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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://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/content-agents/references/material-agent-client/README.md

Assign Visual Materials

When to Use

Use this reference after USD conversion and minimum USD validation when an asset needs visual material assignment. It is normally selected through the content-agents router and calls this reference's scripts/run.py, which talks to the Content Agents Material Agent service API and downloads the materialized USD output.

This reference does not assign rigid bodies, colliders, mass, friction, or texture maps. Run physics-agent-client after this step when simulation physics are required. Run texture-agent-client only when textured output is desired.

Upstream Reference

Use the upstream NVIDIA Omniverse Content Agents Material Agent client skill as the authoritative reference for service API behavior, endpoint semantics, request fields, and client-side troubleshooting:

  • Upstream skill: https://github.com/nvidia-omniverse/content-agents/blob/v0.5.2/.codex/skills/material-agent-client/SKILL.md

  • Upstream repository: https://github.com/nvidia-omniverse/content-agents at manifest pin v0.5.2

  • Upstream service client: https://github.com/nvidia-omniverse/content-agents/blob/v0.5.2/apps/material_agent_service/client/client.py

Access note: Browser or raw-file fetches of the upstream skill URL can fail. If that happens, use the normalized local clone of https://github.com/nvidia-omniverse/content-agents checked out to the exact ref in upstream-versions.lock.json and read .codex/skills/material-agent-client/SKILL.md from that checkout. Resolve that clone from CONTENT_AGENTS_UPSTREAM_ROOT, then $OMNIVERSE_CAD_TO_SIMREADY_UPSTREAM_ROOT/content-agents, then $HOME/.omniverse-cad-to-simready/upstreams/content-agents.

Do not copy or reinterpret upstream Material Agent API behavior here. Keep this reference limited to this reference's wrapper contract, required environment, report shape, and downstream handoff.

Dependency Check

Require:

  • this reference's portable scripts/run.py and scripts/check_dependencies.py

  • a reachable Material Agent service URL through --base-url or CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL

  • CONTENT_AGENTS_MATERIAL_AGENT_TOKEN, MATERIAL_AGENT_TOKEN, CONTENT_AGENTS_TOKEN, NGC_API_KEY, or NVCF_API_KEY when the service requires bearer auth.

If no Material Agent base URL is configured, do not immediately stop at assignment. Use deploy-content-agents with target material; that reference points to the upstream deployment skill and owns deployment details. After deployment health checks pass, export the resulting host/client URL as CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL and rerun material-agent-client.

First-time users must not run assignment before service readiness is settled. Check for a reachable endpoint, then check for NVIDIA_API_KEY; if the key is missing, ask the user to create/provide one and wait. When deployment succeeds and the service is healthy, run this command.

If deployment is unavailable or fails because the upstream checkout, Docker/GPU prerequisites, renderer wiring, or required credentials are missing, preserve those deployment findings and then report the material assignment as blocked. Do not hand-author substitute material bindings or bypass the Content Agents service when this reference was selected.

Do not commit API keys, put them in reports, or pass them as command-line arguments in normal workflows because process listings can expose argv. The portable wrapper redacts tokens from its report command, but prefer CONTENT_AGENTS_MATERIAL_AGENT_TOKEN, MATERIAL_AGENT_TOKEN, CONTENT_AGENTS_TOKEN, NGC_API_KEY, NVCF_API_KEY, or matching *_FILE variables from the environment. NVIDIA_API_KEY is deployment auth and is not used as the default client bearer token. The --token option remains available only for constrained automation that cannot inject environment variables.

Inputs

Collect:

InputRequirement
asset_pathRequired .usd, .usda, .usdc, or .usdz asset.
output_directoryRequired directory for downloaded service artifacts.
base_urlOptional Material Agent service endpoint; overrides env-based base URL resolution.
tokenOptional bearer token; defaults to env.
emailOptional user email metadata.
promptOptional material assignment guidance; prefer the material_physics_prompt from identify-asset-context when available.
optimize_usdOptional; enabled by default. The wrapper inspects USD topology first and disables it only for instance/prototype-only assets that would otherwise lose all renderable prims if the main service falls back to original topology. If system python3 cannot import pxr, the wrapper tries uv run --python 3.12 for topology inspection before falling back to the service default.
skip_instancesOptional; normally left to the service default when optimize_usd remains enabled. The wrapper sends skip_instances=false only when it selects the instance/prototype-only traversal path.
vlm_max_workersOptional Material Agent VLM worker limit. The wrapper defaults to 1 to avoid partial prediction batches from bursty service-side VLM concurrency.
render_num_workersOptional Material Agent render worker limit passed through to the service when supplied.
material_stepsOptional comma-separated service steps. The wrapper defaults to build_dataset_usd,build_dataset_prepare_dataset,predict,apply; final rendering is handled by ovrtx-render-service after material assignment.

Upload Prep

Before uploading USD-layer inputs, the wrapper stages a material-safe copy when it finds MDL shader sourceAsset attributes such as gltf/pbr.mdl. Converted glTF or CAD assets can reference these MDL sidecars even when the sidecar files are absent from the converted asset directory. Those missing shader-source files are not needed for Material Agent prediction, and they can block USDZ upload packaging. The report records this as material_upload_info.staged=true with stripped_mdl_source_assets.

The wrapper then performs mandatory dependency inspection using an available OpenUSD runtime and packages every resolvable sidecar into the uploaded USDZ. Material Agent has one explicit exception: unresolved texture extensions may pass through in the original USD with an upload_info.warning when dependency inspection finds no resolved sidecars, because material prediction can replace missing source textures. When a missing texture prevents packaging one or more resolved dependencies, the wrapper fails locally rather than upload a root layer that drops those sidecars. Missing USD layers and all other non-texture dependencies fail locally before a service session is created. Set CONTENT_AGENTS_OPENUSD_PYTHON to a Python 3.12 interpreter with pxr when the process runtime and trusted skill-project fallback cannot perform this inspection.

Output Cleanup

After the required materialized USD artifact is downloaded, the wrapper runs a narrow material hygiene pass on USD-layer outputs. It finds actually bound materials, then removes unbound UsdShade.Material subtrees whose shader children use implementationSource = "sourceAsset" without a valid authored or packaged MDL sourceAsset. If a bound material still has that broken shader shape, the wrapper preserves the binding and rewrites only the broken shader prim to a neutral UsdPreviewSurface fallback. This preserves the Material Agent's usable material assignment while pruning or repairing stale converted material networks that can trigger SimReady material validation failures. The report records the result in material_output_cleanup.

Pass --no-material-output-cleanup only for debugging when the unmodified service artifact must be preserved.

Rate Limits

This wrapper retries transient status polling and delayed artifact downloads, including HTTP 429 responses returned by those wrapper-visible endpoints. It cannot retry per-prim VLM predictions that the Material Agent has already marked failed inside a completed session. If the service report shows VLM rate limits, preserve the partial predictions, rerun later or with a smaller asset/workload when possible, and use a service key with sufficient quota for large assemblies.

Local Scene Optimizer Permission Workaround

For local Docker deployments, a known upstream issue can make the optimized Material Agent path fail inside the service with a log like: Scene Optimizer failed — continuing pipeline without optimization (using original USD): [Errno 13] Permission denied: '/app/.build-resources/scene_optimizer_core/python'. This is a Scene Optimizer bundle permission problem in the service container, not a signal to permanently disable Material Agent optimize_usd.

When optimize_usd=true was intended and local service logs show the permission error above on a container named content-material-agent-service, repair the running deployment and rerun the same Material Agent command:

docker exec --user root content-material-agent-service chmod -R a+rX /app/.build-resources/scene_optimizer_core

If the container name differs, use the active Material Agent service container. If the endpoint is managed or remote and you cannot inspect or repair the container, preserve the report and include the optimizer-bypass evidence in the blocked or failed handoff. Track the upstream issue in the https://github.com/nvidia-omniverse/content-agents issue tracker.

Instructions

  1. Confirm the asset exists and is a USD-family file.

  2. Resolve the Material Agent endpoint from --base-url or CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL.

  3. If no endpoint is available, check NVIDIA_API_KEY; if missing, ask the user to provide one and wait.

  4. Use deploy-content-agents with target material; when deployment succeeds and the service is healthy, set CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL and return to this workflow.

  5. If an asset context report exists, use its likely identity, evidence, and material hints to craft --prompt.

  6. Run this reference's portable scripts/run.py. It inspects the USD first, strips missing MDL shader-source upload references when needed, keeps optimize_usd=true by default, sends vlm_max_workers=1, omits the service-side render step, and switches to optimize_usd=false with skip_instances=false only for instance/prototype-only topology where the main service would otherwise skip all renderable prims. If the optimized path still fails with the known Rendering produced 0 images symptom, the wrapper retries once with optimize_usd=false and skip_instances=false and records both attempts. After downloading the materialized USD, it removes unbound stale material subtrees and repairs bound stale shaders with broken sourceAsset references.

  7. If the optimized path was intended but service logs show the local Scene Optimizer permission failure above, repair the container permissions and rerun the optimized command before accepting a direct-traversal result as diagnostic.

  8. Preserve the JSON report, materialized USD output, predictions JSONL, and report HTML when available.

  9. Use output_usd_path from the report as the input to physics-agent-client.

CLI Pattern

python3 /path/to/skills/omniverse-cad-to-simready/references/content-agents/references/material-agent-client/scripts/run.py asset.usda output_dir/materials \
  --prompt "$ASSET_CONTEXT_PROMPT" \
  --report output_dir/materials/material-agent-client.json

Add --base-url "$CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL" only when overriding the URL resolved from the environment.

Use --layer-only only when the user wants a bindings layer and the downstream workflow knows how to compose it.

--optimize-usd is the default effective path. Pass --no-optimize-usd only to force direct Material Agent traversal. For converted CAD assets that contain only instanced/prototype renderable geometry, the wrapper chooses that direct traversal path automatically and sends skip_instances=false; this avoids main Material Agent sessions that produce a zero-image dataset after skipping every instance/proxy prim.

When topology inspection is unavailable but the service returns Rendering produced 0 images from build_dataset_usd, the wrapper treats that as the same recoverable zero-render symptom and retries once through direct traversal. The JSON report includes attempts when this fallback runs.

Use --no-material-output-cleanup only when preserving the raw downloaded Material Agent artifact is more important than downstream SimReady validation hygiene.

Use --material-steps only when the service's own render artifact is required. The CAD-to-SimReady workflow treats the standalone ovrtx-render-service output as the final render.

Output Format

The report includes:

  • asset_path

  • skill

  • agent

  • tool

  • passed

  • status

  • base_url

  • session_id

  • output_directory

  • output_usd_path

  • material_upload_info

  • material_output_cleanup

  • artifacts

  • service_status

  • service_results

  • checks

  • warnings

  • errors

  • next_step

Pass/Fail Policy

Fail or block when:

  • the input asset is missing or not USD-family

  • the service URL is missing and deploy-content-agents cannot deploy a healthy Material Agent service

  • the service session fails or times out

  • the required materialized USD artifact cannot be downloaded

Warn when optional prediction or HTML report artifacts are unavailable.

Next Steps

Use this handoff:

ResultNext step
Materialized USD downloadedRun physics-agent-client on output_usd_path.
Service endpoint missingCheck NVIDIA_API_KEY, use deploy-content-agents target material, export CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL, then rerun.
Service deployment blockedResolve the deployment blocker, or configure a Material Agent base URL and usage token, then rerun.
Service failedInspect service_status, service_results, and optional report artifacts.

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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