file at /path/to/model.step to a SimReady asset.”
The agent will initiate the preflight check, convert the file to USD, apply material and physics properties, validate the result, and output a report.
“Validate this existing USD file for SimReady conformance.”
The agent will run the validation-only workflow, checking the provided USD against SimReady profiles and reporting any findings.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/nvidia/omniverse-cad-to-simready/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip omniverse-cad-to-simready.zip -d .agents/skills

Documentation by Omniverse

CAD to SimReady

When to Use

Use this workflow skill for an end-to-end pipeline from a source asset to a SimReady asset or package. It coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly; do not replace it with a single monolithic runner command.

This skill is documentation-driven and does not ship scripts/run.py; it must not depend on a repository checkout. Shell is declared because this workflow invokes installed stage reference scripts directly, from each reference's installed directory, and it still must not grow a monolithic runner.

Prerequisites

  • Prefer preflight first for deterministic setup: it installs/verifies local upstream checkouts, writes a cad-to-simready-preflight.json manifest, and exports PHYSICAL_AI_PREFLIGHT_MANIFEST plus PHYSICAL_AI_REQUIRE_PREFLIGHT=1 for downstream references.

  • Python 3.12 and uv (per repo README.md).

  • A Content Agents model provider key when local deployment will run, or explicit endpoint variables plus usage tokens for already-running endpoints; see references/preflight/README.md for the full list.

  • Docker, NVIDIA Container Toolkit, and an NVIDIA GPU for Content Agents and OVRTX stages.

  • Local upstream checkouts under ${OMNIVERSE_CAD_TO_SIMREADY_UPSTREAM_ROOT:-$HOME/.omniverse-cad-to-simready/upstreams} when a stage needs upstream scripts or specs.

First Action

For any broad CAD/source-asset to SimReady request, assume property_assignment_intent=run unless the user explicitly asks for conversion-only, validation-only, or no material/physics assignment. For conversion-only requests, set property_assignment_intent=skip, do not deploy Content Agents, run convert-to-usd, then run validate-usd-minimum on the generated USD if conversion succeeds. For validation-only requests, set property_assignment_intent=skip and validate the USD the user provided without rerunning conversion.

Run preflight (or verify an existing PHYSICAL_AI_PREFLIGHT_MANIFEST) before any converter, validation, Content Agents, OVRTX, packaging, or FET step; treat it as dependency bootstrap, not workflow routing. Use --skip-content-agents for conversion-only/validation-only requests.

When property_assignment_intent=run, verify or deploy Content Agents services immediately after confirming the source path and resolving intent, before asset-context inspection, converter dependency checks, conversion, validation, conformance, rendering, packaging, or upstream source builds. Treat explicitly provided healthy endpoints as user-owned; otherwise run deploy-content-agents, which deploys the shared standalone OVRTX renderer, then Material, Physics, and optional Texture service containers in order.

Instructions

  1. Confirm the source asset path exists, resolve output_root, and classify the request as end-to-end, conversion-only, validation-only, or packaging.

  2. Resolve property_assignment_intent before running any asset inspection, converter probe, conversion, validation, conformance, rendering, or packaging step.

  3. Run preflight for the selected workflow targets, unless a ready PHYSICAL_AI_PREFLIGHT_MANIFEST is already configured. Source the generated env file before running downstream scripts. Treat preflight as dependency setup only: it may use a provided --source-asset, --source-format, or --conversion-tools value to scope dependency checks, but convert-to-usd and the upstream converter references still decide actual conversion support.

  4. Verify or deploy Content Agents services first when property_assignment_intent=run; block on missing authentication or unhealthy services instead of continuing.

  5. Read references/workflow.md and references/commands.md, then run only the stage references needed for the current request.

  6. Run identify-asset-context on the original source asset when web search is available or property assignment will run.

  7. Route the source through convert-to-usd, or skip conversion for existing USD input and treat the source path as the current USD path.

  8. Run validate-usd-minimum before expensive downstream work. Treat this as a viability gate only: record unit/profile issues such as metersPerUnit != 1.0, but do not run simready-conform-profile, FET001, or any other FET repair before Content Agents assignment when property assignment will run.

  9. Run Content Agents material, physics, and optional texture assignment on the converted/minimum-valid USD when requested or required.

  10. Run simready-conform-profile on the latest simulation USD path after property assignment and preserve every selected FET repair report.

  11. Run validation gates in order: omni-asset-validate, omni-asset-validate-geometry, omni-asset-validate-physics, and simready-validate.

  12. Rerun simready-conform-profile when simready-validate reports a repairable requirement, then rerun profile validation on the newest authored USD.

  13. Run ovrtx-render-service when preview, thumbnail, or inspection images are requested. When package outputs are requested, run assemble-package-source next to create the clean deliverable/ package source from the final USD and thumbnail, then run nv-core-package-sample and nv-core-package-sample-validation on that deliverable folder only.

  14. Emit the consolidated workflow report with the final USD path, all stage reports, validation findings, rerun reasons, and next work.

Output Format

Emit a consolidated workflow report in Markdown, and include JSON when the workflow writes structured artifacts. Report overall status as passed, blocked, failed, or needs_rerun. See references/workflow.md for the required Markdown and JSON report fields.

Detailed References

Read only the references needed for the current request:

  • references/preflight/README.md: deterministic local setup, manifest/env contract, wrappers, deployment opt-out, and guardrail behavior.

  • references/workflow.md: inputs, source routing, detailed workflow, validation policy, output report fields, and next steps.

  • references/commands.md: concrete portable script command patterns.

  • references/assemble-package-source/README.md: two-zone package source assembly, root USD naming, thumbnail placement, and deliverable checks.

  • references/troubleshooting.md: symptom/cause/fix table plus FET (GSP.001/RB.MB.001) repair-routing detail.

  • references/publishing-layout.md: frontmatter compatibility-field notes and layout rationale for this skill's own file tree.

Publishing Layout Notes

Use skills/omniverse-cad-to-simready/ as the source of truth for this product repo's skill. The .agents/skills symlink is a compatibility alias for local agentskills.io-style discovery, and the nested references/ tree is intentional. See references/publishing-layout.md for the alias list, frontmatter field placement, and flattening rules.

Limitations

  • This workflow coordinates existing conversion, property assignment, conformance, validation, rendering, and packaging skills; it does not replace them with a single monolithic runner command.

Troubleshooting

Read references/troubleshooting.md only when a specific stage or validation gate is failing; it owns the symptom/cause/fix table and FET repair routing.

Hard Rules

  • Prefer the preflight manifest for local upstream roots, converter executables, SimReady validation runtime, OVRTX endpoint, and Content Agents service URLs. When PHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set, do not bypass the manifest with direct upstream discovery.

  • Do not run asset inspection, converter probes, local upstream builds, conversion, validation, conformance, rendering, or packaging before Content Agents readiness when property assignment will run.

  • Use stage-specific installed reference scripts directly. Do not add or call a single omniverse-cad-to-simready runner command.

  • For source conversion, delegate to the convert-to-usd reference; do not substitute another converter for CAD or mesh formats.

  • For property assignment, use Content Agents references as separate atomic steps: material first, then physics, then texture only when requested.

  • When property assignment will run, do not run simready-conform-profile or any FET helper before Content Agents. Validate minimum USD first, then run Content Agents on that converted/minimum-valid USD, then apply FET repairs to the latest service-authored USD.

  • When property assignment will run, do not run simready-validate or any SimReady profile validation before Content Agents. The only validation gate allowed before service calls is validate-usd-minimum, which is a basic USD viability check.

  • Stop at the first failing deployment, conversion, property-assignment, or conformance authoring gate unless the user explicitly asks for best-effort continuation.

  • Do not stop at validation findings after a meaningful USD artifact exists. Continue remaining diagnostic gates and mark the result needs_rerun.

  • Do not leave a GSP.001 profile failure as an unclassified final finding. Route it to upstream simready-foundation-conform-fet-005-simulate-grasp-physics; if the current agent cannot inspect renders or no explicit grasp points are available, report a blocked FET005 repair with the visual evidence path or missing input reason.

  • Preserve every stage report and pass the concrete output USD path from each report into the next stage.

Files

references/identify-asset-context/README.md

Identify Asset Context

When to Use

Use this reference before convert-to-usd and before Content Agents property assignment when the original source asset may contain product names, part numbers, manufacturer clues, CAD metadata, or other identifiers. The goal is to replace pure visual guessing with a small evidence-backed context report that can be passed into material-agent-client and physics-agent-client prompts.

This reference combines deterministic local inspection with web research. The reference's scripts/run.py extracts local clues from the source file; the agent then uses the recommended queries plus exact filename searches to gather public evidence and write an asset context report.

Inputs

Collect:

InputRequirement
source_assetRequired raw source asset path, preferably before conversion.
output_directoryRequired directory for local inspection and research reports.
web_searchRequired when network/tools are available; if unavailable, mark web research blocked.
converted_usd_pathOptional converted USD path for render or geometry context after conversion.
preview_image_pathOptional render preview used only as secondary visual evidence.

Instructions

  1. Confirm the source asset exists.

  2. Run this reference's scripts/run.py on the original source file and save JSON plus Markdown reports.

  3. Search the web using the exact source filename, internal filename from the report when present, local identifiers, and recommended query list.

  4. Prefer manufacturer datasheets, product pages, standards documents, package labels, or official catalogs over forums and reseller snippets.

  5. Summarize likely identity, manufacturer, product family, application, material candidates, physics/use assumptions, confidence, and cited evidence.

  6. Produce a concise material_physics_prompt suitable for --prompt on Material and Physics Agent commands.

  7. If evidence conflicts or only weak matches exist, keep uncertainty explicit and do not overfit the downstream prompt.

CLI Pattern

Local inspection:

python3 /path/to/skills/omniverse-cad-to-simready/references/identify-asset-context/scripts/run.py /path/to/source_asset \
  --report /path/to/output_dir/asset-context/asset-context.json \
  --markdown-report /path/to/output_dir/asset-context/asset-context.md

Use the report's recommended_web_queries as the starting query list. Always add exact filename and internal STEP/IGES FILE_NAME searches when those differ.

Research Report

Write asset-context.md and, when useful, asset-context.json with:

FieldMeaning
source_asset_pathOriginal source asset path.
local_identifiersFilename, internal filename, product codes, and extracted part-number-like tokens.
web_queriesQueries actually searched.
evidenceCited web sources with short relevance notes.
likely_identityBest concise identity, such as product family and part description.
manufacturerManufacturer or vendor when supported by evidence.
product_familyProduct line, standard, connector family, robot model, fixture family, etc.
applicationExpected real-world use context.
material_hintsEvidence-backed or clearly inferred visual material candidates.
physics_hintsRigid-body, collider, mass, friction, compliance, and use-case assumptions.
confidencehigh, medium, or low, with a short reason.
material_physics_promptA compact prompt to pass into assignment agents.

Handoff Prompts

For material-agent-client, include:

  • likely asset identity and manufacturer

  • product family/application

  • visible material candidates and finish, clearly separating evidence from inference

  • any constraints, such as connector housing, metal latch, gold contacts, rubber cable, or PCB laminate

For physics-agent-client, include:

  • whether the asset is a connector, cover, bracket, robot, tool, fixture, or flexible object

  • likely rigid/static behavior for robotics simulation

  • candidate component materials and density assumptions

  • collider strategy when the asset is one merged CAD mesh

  • confidence and any unsupported assumptions

Pass/Fail Policy

This context stage passes when local inspection succeeds and the research report is written. It can pass with low confidence if uncertainty is explicit.

Block when the source file is missing. Mark web research as blocked, not failed, when browsing is unavailable or the user explicitly asks not to search the web.

Next Steps

  • Run convert-to-usd after the context report is created.

  • Pass the material_physics_prompt into material-agent-client --prompt and physics-agent-client --prompt.

  • Include source links and confidence in the final CAD-to-SimReady report.

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: Declares allowed tools, Needs Python

The author says: Orchestrator skill. Managed Content Agents deployment requires a configured model provider key matching the selected backend, such as NVIDIA_API_KEY, OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY, or GEMINI_API_KEY, Docker + NVIDIA Container Toolkit + GPU, Python 3.12, and an upstream checkout of nvidia-omniverse/content-agents at the ref pinned in upstream-versions.lock.json. Reused/provided endpoints may instead use explicit endpoint and usage-token environment variables. Linux/macOS only.

Security

What our scanner noticed· Medium risk

  • Large base64-encoded blobs
  • Instructions that use the network
  • Downloads piped into a shell
  • 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
Omniverse
Publisher
NVIDIA (Official)
Distributed by
NVIDIA
Source
NVIDIA/skills · skills/omniverse-cad-to-simready · commit fce3cca
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE-APACHE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

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