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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

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/openai/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 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

  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.

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

SymptomCauseFix
Downstream reference reports that cad-to-simready preflight has not prepared a componentPHYSICAL_AI_REQUIRE_PREFLIGHT=1 is set, but the manifest is missing or the required runtime/service is not readyRun 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 unclassifiedVisual evidence or explicit grasp points were not provided to FET005Run 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 existsWorkflow stopped at the first validation findingContinue 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 endpointContent Agents service was not deployed before conversionRun 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 repairA FET repair, commonly FET001 unit normalization, was applied before Material Agent and changed the USD layering/scene state consumed by the serviceRerun 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 runtimeRepair 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 primsThe profile counts UsdPhysics.RigidBodyAPI prims, not visual or collider prims; Physics Agent may author one root rigid bodyRoute 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-conform-profile/README.md

SimReady Conform Profile

When to Use

Use this router reference after USD conversion and property assignment, before simready-validate. It chooses the SimReady feature-level conformance skill that should repair a failing profile requirement.

This reference ships a narrow scripts/run.py router for deterministic Skill Hub handoff and report generation. It should not be treated as the source of truth for canonical FET instructions. The source of truth is the SimReady Foundation repository:

https://github.com/NVIDIA/simready-foundation/tree/main

Do not copy upstream FET skill instructions, requirement summaries, validators, or repair policy into this repo. If browser or raw-file access is unavailable, use a local checkout and read the upstream SKILL.md file directly.

Prerequisites

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

  • A required .usd, .usda, .usdc, or .usdz asset after conversion and property assignment.

  • OpenUSD Python APIs (pxr.Usd, pxr.UsdGeom) for local helper scripts when they are used.

  • A SimReady Foundation checkout at ${SIMREADY_FOUNDATION_ROOT:-$PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT/simready-foundation} or $HOME/.physical-ai-skill-hub/upstreams/simready-foundation, checked out to branch main.

Scope

This reference owns only Skill Hub routing, report handoff, and local helper selection. Upstream SimReady Foundation owns feature-level conformance behavior.

Upstream Skills

Resolve upstream skill files from:

$SIMREADY_FOUNDATION_ROOT/skills/<skill-name>/SKILL.md

Use this mapping when routing validation failures:

Requirement areaUpstream Foundation skill
Core metadata, sidecar JSON, asset naming, and package layout failuressimready-foundation-conform-fet-000-core
Minimal/base-neutral USD feature failuressimready-foundation-conform-fet-001-minimal
Rigid-body physics failuressimready-foundation-conform-fet-003-rigid-body-physics
Multibody physics failuressimready-foundation-conform-fet-004-simulate-multi-body-physics
Prop grasp vector failures for GSP.001simready-foundation-conform-fet-005-simulate-grasp-physics
Material failuressimready-foundation-conform-fet-006-materials
Nonvisual material failuressimready-foundation-conform-fet-007-nonvisual-materials
Robot core profile failuressimready-foundation-conform-fet-021-robot-core
Robot material failuressimready-foundation-conform-fet-023-robot-materials
Base articulation failuressimready-foundation-conform-fet-024-base-articulation

The matching branch URLs are:

https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-000-core/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-001-minimal/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-003-rigid-body-physics/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-004-simulate-multi-body-physics/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-005-simulate-grasp-physics/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-006-materials/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-007-nonvisual-materials/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-021-robot-core/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-023-robot-materials/SKILL.md
https://github.com/NVIDIA/simready-foundation/blob/main/skills/simready-foundation-conform-fet-024-base-articulation/SKILL.md

Local Helper Policy

Some legacy reference-local scripts remain only as narrow report-producing helpers for the Skill Hub workflow. They are not the FET skill source of truth. Before running one, read the matching upstream Foundation skill and make sure the helper still matches the selected profile requirement.

Do not add new copied FET docs to this repo. If a needed repair is fully covered by an upstream Foundation script, run the upstream script from the Foundation checkout instead of adding another local implementation here.

Inputs

Collect:

InputRequirement
usd_assetRequired .usd, .usda, .usdc, or .usdz asset after conversion and property assignment.
output_rootRequired or inferred directory for conformance outputs and reports.
simready_profileSelected SimReady profile. Default to Prop-Robotics-Neutral for generic props unless the user names another profile.
profile_versionSelected profile version. Default to 1.0.0 unless the user names another version.
validation_reportPreferred JSON report from simready-validate, used to identify failing feature and requirement IDs.
source_assetOptional provenance path for metadata.
grasp_target_primOptional prim path for grasp-vector placement.
grasp_pointsOptional explicit grasp vector points.

For .usdz, Core metadata repair may be sidecar-only, but feature repairs that must author USD prims cannot rewrite a sealed package. Report that limitation and ask for or produce an unpacked USD-family asset when prim-level repair is required.

Profile Policy

Default behavior for current profiles:

Profile familyConformance routing
Prop-Robotics-*Route Core failures to simready-foundation-conform-fet-000-core; route GSP.001 or FET005 failures to simready-foundation-conform-fet-005-simulate-grasp-physics; route material and physics failures to their matching upstream FET skills.
Robot-Body-*Route Core failures to simready-foundation-conform-fet-000-core; route robot schema, robot material, articulation, and physics failures to the matching upstream robot or physics FET skills. Do not add prop grasp vectors unless the user explicitly asks or validation identifies a matching requirement.
Unknown or custom profileRun profile validation or inspect the failing feature IDs before choosing upstream FET skills.

Prefer explicit user intent over defaults. Do not guess destructive edits or overwrite source files.

Instructions

  1. Confirm the USD asset exists.

  2. Select the profile and profile version.

  3. Read the relevant upstream Foundation skill before authoring any repair.

  4. Route Core metadata, naming, and layout failures to simready-foundation-conform-fet-000-core.

  5. Inspect the latest staged USD metadata before final profile validation. If metersPerUnit is present but not 1.0, or validation reports UN.007, route to simready-foundation-conform-fet-001-minimal before later feature repairs.

  6. Route the next failing feature to the matching upstream FET skill. For GSP.001, use simready-foundation-conform-fet-005-simulate-grasp-physics because it owns the visual/semantic grasp decision. For RB.MB.001 or FET004_BASE_*, use simready-foundation-conform-fet-004-simulate-multi-body-physics; count actual UsdPhysics.RigidBodyAPI prims and inspect existing component colliders or part roots. If there are at least two reusable candidates, run the FET004 flow instead of marking the profile gate not applicable. If there is only one mesh component or one GeomSubset component, let simready-validate report RB.MB.001 as a non-blocking ignored issue.

  7. Preserve every JSON report and summarize each authoring step as pass, fail, skipped, or blocked.

  8. Stop at the first failed authoring step unless the user asks for best-effort continuation.

  9. Hand off the latest authored USD path to simready-validate.

Command Patterns

Resolve the Foundation checkout before following any FET skill:

export PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT="${PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT:-$HOME/.physical-ai-skill-hub/upstreams}"
export SIMREADY_FOUNDATION_ROOT="${SIMREADY_FOUNDATION_ROOT:-$PHYSICAL_AI_SKILL_HUB_UPSTREAM_ROOT/simready-foundation}"
git -C "$SIMREADY_FOUNDATION_ROOT" checkout main

Read the upstream skill selected by this router:

sed -n '1,220p' "$SIMREADY_FOUNDATION_ROOT/skills/simready-foundation-conform-fet-005-simulate-grasp-physics/SKILL.md"

Run the local router when you already have a validation report, or before final validation to apply deterministic Core and unit repairs:

python3 /path/to/skills/omniverse-cad-to-simready/references/simready-conform-profile/scripts/run.py \
  /path/to/output_dir/physics/output_physics.usd \
  --output-dir /path/to/output_dir/conform/profile \
  --validation-report /path/to/output_dir/validation/simready-profile.json \
  --profile Prop-Robotics-Neutral \
  --profile-version 1.0.0 \
  --source-asset /path/to/source.step \
  --pipeline-step usd-convert-cad \
  --pipeline-step material-agent-client \
  --pipeline-step physics-agent-client \
  --report /path/to/output_dir/conform/profile/simready-conform-profile.json

For GSP.001, pass at least two explicit --grasp-point x,y,z values selected from visual evidence. Without explicit points, the router records FET005 as blocked instead of authoring a placeholder grasp line.

Run upstream scripts from the Foundation checkout when the upstream skill provides them. For example, after visual review has selected explicit grasp points:

uv run --python 3.12 python "$SIMREADY_FOUNDATION_ROOT/skills/simready-foundation-conform-fet-005-simulate-grasp-physics/scripts/author_grasp_line.py" \
  /path/to/output_dir/conform/metadata/asset.usda \
  --output /path/to/output_dir/conform/grasp/asset.usda \
  --name grasp_identifier_01 \
  --point=-0.05,0.0,0.0 \
  --point=0.05,0.0,0.0 \
  --rationale "vision-reviewed graspable region" \
  --report /path/to/output_dir/conform/grasp/author-grasp-line.json

Then validate:

python3 /path/to/skills/omniverse-cad-to-simready/references/simready-validate/scripts/run.py /path/to/output_dir/conform/grasp/asset.usda \
  --profile Prop-Robotics-Neutral \
  --profile-version 1.0.0 \
  --foundation-root "$SIMREADY_FOUNDATION_ROOT" \
  --report /path/to/output_dir/validation/simready-profile.json

Output Format

The workflow summary should include:

FieldMeaning
input_usd_pathUSD path received by this workflow.
output_usd_pathLatest authored USD path after conformance.
simready_profileSelected profile name.
profile_versionSelected profile version.
upstream_skillUpstream Foundation skill name and URL used for each repair.
stepsOrdered FET conformance step results.
reportsPaths to each selected feature repair JSON report.
passedWhether all required conformance steps passed.
next_stepUsually simready-validate.

Limitations

  • This reference does not predict material, physics, or texture properties.

  • This reference does not perform final validation; run simready-validate after conformance authoring.

  • For .usdz, Core metadata repair may be sidecar-only, but feature repairs that must author USD prims cannot rewrite a sealed package.

  • Do not guess destructive edits or overwrite source files.

  • Do not copy upstream SimReady Foundation FET skill docs into this repo.

Troubleshooting

SymptomCauseFix
Foundation skill file is missingSIMREADY_FOUNDATION_ROOT points to the wrong checkout or branchCheck out https://github.com/NVIDIA/simready-foundation at main.
Sealed .usdz cannot be repaired in placeFeature repairs that author USD prims cannot rewrite a sealed packageProduce or request an unpacked USD-family asset before running prim-level repair. Core metadata repair may still proceed sidecar-only.
GSP.001 failure reported as final without classificationVision-capable inspection or explicit grasp points were not availableRoute to upstream simready-foundation-conform-fet-005-simulate-grasp-physics. If neither vision nor explicit points are available, report the FET005 step as blocked.
RB.MB.001 failure reported after Physics AgentThe USD has fewer than two UsdPhysics.RigidBodyAPI prims, even if it has many visual or collider primsRoute to upstream simready-foundation-conform-fet-004-simulate-multi-body-physics when there are at least two existing component colliders or part roots that represent source parts. If the asset has only one mesh component or one GeomSubset component, simready-validate treats RB.MB.001 as non-blocking and preserves it under ignored_issues; do not invent geometry.

Pass/Fail Policy

Fail when:

  • the input USD asset does not exist

  • the selected upstream Foundation skill cannot be found

  • the selected feature repair fails

  • a required conformance step cannot run because the asset format is unsupported

  • the output path would overwrite without explicit --force

Skip when:

  • a profile family does not require a conformance action, such as prop grasp vectors on a robot body profile

  • the user explicitly asks to defer a feature repair such as grasp vectors or metadata

Warn when:

  • the Foundation checkout is not pinned to main

  • profile-specific requirements are unknown and only Core metadata repair was authored

  • a grasp placement needs visual evidence or user-approved explicit points

  • .usdz input prevents in-package grasp vector authoring

Next Steps

After conformance authoring passes, run simready-validate with the selected profile and the same Foundation checkout. If validation still fails, use the failed requirement IDs to decide whether to rerun the upstream FET skill with better parameters or add a new upstream SimReady Foundation skill.

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

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