Omniverse Cad To Simready

OpenAIOfficialCreated by OmniverseDistributed by OpenAI

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

From the skill’s files

Taken from the skill’s own files (its description, section headings and stated usage). Not an AutoGineer summary, and not written by the author as one.

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. Use this workflow skill when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package. This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly. Do not replace the workflow with a single monolithic runner command.

What it does

When to Use
Prerequisites
Minimum Viable Scope
First Action
Instructions
Output Format

When to use it

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…
Use this workflow skill when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package.
This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly.
This skill is documentation-driven and does not ship scripts/run.py.
It should not depend on a repository checkout.
When a stage needs deterministic execution, run the portable script from that stage reference's installed directory.

Advantages

The skill’s files do not state this.

Usage examples

The skill’s files do not state this.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/openai/omniverse-cad-to-simready/download

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 when the user wants an end-to-end pipeline from a source asset to a SimReady asset or package. This skill coordinates existing conversion, authoring, validation, conformance, rendering, and packaging references directly. Do not replace the workflow with a single monolithic runner command.

This skill is documentation-driven and does not ship scripts/run.py. It should not depend on a repository checkout. When a stage needs deterministic execution, run the portable script from that stage reference's installed directory. Shell is declared because this workflow invokes installed stage reference scripts directly; it still must not grow a monolithic runner.

Prerequisites

Prefer running the preflight reference first for deterministic setup. It installs or 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).
NVIDIA_API_KEY from https://build.nvidia.com when local Content Agents deployment will run. Already-running endpoints may instead use explicit endpoint variables plus usage tokens such as NGC_API_KEY, NVCF_API_KEY, or CONTENT_AGENTS_*_TOKEN.
Docker, NVIDIA Container Toolkit, and an NVIDIA GPU for Content Agents and OVRTX stages.
Local upstream checkouts under ${PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT:-$HOME/.physical-ai-skill-hub/upstreams} when a downstream stage needs upstream scripts or specs.

Minimum Viable Scope

Conversion-only is a valid workflow request. When the user asks only to convert or smoke-test source asset conversion, 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.

Do not imply that uv sync installs every source converter runtime. URDF, MuJoCo/MJCF, and the repo Python dependencies are handled by the project environment, but NVIDIA-backed source conversion requires an installed and validated NVIDIA-Omniverse/usd-convert-cad checkout. If that runtime is missing or does not support the source, preserve the blocked conversion report and its install_hint instead of attempting an unrequested local build or substituting another converter.

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.

Before invoking converter, validation, Content Agents, OVRTX, packaging, or FET helper scripts, run the preflight reference or verify an existing PHYSICAL_AI_PREFLIGHT_MANIFEST. Treat preflight as the mandatory dependency bootstrap step, not as workflow routing. If the user explicitly asks not to deploy services or asks for conversion-only/validation-only, use --skip-content-agents. When PHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set and a required component is not ready in the manifest, downstream references must block with the preflight guardrail instead of rediscovering upstreams or services directly.

When property_assignment_intent=run, the first operational action after confirming the source path and resolving intent is to verify or deploy Content Agents services. Do this before asset-context inspection, converter dependency checks, conversion, validation, conformance, rendering, packaging, or upstream source builds.

Use healthy existing endpoints when available. If OVRTX, Material, or Physics endpoints are missing or unhealthy, run deploy-content-agents first and do not continue until the shared standalone OVRTX renderer plus independent Material and Physics service containers are healthy and exported through CONTENT_AGENTS_*_BASE_URL. Deploy the Texture Agent too when texture generation is requested.

If required deployment authentication is missing, ask the user for NVIDIA_API_KEY and wait. If a provided endpoint requires usage auth, ask for the appropriate usage token instead. If deployment cannot produce healthy services, report Content Agents readiness as blocked instead of proceeding to conversion.

Instructions

Confirm the source asset path exists, resolve output_root, and classify the request as end-to-end, conversion-only, validation-only, or packaging.
Resolve property_assignment_intent before running any asset inspection, converter probe, conversion, validation, conformance, rendering, or packaging step.
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.
Verify or deploy Content Agents services first when property_assignment_intent=run; block on missing authentication or unhealthy services instead of continuing.
Read references/workflow.md and references/commands.md, then run only the stage references needed for the current request.
Run identify-asset-context on the original source asset when web search is available or property assignment will run.
Route the source through convert-to-usd, or skip conversion for existing USD input and treat the source path as the current USD path.
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.
Run Content Agents material, physics, and optional texture assignment on the converted/minimum-valid USD when requested or required.
Run simready-conform-profile on the latest simulation USD path after property assignment and preserve every selected FET repair report.
Run validation gates in order: omni-asset-validate, omni-asset-validate-geometry, omni-asset-validate-physics, and simready-validate.
Rerun simready-conform-profile when simready-validate reports a repairable requirement, then rerun profile validation on the newest authored USD.
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.
Emit the consolidated workflow report with the final USD path, all stage reports, validation findings, rerun reasons, and next work.

Use the simready-conform-profile reference only after property assignment when property_assignment_intent=run. It routes feature repair to upstream SimReady Foundation FET skills such as simready-foundation-conform-fet-000-core, simready-foundation-conform-fet-001-minimal, simready-foundation-conform-fet-004-simulate-multi-body-physics, and simready-foundation-conform-fet-005-simulate-grasp-physics from branch main.

If simready-validate reports a repairable requirement after the first conformance pass, feed the structured requirement IDs back into the simready-conform-profile reference before writing the final result. In particular, GSP.001 is owned by upstream simready-foundation-conform-fet-005-simulate-grasp-physics; run that skill when a vision-capable agent can inspect visual evidence or explicit grasp points were provided, otherwise record the FET005 step as blocked by missing vision/points instead of treating it as an optional preview task. For RB.MB.001, route the failure to upstream simready-foundation-conform-fet-004-simulate-multi-body-physics. Do not assume multiple visual prims are multiple rigid bodies; inspect UsdPhysics.RigidBodyAPI applications. When the Physics Agent report shows composed topology optimization or the USD has existing component colliders/part roots and the profile validator reports FET004/RB.MB.001, FET004 should promote those existing components into rigid bodies without creating geometry. Do not mark the gate not applicable until after confirming there are fewer than two reusable body candidates.

Output Format

Emit a consolidated workflow report in Markdown, and include JSON when the workflow writes structured artifacts. The report must include:

Overall status: passed, blocked, failed, or needs_rerun.
Request summary: source asset path, detected source format, output root, selected SimReady profile/version, and property assignment intent.
Ordered stage results: stage reference, input artifact, output USD or USDZ path, report path, status, blocker reason, and rerun reason when applicable.
Content Agents readiness and property assignment results with service URLs, tokens, and credentials redacted.
Conformance and validation findings grouped by gate, requirement ID, selected FET repair reference, repair-loop attempt, and final disposition.
Final artifacts: final reported USD path, render preview path when requested, package root and package validation report when packaging ran, Markdown report path, JSON report path when present, and recommended next work.

Detailed References

Read only the references needed for the current request:

references/preflight/README.md: deterministic local setup, manifest/env contract, Linux and Windows wrappers, Content Agents deployment opt-out, and guardrail behavior.
references/workflow.md: inputs, source routing, detailed workflow, validation policy, output report fields, approval points, and next steps.
references/commands.md: concrete portable script command patterns for each stage.
references/assemble-package-source/README.md: two-zone package source assembly, canonical root USD naming, thumbnail placement, and self-contained deliverable checks.

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 .codex/skills and .claude/skills are agent-specific compatibility aliases.

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

The nested references/ tree is intentional. It keeps one public catalog skill while retaining script-bearing atomic stage references, upstream handoff notes, and router documentation under the workflow. Do not flatten those references or promote nested README references to sibling SKILL.md files unless the repo's publishing model changes.

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.
Stop at the first failing deployment, conversion, property-assignment, or conformance authoring gate unless the user explicitly asks for best-effort continuation.
Upstream simready-foundation-conform-fet-005-simulate-grasp-physics needs visual review or explicit grasp points before it can author a meaningful grasp vector.

Troubleshooting

Symptom	Cause	Fix
Downstream reference reports that cad-to-simready preflight has not prepared a component	`PHYSICAL_AI_REQUIRE_PREFLIGHT=1` is set, but the manifest is missing or the required runtime/service is not `ready`	Run `preflight/scripts/preflight.py`, source the generated env file, or explicitly disable service deployment with `--skip-content-agents` only when Content Agents are out of scope.
Workflow stops on `GSP.001` and reports the failure as unclassified	Visual evidence or explicit grasp points were not provided to FET005	Run upstream `simready-foundation-conform-fet-005-simulate-grasp-physics` only after a vision-capable agent has reviewed the asset, or pass explicit grasp points. Otherwise report the FET005 step as `blocked`, not failed.
Validation fails after a meaningful USD artifact already exists	Workflow stopped at the first validation finding	Continue remaining diagnostic gates and mark the result `needs_rerun`. Do not stop at validation findings once a USD artifact has been produced.
Property-assignment stage fails with a missing service endpoint	Content Agents service was not deployed before conversion	Run `deploy-content-agents` first. Do not start asset inspection, conversion, validation, conformance, rendering, or packaging before Content Agents readiness when property assignment will run.
Material Agent reports that rendering produced `0 images` after unit or profile repair	A FET repair, commonly FET001 unit normalization, was applied before Material Agent and changed the USD layering/scene state consumed by the service	Rerun assignment from the converted/minimum-valid USD: Material Agent first, then Physics Agent, then run `simready-conform-profile` and FET repairs on the latest service-authored USD.
Material or Physics Agent local optimized path reports `Permission denied: '/app/.build-resources/scene_optimizer_core/python'`	Local Docker Scene Optimizer bundle permissions prevent the non-root service user from reading the packaged SO runtime	Repair the relevant local container with `docker exec --user root content-material-agent-service chmod -R a+rX /app/.build-resources/scene_optimizer_core` or `docker exec --user root content-physics-agent-service chmod -R a+rX /app/.build-resources/scene_optimizer_core`, then rerun the same optimized agent command. Do not treat the no-optimizer fallback as the root cause for instanced/prototype assets.
`RB.MB.001` fails even though the asset has many prims	The profile counts `UsdPhysics.RigidBodyAPI` prims, not visual or collider prims; Physics Agent may author one root rigid body	Route to upstream `simready-foundation-conform-fet-004-simulate-multi-body-physics`. First ensure Physics Agent used composed-topology optimization when applicable, then promote existing component colliders/part roots when the active profile reports FET004/RB.MB.001 and no geometry must be invented.

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/simready-validate/README.md

SimReady Validate Profile

When to Use

Use this reference after Content Agents assignment, post-assignment simready-conform-profile, validate-usd-minimum, and omni-asset-validate have run, and the user has selected, or needs help selecting, a SimReady Foundation profile. This is a validation-only skill: it reports profile conformance and blockers, but does not repair or stamp assets unless explicitly requested. For end-to-end CAD-to-SimReady workflows where material/physics assignment will run, do not run this reference before Content Agents. The only pre-assignment validation gate should be validate-usd-minimum.

SimReady Foundation organizes validation in four layers:

Requirements: atomic checks such as UN.006 or VG.MESH.001
Capabilities: grouped requirements such as units or geometry
Features: use-case bundles such as FET001_BASE_NEUTRAL
Profiles: named bundles of features such as robotics prop or robot-body profiles

Dependency Check

Require:

Prefer a ready PHYSICAL_AI_PREFLIGHT_MANIFEST from the preflight reference. This wrapper consumes the prepared SimReady Foundation root and simready-validate executable from that manifest before falling back to direct legacy discovery. When PHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set, missing profile-validation readiness blocks at the preflight guardrail.
simready.validate / simready-validate from NVIDIA SimReady Foundation, or a source checkout with requirements.txt or nv_core/validator_sample/requirements.txt
Upstream source: https://github.com/NVIDIA/simready-foundation on branch main
Temporary aarch64 OpenUSD runtime fallback: NVIDIA OpenUSD Exchange SDK package usd-exchange>=2.3.0 from https://github.com/NVIDIA-Omniverse/usd-exchange
SimReady Foundation spec files: capabilities/, features/, and profiles/profiles.toml

Check installed reference dependencies with:

python3 scripts/check_dependencies.py --report dependency-check.json

If --foundation-root, --foundation-spec-root, SIMREADY_FOUNDATION_ROOT, and SIMREADY_FOUNDATION_SPEC_ROOT are not configured and no installed simready.validate specs are available, provide a checkout under $HOME/.physical-ai-skill-hub/upstreams/simready-foundation or $PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT/simready-foundation, checked out to main, and load nv_core/sr_specs/docs plus nv_core/validator_sample from that checkout.

If simready-validate is not on PATH, do not stop there. scripts/run.py must install the runtime from the Foundation checkout's root requirements.txt when present, otherwise from nv_core/validator_sample/requirements.txt, into a dedicated venv and use that executable. Override the venv with PHYSICAL_AI_SIMREADY_VALIDATE_VENV; otherwise the default is $XDG_CACHE_HOME/physical-ai-skill-hub/simready-validate-venv or $HOME/.cache/physical-ai-skill-hub/simready-validate-venv.

Until the upstream Foundation dependency metadata is fixed, Linux aarch64 hosts need one extra guardrail: PyPI usd-core is not available for this architecture, while usd-exchange ships the required OpenUSD Python modules and shared libraries for aarch64. If the normal Foundation requirements.txt install fails because usd-core cannot resolve, scripts/run.py must retry in the same dedicated venv by installing usd-exchange>=2.3.0, omniverse-asset-validator, omniverse-usd-profiles, the non-simready-validate Foundation requirements such as numpy, and then simready-validate itself with --no-deps. Do not report BLOCKED for the aarch64 usd-core resolver failure until this USD Exchange SDK fallback has also failed.

Do not fall back to local profile presets or direct omni_asset_validate feature/capability flags for validation. Report BLOCKED only when the executable is unavailable, no usable Foundation checkout/spec root exists for installation and validation, or both the normal Foundation install and the aarch64 USD Exchange SDK fallback fail.

Target Selection

Supported formal profiles are loaded from SimReady Foundation profiles.toml. The default profile is:

[email protected]

Use --list-profiles to expose selectable profile options before running validation:

simready-validate --list-profiles --foundation-root /path/to/simready-foundation

Recognize these common profile names:

Profile	Use
`Prop-Robotics-Neutral`	Neutral robotics prop profile.
`Prop-Robotics-Physx`	Robotics prop with PhysX rigid-body simulation requirements.
`Prop-Robotics-Isaac`	Isaac Sim-oriented robotics prop profile.
`Robot-Body-Neutral`	Neutral robot body profile.
`Robot-Body-Runnable`	Runnable robot body profile with PhysX/articulation/drive requirements.
`Robot-Body-Isaac`	Isaac Sim robot body profile.

For URDF or MuJoCo robot assets, prefer Robot-Body-Runnable unless the user names another profile. For generic CAD/mesh props, prefer the default Prop-Robotics-Neutral. Use Prop-Robotics-Physx when the user asks for PhysX-specific prop validation.

Instructions

Confirm the asset is an existing USD asset path.
Confirm Content Agents and post-assignment conformance have already run when property assignment is in scope. If the request is explicitly validation-only or property assignment was skipped, record that exception.
Confirm earlier validation has passed, or state that minimum USD and generic Asset Validator checks should run first.
Select a formal SimReady Foundation profile from user intent and asset type.
Resolve the SimReady Foundation source checkout from --foundation-root or SIMREADY_FOUNDATION_ROOT; alternatively resolve specs from --foundation-spec-root or SIMREADY_FOUNDATION_SPEC_ROOT. If no path is configured, use $PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT/simready-foundation or $HOME/.physical-ai-skill-hub/upstreams/simready-foundation, checked out to main.
Run this reference's portable scripts/run.py, which installs simready-validate from the Foundation checkout when the CLI is missing on PATH, uses the temporary USD Exchange SDK runtime fallback on Linux aarch64 when PyPI usd-core cannot resolve, then uses Foundation simready-validate/validator_sample behavior to load Foundation capabilities, features, and profiles/profiles.toml.
Parse profile, feature, requirement, issue, warning, and error results from the Foundation validation runtime.
Inspect the asset topology with OpenUSD. Treat RB.MB.001 as non-blocking when the asset has only one mesh component or one GeomSubset component, because there is no reusable multi-body component structure to promote. Preserve the ignored issue under ignored_issues, add a warning, and pass the profile if no other failures remain.
Fail when any selected profile feature fails or any issue has ERROR or FAILURE severity after applying the single-component RB.MB.001 policy.
Report a structured SimReady profile validation result.

CLI Pattern

Prefer the installed reference-local script for runtime checks:

python3 scripts/run.py asset.usda \
  --profile Prop-Robotics-Neutral \
  --report report.json

SIMREADY_FOUNDATION_ROOT=/path/to/simready-foundation \
  python3 scripts/run.py asset.usda --profile Prop-Robotics-Neutral --report report.json

python3 scripts/run.py asset.usda \
  --profile Robot-Body-Runnable \
  --foundation-root /path/to/simready-foundation \
  --report report.json

Do not use --fix, --stamp, or profile adaptation unless the user explicitly asks for those operations.

When running from outside the reference directory, use the installed reference path:

python3 /path/to/skills/omniverse-cad-to-simready/references/simready-validate/scripts/run.py asset.usda --profile Prop-Robotics-Neutral --report report.json

Output Format

Reports should follow:

scripts/report_schema.json

Include:

asset_path
validator_skill
validator_tool
passed
status
profile_name
profile_target
command
available_profiles
profile_results
feature_results
requirement_counts
issue_counts
issues
ignored_issues
asset_topology
validation_policy
warnings
errors
next_step

Pass/Fail Policy

Fail when:

required validator dependencies are missing
the selected SimReady Foundation profile is unknown or not present in profiles.toml
the Foundation validation runtime returns FAIL or ERROR
any issue has severity ERROR or FAILURE after the single-component RB.MB.001 policy is applied
any selected feature reports failed requirements after the single-component RB.MB.001 policy is applied

Warn when:

the target is narrower than the user's stated use case
profile stamping or adaptation is requested but not available in the runtime
RB.MB.001 is ignored as non-blocking because the USD has only one mesh component or one GeomSubset component

Next Steps

Use this handoff:

Result	Next step
Passes selected profile	Report validation result and preserve the JSON report.
Fails selected profile feature	Send issues to a post-assignment repair loop through `simready-conform-profile`, then rerun this reference on the newest authored USD.
SimReady Foundation runtime blocked	Provide a `simready-foundation` checkout on branch `main` with `--foundation-root` or `SIMREADY_FOUNDATION_ROOT`, then retry so `scripts/run.py` can install the compatible runtime from `requirements.txt`; on Linux aarch64, confirm the USD Exchange SDK fallback was attempted after any `usd-core` resolver failure.

Requirements and compatibility

Written for: OpenAI Codex

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 an API key, Needs Python

The author says: Orchestrator skill. Managed Content Agents deployment requires NVIDIA_API_KEY (build.nvidia.com), Docker + NVIDIA Container Toolkit + GPU, Python 3.12, and an upstream checkout of nvidia-omniverse/content-agents on branch main. 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

OpenAI (Official)

Distributed by

OpenAI

Source

openai/plugins · plugins/nvidia/skills/omniverse-cad-to-simready · commit d420d13

Licence

Apache License 2.0 (redistribution allowed)

LICENSE (written by AutoGineer)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

AutoGineer is not affiliated with or endorsed by Omniverse or OpenAI.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download omniverse-cad-to-simready.zip

From the author

From the skill’s files

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Omniverse

CAD to SimReady

When to Use

Prerequisites

Minimum Viable Scope

First Action

Instructions

Output Format

Detailed References

Publishing Layout Notes

Limitations

Troubleshooting

Hard Rules

Files

references/simready-validate/README.md

SimReady Validate Profile

When to Use

Dependency Check

Target Selection

Instructions

CLI Pattern

Output Format

Pass/Fail Policy

Next Steps

Requirements and compatibility

Security

Attribution and licence

Related skills

Setup TS Deep Modules

To Spec

Improve Codebase Architecture

Domain Modeling

Codebase Design

Prototype

Download ZIP