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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/content-agents/scripts/content_agent_client.py

#!/usr/bin/env python3
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

from __future__ import annotations

import argparse
from email.message import Message
import json
import os
from pathlib import Path
import shutil
import subprocess
import sys
import time
from typing import Any
from urllib.error import HTTPError, URLError
from urllib.parse import urljoin
from urllib.request import Request, urlopen
import uuid

sys.path.insert(0, str(Path(__file__).resolve().parents[3] / "shared"))

from script_utils import check_result as _check, emit_json_report

from content_agent_material_cleanup import cleanup_material_output
from preflight_manifest import load_preflight_manifest, preflight_required, preflight_status_check, ready_service_url


USD_EXTENSIONS = {".usd", ".usda", ".usdc", ".usdz"}
USD_LAYER_EXTENSIONS = {".usd", ".usda", ".usdc"}
TERMINAL_SUCCESS = {"completed", "complete", "succeeded", "success", "done"}
TERMINAL_FAILURE = {"failed", "failure", "cancelled", "canceled", "error"}
MATERIAL_ZERO_IMAGE_MARKERS = (
    "rendering produced 0 images",
    "build_dataset_usd",
)
PHYSICS_OPTIMIZER_FAILURE_MARKERS = (
    "optimize_usd",
    "scene optimizer",
    "local backend unavailable",
    "optimizer_endpoint",
    "nvcf_optimizer_function_id",
)
SCENE_OPTIMIZER_PERMISSION_MARKERS = (
    "permission denied",
    "/app/.build-resources/scene_optimizer_core/python",
)
PHYSICS_SCENE_OPTIMIZER_CONTAINER_CANDIDATES = (
    "content-physics-agent-service",
    "pash-e2e-physics_agent_service",
    "physics_agent_service",
)
MDL_UPLOAD_PREP_SNIPPET = r"""
import json
import shutil
import sys
from pathlib import Path

from pxr import Sdf, Usd

asset_path = Path(sys.argv[1]).resolve()
label = sys.argv[2] if len(sys.argv) > 2 else "content_agents"
info = {
    "staged": False,
    "path": str(asset_path),
    "stripped_mdl_source_assets": 0,
    "cleared_unresolved_service_asset_paths": 0,
    "warning": None,
}

def is_unresolved_service_asset_path(path: str) -> bool:
    lower = path.lower()
    return ".usdz[" in lower and lower.startswith(
        (
            "/var/material-agent/sessions/",
            "/var/physics-agent/sessions/",
            "/var/texture-agent/sessions/",
        )
    )

stage = Usd.Stage.Open(str(asset_path))
if stage is None:
    info["warning"] = f"Could not inspect {label} upload USD for MDL source assets"
    print(json.dumps(info))
    raise SystemExit(0)
mdl_attr_count = 0
service_asset_path_count = 0
for prim in stage.Traverse():
    for attr in prim.GetAttributes():
        try:
            value = attr.Get()
        except Exception:
            continue
        if not isinstance(value, Sdf.AssetPath):
            continue
        path = str(value.path)
        if path.lower().endswith(".mdl"):
            mdl_attr_count += 1
        elif is_unresolved_service_asset_path(path):
            service_asset_path_count += 1
if mdl_attr_count == 0 and service_asset_path_count == 0:
    print(json.dumps(info))
    raise SystemExit(0)
staged_path = asset_path.with_name(f"{asset_path.stem}_{label}_upload{asset_path.suffix.lower()}")
if staged_path.exists():
    staged_path.unlink()
shutil.copy2(asset_path, staged_path)
staged = Usd.Stage.Open(str(staged_path))
if staged is None:
    raise RuntimeError(f"Could not open staged {label} upload USD: {staged_path}")
stripped = 0
cleared_service_paths = 0
for prim in staged.Traverse():
    for attr in prim.GetAttributes():
        try:
            value = attr.Get()
        except Exception:
            continue
        if not isinstance(value, Sdf.AssetPath):
            continue
        path = str(value.path)
        if path.lower().endswith(".mdl"):
            attr.Clear()
            stripped += 1
        elif is_unresolved_service_asset_path(path):
            attr.Clear()
            cleared_service_paths += 1
if (stripped or cleared_service_paths) and not staged.GetRootLayer().Save():
    raise RuntimeError(f"Could not save staged {label} upload USD: {staged_path}")
info.update(
    {
        "staged": True,
        "path": str(staged_path.resolve()),
        "stripped_mdl_source_assets": stripped,
        "cleared_unresolved_service_asset_paths": cleared_service_paths,
        "source_path": str(asset_path),
    }
)
print(json.dumps(info))
"""
USD_TOPOLOGY_INSPECTION_SNIPPET = r"""
import json
import sys
from pathlib import Path

from pxr import Usd, UsdGeom

asset_path = Path(sys.argv[1]).resolve()
result = {
    "inspected": False,
    "reason": None,
    "default_prim_path": None,
    "mesh_count": 0,
    "geom_subset_count": 0,
    "mesh_with_geom_subset_count": 0,
    "instance_count": 0,
    "instance_proxy_count": 0,
    "prototype_count": 0,
    "has_composed_component_topology": False,
    "component_topology_reasons": [],
}
stage = Usd.Stage.Open(str(asset_path))
if stage is None:
    result["reason"] = "Could not open USD stage"
    print(json.dumps(result))
    raise SystemExit(0)
default_prim = stage.GetDefaultPrim()
if not default_prim:
    result["reason"] = "Stage has no default prim"
    print(json.dumps(result))
    raise SystemExit(0)
result["inspected"] = True
result["default_prim_path"] = str(default_prim.GetPath())
try:
    result["prototype_count"] = len(stage.GetPrototypes())
except Exception:
    result["prototype_count"] = 0
mesh_paths_with_subsets = set()
for prim in Usd.PrimRange(default_prim):
    if not prim.IsActive():
        continue
    if prim.IsA(UsdGeom.Mesh):
        result["mesh_count"] += 1
    if prim.IsInstance():
        result["instance_count"] += 1
    if prim.IsInstanceProxy():
        result["instance_proxy_count"] += 1
    is_geom_subset = prim.GetTypeName() == "GeomSubset"
    try:
        is_geom_subset = is_geom_subset or bool(UsdGeom.Subset(prim))
    except Exception:
        pass
    if is_geom_subset:
        result["geom_subset_count"] += 1
        parent = prim.GetParent()
        if parent and parent.IsA(UsdGeom.Mesh):
            mesh_paths_with_subsets.add(str(parent.GetPath()))
result["mesh_with_geom_subset_count"] = len(mesh_paths_with_subsets)
if result["geom_subset_count"]:
    result["component_topology_reasons"].append("geom_subsets")
if result["instance_count"] or result["instance_proxy_count"] or result["prototype_count"]:
    result["component_topology_reasons"].append("instances_or_prototypes")
result["has_composed_component_topology"] = bool(result["component_topology_reasons"])
print(json.dumps(result))
"""

AGENTS: dict[str, dict[str, Any]] = {
    "material-agent-client": {
        "agent_key": "material",
        "agent": "material-agent",
        "default_env": ("CONTENT_AGENTS_MATERIAL_AGENT_BASE_URL", "MATERIAL_AGENT_BASE_URL"),
        "token_env": (
            "CONTENT_AGENTS_MATERIAL_AGENT_TOKEN",
            "MATERIAL_AGENT_TOKEN",
            "CONTENT_AGENTS_TOKEN",
            "NGC_API_KEY",
            "NVCF_API_KEY",
        ),
        "output_endpoint": "output",
        "output_suffix": "_material.usd",
        "output_label": "materialized_usd",
        "optional_artifacts": (
            ("predictions", "predictions", ".jsonl", False),
            ("report", "report", ".html", False),
        ),
        "next_step": "physics-agent-client",
    },
    "physics-agent-client": {
        "agent_key": "physics",
        "agent": "physics-agent",
        "default_env": ("CONTENT_AGENTS_PHYSICS_AGENT_BASE_URL", "PHYSICS_AGENT_BASE_URL"),
        "token_env": (
            "CONTENT_AGENTS_PHYSICS_AGENT_TOKEN",
            "PHYSICS_AGENT_TOKEN",
            "CONTENT_AGENTS_TOKEN",
            "NGC_API_KEY",
            "NVCF_API_KEY",
        ),
        "output_endpoint": "output-usd",
        "output_suffix": "_physics.usd",
        "output_label": "physics_usd",
        "optional_artifacts": (
            ("predictions", "predictions", ".jsonl", False),
            ("dataset", "dataset", ".jsonl", False),
            ("report", "report", ".html", False),
        ),
        "next_step": "simready-conform-profile",
    },
    "texture-agent-client": {
        "agent_key": "texture",
        "agent": "texture-agent",
        "default_env": ("CONTENT_AGENTS_TEXTURE_AGENT_BASE_URL", "TEXTURE_AGENT_BASE_URL"),
        "token_env": (
            "CONTENT_AGENTS_TEXTURE_AGENT_TOKEN",
            "TEXTURE_AGENT_TOKEN",
            "CONTENT_AGENTS_TOKEN",
            "NGC_API_KEY",
            "NVCF_API_KEY",
        ),
        "output_endpoint": "output",
        "output_suffix": "_textured.usdz",
        "output_label": "textured_usdz",
        "optional_artifacts": (
            ("materials", "materials", ".json", False),
            ("textures", "textures", ".zip", False),
            ("renders", "renders", ".zip", False),
        ),
        "next_step": "simready-conform-profile",
    },
}


def _skill_name() -> str:
    return Path(sys.argv[0]).resolve().parents[1].name


def _spec() -> dict[str, Any]:
    skill_name = _skill_name()
    if skill_name not in AGENTS:
        raise RuntimeError(f"Unsupported Content Agents skill directory: {skill_name}")
    return AGENTS[skill_name]


def _env_first(names: tuple[str, ...]) -> str | None:
    for name in names:
        value = os.getenv(name)
        if value:
            return value
    return None


def _env_or_file_first(names: tuple[str, ...]) -> str | None:
    for name in names:
        value = os.getenv(name)
        if value:
            return value
        file_value = os.getenv(f"{name}_FILE")
        if not file_value:
            continue
        try:
            token = Path(file_value).read_text(encoding="utf-8").strip()
        except OSError:
            continue
        if token:
            return token
    return None


def _resolve_base_url(base_url: str | None, spec: dict[str, Any]) -> tuple[str | None, str | None]:
    if base_url:
        return base_url.rstrip("/"), "cli"
    env_base_url = _env_first(spec["default_env"])
    if env_base_url:
        return env_base_url.rstrip("/"), "env_base_url"
    manifest, _, _ = load_preflight_manifest()
    manifest_base_url = ready_service_url(manifest, str(spec["agent_key"]))
    if manifest_base_url:
        return manifest_base_url.rstrip("/"), "preflight_manifest"
    return None, None


def _headers(token: str | None, extra: dict[str, str] | None = None) -> dict[str, str]:
    headers = dict(extra or {})
    if token:
        headers["Authorization"] = f"Bearer {token}"
    return headers


def _http_request(
    method: str,
    url: str,
    *,
    token: str | None = None,
    data: bytes | None = None,
    headers: dict[str, str] | None = None,
    timeout: int = 120,
) -> tuple[int, dict[str, str], bytes]:
    request = Request(url, data=data, headers=_headers(token, headers), method=method)
    try:
        with urlopen(request, timeout=timeout) as response:
            return response.status, dict(response.headers.items()), response.read()
    except HTTPError as exc:
        body = exc.read().decode("utf-8", errors="replace")
        raise RuntimeError(f"HTTP {exc.code} from {url}: {body[:500]}") from exc
    except URLError as exc:
        raise RuntimeError(f"Could not reach {url}: {exc.reason}") from exc
    except (TimeoutError, OSError) as exc:
        raise RuntimeError(f"Could not reach {url}: {exc}") from exc


def _json_request(method: str, url: str, *, token: str | None, timeout: int) -> dict[str, Any]:
    _, _, body = _http_request(method, url, token=token, timeout=timeout)
    payload = json.loads(body.decode("utf-8"))
    return payload if isinstance(payload, dict) else {"value": payload}


def _multipart_body(asset_path: Path, fields: dict[str, str]) -> tuple[bytes, str]:
    boundary = f"----physical-ai-skill-{uuid.uuid4().hex}"
    chunks: list[bytes] = []
    for name, value in fields.items():
        chunks.extend(
            [
                f"--{boundary}\r\n".encode("utf-8"),
                f'Content-Disposition: form-data; name="{name}"\r\n\r\n'.encode("utf-8"),
                str(value).encode("utf-8"),
                b"\r\n",
            ]
        )
    chunks.extend(
        [
            f"--{boundary}\r\n".encode("utf-8"),
            f'Content-Disposition: form-data; name="usd_file"; filename="{asset_path.name}"\r\n'.encode("utf-8"),
            b"Content-Type: application/octet-stream\r\n\r\n",
            asset_path.read_bytes(),
            b"\r\n",
            f"--{boundary}--\r\n".encode("utf-8"),
        ]
    )
    return b"".join(chunks), f"multipart/form-data; boundary={boundary}"


def _post_pipeline(asset_path: Path, base_url: str, token: str | None, fields: dict[str, str], timeout: int) -> str:
    body, content_type = _multipart_body(asset_path, fields)
    _, _, response_body = _http_request(
        "POST",
        urljoin(f"{base_url.rstrip('/')}/", "pipeline"),
        token=token,
        data=body,
        headers={"Content-Type": content_type},
        timeout=timeout,
    )
    payload = json.loads(response_body.decode("utf-8"))
    session_id = payload.get("session_id")
    if not session_id:
        raise RuntimeError("Content Agents service did not return session_id")
    return str(session_id)


def _layer_identifier(layer: Any) -> str:
    return str(getattr(layer, "realPath", None) or getattr(layer, "identifier", "") or "")


def _prepare_upload_asset(asset_path: Path, output_directory: Path) -> tuple[Path, dict[str, Any]]:
    upload_info: dict[str, Any] = {
        "asset_path": str(asset_path),
        "dependency_layers": [],
        "dependency_assets": [],
        "dependency_count": 0,
        "inspection_error": None,
        "packaging": "none",
        "package_size_bytes": None,
        "path": str(asset_path),
        "unresolved_paths": [],
    }
    if asset_path.suffix.lower() == ".usdz":
        upload_info["packaging"] = "already_usdz"
        return asset_path, upload_info

    try:
        from pxr import UsdUtils
    except Exception as exc:
        upload_info["inspection_error"] = f"OpenUSD dependency inspection is unavailable: {exc}"
        return asset_path, upload_info

    try:
        layers, assets, unresolved_paths = UsdUtils.ComputeAllDependencies(str(asset_path))
    except Exception as exc:
        upload_info["inspection_error"] = f"Could not inspect USD dependencies: {exc}"
        return asset_path, upload_info

    root_path = asset_path.resolve()
    dependency_layers: list[str] = []
    for layer in layers:
        identifier = _layer_identifier(layer)
        if not identifier:
            continue
        try:
            if Path(identifier).resolve() == root_path:
                continue
        except OSError:
            pass
        dependency_layers.append(identifier)

    dependency_assets = [str(asset) for asset in assets]
    unresolved = [str(path) for path in unresolved_paths]
    upload_info["dependency_layers"] = dependency_layers
    upload_info["dependency_assets"] = dependency_assets
    upload_info["unresolved_paths"] = unresolved
    upload_info["dependency_count"] = len(dependency_layers) + len(dependency_assets)

    if unresolved:
        raise RuntimeError("Cannot package USD for Content Agents upload; unresolved dependencies: " + ", ".join(unresolved))
    if upload_info["dependency_count"] == 0:
        return asset_path, upload_info

    output_directory.mkdir(parents=True, exist_ok=True)
    package_path = output_directory / f"{asset_path.stem}_content_agents_upload.usdz"
    if package_path.exists():
        package_path.unlink()
    ok = UsdUtils.CreateNewUsdzPackage(str(asset_path), str(package_path))
    if not ok or not package_path.exists() or package_path.stat().st_size == 0:
        raise RuntimeError(f"OpenUSD failed to package USD dependencies for Content Agents upload: {package_path}")

    upload_info["packaging"] = "usdz"
    upload_info["path"] = str(package_path.resolve())
    upload_info["package_size_bytes"] = package_path.stat().st_size
    return package_path, upload_info


def _is_unresolved_service_asset_path(path: str) -> bool:
    lower = path.lower()
    return ".usdz[" in lower and lower.startswith(
        (
            "/var/material-agent/sessions/",
            "/var/physics-agent/sessions/",
            "/var/texture-agent/sessions/",
        )
    )


def _stage_mdl_safe_upload_asset(asset_path: Path, label: str) -> tuple[Path, dict[str, Any]]:
    info: dict[str, Any] = {
        "staged": False,
        "path": str(asset_path),
        "stripped_mdl_source_assets": 0,
        "cleared_unresolved_service_asset_paths": 0,
        "warning": None,
    }
    if asset_path.suffix.lower() not in USD_LAYER_EXTENSIONS:
        return asset_path, info

    try:
        from pxr import Sdf, Usd
    except Exception as exc:
        staged_path, external_info = _stage_mdl_safe_upload_asset_external(asset_path, label)
        if external_info.get("staged") or not external_info.get("warning"):
            return staged_path, external_info
        info["warning"] = (
            f"OpenUSD Python APIs are unavailable for {label} upload prep: {exc}. "
            + str(external_info.get("warning") or "No alternate OpenUSD Python runtime staged the upload.")
        )
        return asset_path, info

    try:
        stage = Usd.Stage.Open(str(asset_path))
    except Exception as exc:
        info["warning"] = f"Could not inspect {label} upload USD for MDL source assets: {exc}"
        return asset_path, info
    if stage is None:
        info["warning"] = f"Could not inspect {label} upload USD for MDL source assets"
        return asset_path, info

    mdl_attrs: list[str] = []
    service_asset_attrs: list[str] = []
    for prim in stage.Traverse():
        for attr in prim.GetAttributes():
            try:
                value = attr.Get()
            except Exception:
                continue
            if not isinstance(value, Sdf.AssetPath):
                continue
            path = str(value.path)
            if path.lower().endswith(".mdl"):
                mdl_attrs.append(str(attr.GetPath()))
            elif _is_unresolved_service_asset_path(path):
                service_asset_attrs.append(str(attr.GetPath()))
    if not mdl_attrs and not service_asset_attrs:
        return asset_path, info

    staged_path = asset_path.with_name(f"{asset_path.stem}_{label}_upload{asset_path.suffix.lower()}")
    try:
        if staged_path.exists():
            staged_path.unlink()
        shutil.copy2(asset_path, staged_path)
        staged = Usd.Stage.Open(str(staged_path))
        if staged is None:
            raise RuntimeError(f"Could not open staged {label} upload USD: {staged_path}")
        stripped = 0
        cleared_service_paths = 0
        for prim in staged.Traverse():
            for attr in prim.GetAttributes():
                try:
                    value = attr.Get()
                except Exception:
                    continue
                if not isinstance(value, Sdf.AssetPath):
                    continue
                path = str(value.path)
                if path.lower().endswith(".mdl"):
                    attr.Clear()
                    stripped += 1
                elif _is_unresolved_service_asset_path(path):
                    attr.Clear()
                    cleared_service_paths += 1
        if (stripped or cleared_service_paths) and not staged.GetRootLayer().Save():
            raise RuntimeError(f"Could not save staged {label} upload USD: {staged_path}")
    except Exception as exc:
        staged_path.unlink(missing_ok=True)
        info["warning"] = f"Could not stage {label} upload USD without MDL source assets: {exc}"
        return asset_path, info

    info.update(
        {
            "staged": True,
            "path": str(staged_path.resolve()),
            "stripped_mdl_source_assets": stripped,
            "cleared_unresolved_service_asset_paths": cleared_service_paths,
            "source_path": str(asset_path),
        }
    )
    return staged_path, info


def _stage_mdl_safe_upload_asset_external(asset_path: Path, label: str) -> tuple[Path, dict[str, Any]]:
    uv = shutil.which("uv")
    info: dict[str, Any] = {
        "staged": False,
        "path": str(asset_path),
        "stripped_mdl_source_assets": 0,
        "warning": None,
    }
    if not uv:
        info["warning"] = "uv was not found on PATH for alternate OpenUSD Python upload prep"
        return asset_path, info
    command = [uv, "run", "--python", "3.12", "python", "-c", MDL_UPLOAD_PREP_SNIPPET, str(asset_path), label]
    try:
        completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=120, check=False)
    except Exception as exc:
        info["warning"] = f"Alternate OpenUSD Python upload prep failed to launch: {exc}"
        return asset_path, info
    if completed.returncode != 0:
        detail = (completed.stderr or completed.stdout or "").strip()
        info["warning"] = f"Alternate OpenUSD Python upload prep failed: {detail[:500]}"
        return asset_path, info
    try:
        payload = json.loads(completed.stdout)
    except json.JSONDecodeError as exc:
        info["warning"] = f"Alternate OpenUSD Python upload prep returned invalid JSON: {exc}"
        return asset_path, info
    if not isinstance(payload, dict):
        info["warning"] = "Alternate OpenUSD Python upload prep returned a non-object payload"
        return asset_path, info
    if payload.get("staged") and payload.get("path"):
        return Path(str(payload["path"])), payload
    return asset_path, payload


def _stage_physics_upload_asset(asset_path: Path) -> tuple[Path, dict[str, Any]]:
    return _stage_mdl_safe_upload_asset(asset_path, "physics")


def _stage_material_upload_asset(asset_path: Path) -> tuple[Path, dict[str, Any]]:
    return _stage_mdl_safe_upload_asset(asset_path, "material")


def _inspect_usd_topology_external(asset_path: Path) -> dict[str, Any]:
    uv = shutil.which("uv")
    if not uv:
        return {"inspected": False, "reason": "uv was not found on PATH for alternate OpenUSD Python inspection"}
    command = [uv, "run", "--python", "3.12", "python", "-c", USD_TOPOLOGY_INSPECTION_SNIPPET, str(asset_path)]
    try:
        completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=120, check=False)
    except Exception as exc:
        return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection failed to launch: {exc}"}
    if completed.returncode != 0:
        detail = (completed.stderr or completed.stdout or "").strip()
        return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection failed: {detail[:500]}"}
    try:
        payload = json.loads(completed.stdout)
    except json.JSONDecodeError as exc:
        return {"inspected": False, "reason": f"Alternate OpenUSD Python inspection returned invalid JSON: {exc}"}
    return payload if isinstance(payload, dict) else {"inspected": False, "reason": "Alternate OpenUSD Python inspection returned a non-object payload"}


def _wait_for_status(
    base_url: str,
    token: str | None,
    session_id: str,
    *,
    timeout: int,
    poll_interval: float,
    request_timeout: int,
) -> dict[str, Any]:
    deadline = time.monotonic() + timeout
    last_status: dict[str, Any] = {}
    transient_errors: list[str] = []
    status_url = urljoin(f"{base_url.rstrip('/')}/", f"pipeline/{session_id}/status")
    while True:
        try:
            last_status = _json_request("GET", status_url, token=token, timeout=request_timeout)
        except Exception as exc:
            if not _is_transient_status_poll_error(exc):
                raise
            transient_errors.append(str(exc))
            if time.monotonic() >= deadline:
                raise TimeoutError(
                    f"Timed out waiting for Content Agents session {session_id}; "
                    f"last transient status poll error: {exc}"
                ) from exc
            time.sleep(max(0.0, poll_interval))
            continue
        state = str(last_status.get("status", "")).lower()
        if state in TERMINAL_SUCCESS or state in TERMINAL_FAILURE:
            if transient_errors:
                last_status["poll_warnings"] = transient_errors[-10:]
            return last_status
        if time.monotonic() >= deadline:
            raise TimeoutError(f"Timed out waiting for Content Agents session {session_id}")
        time.sleep(max(0.0, poll_interval))


def _is_transient_status_poll_error(exc: Exception) -> bool:
    message = str(exc).lower()
    if message.startswith("could not reach "):
        return True
    if message.startswith("http 5") or message.startswith("http 408") or message.startswith("http 429"):
        return True
    return any(
        marker in message
        for marker in (
            "timed out",
            "timeout",
            "temporarily unavailable",
            "connection reset",
            "connection aborted",
            "remote end closed connection",
            "ssl",
        )
    )


def _is_transient_artifact_error(exc: Exception) -> bool:
    message = str(exc).lower()
    if message.startswith("http 404") and ("not available" in message or "not found" in message):
        return True
    if message.startswith("http 5") or message.startswith("http 408") or message.startswith("http 429"):
        return True
    return any(
        marker in message
        for marker in (
            "timed out",
            "timeout",
            "temporarily unavailable",
            "connection reset",
            "connection aborted",
            "remote end closed connection",
            "ssl",
        )
    )


def _filename_from_content_disposition(value: str | None) -> str | None:
    if not value:
        return None
    message = Message()
    message["content-disposition"] = value
    filename = message.get_filename()
    return Path(filename).name if filename else None


def _download_artifact(
    base_url: str,
    token: str | None,
    session_id: str,
    artifact_name: str,
    endpoint: str,
    output_path: Path,
    required: bool,
    timeout: int,
    *,
    allow_response_usd_suffix: bool = False,
    wait_timeout: float = 0.0,
    poll_interval: float = 2.0,
) -> dict[str, Any]:
    url = urljoin(f"{base_url.rstrip('/')}/", f"artifacts/{session_id}/{endpoint}")
    deadline = time.monotonic() + max(0.0, wait_timeout)
    attempts = 0
    while True:
        attempts += 1
        try:
            _, headers, body = _http_request("GET", url, token=token, timeout=timeout)
            filename = _filename_from_content_disposition(
                headers.get("Content-Disposition") or headers.get("content-disposition")
            )
            if allow_response_usd_suffix and filename:
                suffix = Path(filename).suffix.lower()
                if suffix in USD_EXTENSIONS:
                    output_path = output_path.with_suffix(suffix)
            output_path.parent.mkdir(parents=True, exist_ok=True)
            output_path.write_bytes(body)
            return {
                "name": artifact_name,
                "url": url,
                "path": str(output_path),
                "required": required,
                "downloaded": True,
                "content_type": headers.get("Content-Type") or headers.get("content-type"),
                "error": None,
                "attempts": attempts,
                "retry_count": attempts - 1,
            }
        except Exception as exc:
            should_retry = (
                required
                and wait_timeout > 0
                and time.monotonic() < deadline
                and _is_transient_artifact_error(exc)
            )
            if should_retry:
                time.sleep(max(0.25, poll_interval))
                continue
            return {
                "name": artifact_name,
                "url": url,
                "path": str(output_path),
                "required": required,
                "downloaded": False,
                "content_type": None,
                "error": str(exc),
                "attempts": attempts,
                "retry_count": attempts - 1,
            }


def _required_output_path(agent_key: str, spec: dict[str, Any], asset_path: Path, output_directory: Path) -> Path:
    if agent_key == "physics" and asset_path.suffix.lower() in USD_EXTENSIONS:
        return output_directory / f"{asset_path.stem}_physics{asset_path.suffix.lower()}"
    return output_directory / f"{asset_path.stem}{spec['output_suffix']}"


def _service_fields(args: argparse.Namespace, agent_key: str) -> dict[str, str]:
    fields: dict[str, str] = {}
    if agent_key == "material":
        email = args.email or os.getenv("USER_EMAIL")
        if email:
            fields["user_email"] = email
        if args.prompt:
            fields["user_prompt"] = args.prompt
        fields["optimize_usd"] = "true" if args.optimize_usd else "false"
        if not args.optimize_usd:
            fields["skip_instances"] = "true" if args.skip_instances else "false"
        elif args.skip_instances:
            fields["skip_instances"] = "true"
        if args.skip_prototypes:
            fields["skip_prototypes"] = "true"
        if args.skip_existing_materials:
            fields["skip_existing_materials"] = "true"
        if args.layer_only:
            fields["layer_only"] = "true"
    elif agent_key == "physics":
        if args.prompt:
            fields["user_prompt"] = args.prompt
        if args.render_backend:
            fields["render_backend"] = args.render_backend
        fields["optimize_usd"] = "true" if args.optimize_usd else "false"
        fields["enable_deinstance"] = "true" if args.enable_deinstance else "false"
        fields["enable_split"] = "true" if args.enable_split else "false"
    elif agent_key == "texture":
        if args.prompt:
            fields["user_prompt"] = args.prompt
        if args.material_textures:
            fields["material_textures_json"] = args.material_textures
    return fields


def _inspect_usd_topology(asset_path: Path) -> dict[str, Any]:
    result: dict[str, Any] = {
        "inspected": False,
        "reason": None,
        "default_prim_path": None,
        "mesh_count": 0,
        "geom_subset_count": 0,
        "mesh_with_geom_subset_count": 0,
        "instance_count": 0,
        "instance_proxy_count": 0,
        "prototype_count": 0,
        "has_composed_component_topology": False,
        "component_topology_reasons": [],
    }
    try:
        from pxr import Usd, UsdGeom
    except Exception as exc:
        external = _inspect_usd_topology_external(asset_path)
        if external.get("inspected"):
            external["inspection_runtime"] = "uv-python-3.12"
            return external
        result["reason"] = (
            f"OpenUSD Python APIs are unavailable: {exc}. "
            + str(external.get("reason") or "No alternate OpenUSD Python runtime inspected the stage.")
        )
        return result

    try:
        stage = Usd.Stage.Open(str(asset_path))
    except Exception as exc:
        result["reason"] = f"Could not open USD stage: {exc}"
        return result
    if stage is None:
        result["reason"] = "Could not open USD stage"
        return result

    default_prim = stage.GetDefaultPrim()
    if not default_prim:
        result["reason"] = "Stage has no default prim"
        return result

    result["inspected"] = True
    result["default_prim_path"] = str(default_prim.GetPath())
    try:
        result["prototype_count"] = len(stage.GetPrototypes())
    except Exception:
        result["prototype_count"] = 0

    mesh_paths_with_subsets: set[str] = set()
    for prim in Usd.PrimRange(default_prim):
        if not prim.IsActive():
            continue
        if prim.IsA(UsdGeom.Mesh):
            result["mesh_count"] += 1
        if prim.IsInstance():
            result["instance_count"] += 1
        if prim.IsInstanceProxy():
            result["instance_proxy_count"] += 1

        is_geom_subset = prim.GetTypeName() == "GeomSubset"
        try:
            is_geom_subset = is_geom_subset or bool(UsdGeom.Subset(prim))
        except Exception:
            pass
        if is_geom_subset:
            result["geom_subset_count"] += 1
            parent = prim.GetParent()
            if parent and parent.IsA(UsdGeom.Mesh):
                mesh_paths_with_subsets.add(str(parent.GetPath()))

    result["mesh_with_geom_subset_count"] = len(mesh_paths_with_subsets)
    if result["geom_subset_count"]:
        result["component_topology_reasons"].append("geom_subsets")
    if result["instance_count"] or result["instance_proxy_count"] or result["prototype_count"]:
        result["component_topology_reasons"].append("instances_or_prototypes")
    result["has_composed_component_topology"] = bool(result["component_topology_reasons"])
    return result


def _apply_physics_auto_optimizer(args: argparse.Namespace, topology: dict[str, Any]) -> dict[str, Any]:
    auto_enabled = bool(args.auto_optimize_composed_usd and topology.get("has_composed_component_topology"))
    if auto_enabled:
        args.optimize_usd = True
        args.enable_deinstance = True
        args.enable_split = True
    return {
        "auto_optimize_composed_usd": bool(args.auto_optimize_composed_usd),
        "auto_enabled": auto_enabled,
        "auto_reasons": list(topology.get("component_topology_reasons") or []),
        "optimize_usd": bool(args.optimize_usd),
        "enable_deinstance": bool(args.enable_deinstance),
        "enable_split": bool(args.enable_split),
    }


def _apply_material_auto_optimizer(args: argparse.Namespace, topology: dict[str, Any]) -> dict[str, Any]:
    requested_optimize_usd = args.optimize_usd
    optimize_usd = True if requested_optimize_usd is None else bool(requested_optimize_usd)
    auto_reasons: list[str] = []
    instance_only_geometry = bool(
        topology.get("inspected")
        and topology.get("mesh_count") == 0
        and (
            topology.get("instance_count")
            or topology.get("instance_proxy_count")
            or topology.get("prototype_count")
        )
    )
    auto_disabled_optimizer = bool(
        requested_optimize_usd is None
        and instance_only_geometry
        and not args.skip_instances
    )
    if auto_disabled_optimizer:
        optimize_usd = False
        auto_reasons.append("instance_only_geometry")
    args.optimize_usd = optimize_usd
    return {
        "requested_optimize_usd": requested_optimize_usd,
        "default_optimize_usd": requested_optimize_usd is None,
        "auto_disabled_optimizer": auto_disabled_optimizer,
        "auto_reasons": auto_reasons,
        "optimize_usd": bool(args.optimize_usd),
        "skip_instances": bool(args.skip_instances),
        "skip_prototypes": bool(args.skip_prototypes),
        "skip_existing_materials": bool(args.skip_existing_materials),
    }


def _is_crate_usd(path: Path) -> bool:
    try:
        return path.read_bytes()[:8] == b"PXR-USDC"
    except OSError:
        return False


def _convert_physics_output_to_usd(source_path: Path, output_path: Path) -> tuple[bool, str, Path]:
    if _is_crate_usd(source_path) and source_path.suffix.lower() == ".usd":
        return True, f"Physics output is already crate-backed USD: {source_path}", source_path
    try:
        from pxr import Usd
    except Exception as exc:
        return False, f"OpenUSD Python APIs are unavailable: {exc}", output_path
    stage = Usd.Stage.Open(str(source_path))
    if stage is None:
        return False, f"Could not open physics output stage for crate conversion: {source_path}", output_path
    output_path.parent.mkdir(parents=True, exist_ok=True)
    if not stage.GetRootLayer().Export(str(output_path)):
        return False, f"OpenUSD failed to export crate USD: {output_path}", output_path
    if not output_path.exists() or output_path.stat().st_size == 0:
        return False, f"OpenUSD export did not produce a non-empty file: {output_path}", output_path
    return True, f"Converted physics output to {output_path}", output_path


def _walk_text(value: Any) -> list[str]:
    if value is None:
        return []
    if isinstance(value, dict):
        text: list[str] = []
        for key, item in value.items():
            text.append(str(key))
            text.extend(_walk_text(item))
        return text
    if isinstance(value, list | tuple | set):
        text = []
        for item in value:
            text.extend(_walk_text(item))
        return text
    return [str(value)]


def _report_text(report: dict[str, Any]) -> str:
    fields = [
        report.get("errors"),
        report.get("warnings"),
        report.get("checks"),
        report.get("service_status"),
        report.get("service_results"),
        report.get("usd_topology"),
        report.get("material_optimizer"),
    ]
    return "\n".join(part for field in fields for part in _walk_text(field)).lower()


def _is_material_zero_image_failure(report: dict[str, Any]) -> bool:
    text = _report_text(report)
    return MATERIAL_ZERO_IMAGE_MARKERS[0] in text or (MATERIAL_ZERO_IMAGE_MARKERS[1] in text and "0 images" in text)


def _attempt_summary(report: dict[str, Any], label: str) -> dict[str, Any]:
    return {
        "label": label,
        "passed": bool(report.get("passed")),
        "status": report.get("status"),
        "session_id": report.get("session_id"),
        "output_usd_path": report.get("output_usd_path"),
        "upload_asset_path": report.get("upload_asset_path"),
        "upload_packaging": report.get("upload_packaging"),
        "material_upload_info": report.get("material_upload_info"),
        "material_output_cleanup": report.get("material_output_cleanup"),
        "material_optimizer": report.get("material_optimizer"),
        "physics_upload_info": report.get("physics_upload_info"),
        "physics_optimizer": report.get("physics_optimizer"),
        "service_status": report.get("service_status"),
        "service_results": report.get("service_results"),
        "errors": list(report.get("errors") or []),
        "warnings": list(report.get("warnings") or []),
    }


def _maybe_retry_material_without_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
    if report.get("skill") != "material-agent-client":
        return None
    if getattr(args, "_material_zero_image_retry_attempt", False):
        return None
    if args.optimize_usd is not True:
        return None
    if not _is_material_zero_image_failure(report):
        return None

    retry_args = argparse.Namespace(**vars(args))
    retry_args.optimize_usd = False
    retry_args.skip_instances = False
    retry_args._material_zero_image_retry_attempt = True
    retry_report = run(retry_args)
    existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
    retry_report["attempts"] = [
        _attempt_summary(report, "initial_optimize_usd_true"),
        *existing_attempts,
        _attempt_summary(retry_report, "retry_optimize_usd_false"),
    ]
    retry_report.setdefault("warnings", []).append(
        "Retried Material Agent with optimize_usd=false and skip_instances=false after a zero-render optimized path failure."
    )
    if not retry_report.get("passed"):
        retry_report.setdefault("errors", []).append(
            "Material Agent zero-render retry with optimize_usd=false did not recover the run."
        )
    return retry_report


def _is_physics_optimizer_failure(report: dict[str, Any]) -> bool:
    service_status = report.get("service_status")
    if isinstance(service_status, dict):
        current_step = service_status.get("current_step")
        if isinstance(current_step, dict):
            step_text = "\n".join(_walk_text(current_step)).lower()
            if "optimize_usd" in step_text:
                return True
        completed_steps = service_status.get("completed_steps")
        if isinstance(completed_steps, list) and not completed_steps and str(service_status.get("status", "")).lower() in TERMINAL_FAILURE:
            text = _report_text(report)
            if "content agents session status: failed" in text and "optimize_usd" in text:
                return True
    text = _report_text(report)
    return "optimize_usd" in text and any(marker in text for marker in PHYSICS_OPTIMIZER_FAILURE_MARKERS[1:])


def _is_scene_optimizer_permission_failure(report: dict[str, Any]) -> bool:
    text = _report_text(report)
    return _is_physics_optimizer_failure(report) and all(marker in text for marker in SCENE_OPTIMIZER_PERMISSION_MARKERS)


def _should_attempt_physics_scene_optimizer_repair(report: dict[str, Any]) -> bool:
    if _is_scene_optimizer_permission_failure(report):
        return True
    topology = report.get("usd_topology")
    return bool(
        _is_physics_optimizer_failure(report)
        and isinstance(topology, dict)
        and topology.get("has_composed_component_topology")
    )


def _physics_scene_optimizer_container_candidates() -> list[str]:
    candidates: list[str] = []
    for name in ("CONTENT_AGENTS_PHYSICS_AGENT_CONTAINER", "PHYSICS_AGENT_CONTAINER"):
        value = os.getenv(name)
        if value:
            candidates.append(value)
    candidates.extend(PHYSICS_SCENE_OPTIMIZER_CONTAINER_CANDIDATES)
    return list(dict.fromkeys(candidates))


def _repair_physics_scene_optimizer_permissions() -> dict[str, Any]:
    docker = shutil.which("docker")
    result: dict[str, Any] = {
        "attempted": bool(docker),
        "repaired": False,
        "container": None,
        "command": None,
        "errors": [],
    }
    if not docker:
        result["errors"].append("docker was not found on PATH")
        return result

    for container in _physics_scene_optimizer_container_candidates():
        command = [
            docker,
            "exec",
            "--user",
            "root",
            container,
            "chmod",
            "-R",
            "a+rX",
            "/app/.build-resources/scene_optimizer_core",
        ]
        completed = subprocess.run(command, text=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=60, check=False)
        if completed.returncode == 0:
            result.update(
                {
                    "attempted": True,
                    "repaired": True,
                    "container": container,
                    "command": ["docker", *command[1:]],
                }
            )
            return result
        detail = (completed.stderr or completed.stdout or "").strip()
        result["errors"].append(f"{container}: exit {completed.returncode}: {detail[:300]}")
    return result


def _maybe_repair_and_retry_physics_scene_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
    if report.get("skill") != "physics-agent-client":
        return None
    if getattr(args, "_physics_so_permission_repair_attempt", False):
        return None
    if args.optimize_usd is not True:
        return None
    if not _should_attempt_physics_scene_optimizer_repair(report):
        return None

    repair = _repair_physics_scene_optimizer_permissions()
    report["physics_scene_optimizer_permission_repair"] = repair
    if not repair.get("repaired"):
        report.setdefault("warnings", []).append(
            "Could not repair local Physics Agent Scene Optimizer permissions; keeping the optimized failure as the primary result."
        )
        return None

    retry_args = argparse.Namespace(**vars(args))
    retry_args._physics_so_permission_repair_attempt = True
    retry_report = run(retry_args)
    existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
    retry_report["attempts"] = [
        _attempt_summary(report, "initial_physics_optimize_usd_true"),
        *existing_attempts,
        _attempt_summary(retry_report, "retry_physics_optimize_usd_true_after_so_permission_repair"),
    ]
    retry_report["physics_scene_optimizer_permission_repair"] = repair
    retry_report.setdefault("warnings", []).append(
        "Repaired local Physics Agent Scene Optimizer permissions and retried with optimize_usd still enabled."
    )
    if not retry_report.get("passed"):
        retry_report.setdefault("errors", []).append(
            "Physics Agent retry after Scene Optimizer permission repair did not recover the run."
        )
    return retry_report


def _maybe_retry_physics_without_optimizer(report: dict[str, Any], args: argparse.Namespace) -> dict[str, Any] | None:
    if report.get("skill") != "physics-agent-client":
        return None
    if getattr(args, "_physics_optimizer_retry_attempt", False):
        return None
    if args.optimize_usd is not True:
        return None
    if not _is_physics_optimizer_failure(report):
        return None
    topology = report.get("usd_topology")
    if isinstance(topology, dict) and topology.get("has_composed_component_topology"):
        report.setdefault("warnings", []).append(
            "Skipped optimize_usd=false Physics Agent retry because composed USD topology still needs optimizer deinstance/split before apply_physics."
        )
        return None

    retry_args = argparse.Namespace(**vars(args))
    retry_args.optimize_usd = False
    retry_args.enable_deinstance = False
    retry_args.enable_split = False
    retry_args.auto_optimize_composed_usd = False
    retry_args._physics_optimizer_retry_attempt = True
    retry_report = run(retry_args)
    existing_attempts = retry_report.get("attempts") if isinstance(retry_report.get("attempts"), list) else []
    retry_report["attempts"] = [
        _attempt_summary(report, "initial_physics_optimize_usd_true"),
        *existing_attempts,
        _attempt_summary(retry_report, "retry_physics_optimize_usd_false"),
    ]
    retry_report.setdefault("warnings", []).append(
        "Retried Physics Agent with optimize_usd=false, enable_deinstance=false, and enable_split=false after the optimized path failed."
    )
    if not retry_report.get("passed"):
        retry_report.setdefault("errors", []).append(
            "Physics Agent retry with optimize_usd=false did not recover the run."
        )
    return retry_report


def _report_markdown(report: dict[str, Any]) -> str:
    lines = [
        f"# {report['skill']} Report",
        "",
        f"- Asset: `{report['asset_path']}`",
        f"- Agent: `{report['agent']}`",
        f"- Passed: `{report['passed']}`",
        f"- Status: `{report['status']}`",
        f"- Session: `{report.get('session_id')}`",
        f"- Output USD: `{report.get('output_usd_path')}`",
        f"- Next step: `{report['next_step']}`",
        "",
        "## Checks",
        "",
    ]
    for check in report["checks"]:
        state = "PASS" if check["passed"] else "FAIL"
        lines.append(f"- `{state}` `{check['name']}`: {check['message']}")
    lines.extend(["", "## Artifacts", ""])
    for artifact in report.get("artifacts", []):
        state = "downloaded" if artifact["downloaded"] else "missing"
        lines.append(f"- `{artifact['name']}`: {state} `{artifact.get('path')}`")
    if not report.get("artifacts"):
        lines.append("- None")
    if report.get("errors"):
        lines.extend(["", "## Errors", ""])
        lines.extend(f"- {error}" for error in report["errors"])
    if report.get("warnings"):
        lines.extend(["", "## Warnings", ""])
        lines.extend(f"- {warning}" for warning in report["warnings"])
    cleanup = report.get("material_output_cleanup")
    if isinstance(cleanup, dict):
        lines.extend(["", "## Material Output Cleanup", ""])
        if cleanup.get("skipped_reason"):
            lines.append(f"- Skipped: {cleanup['skipped_reason']}")
        elif cleanup.get("warning"):
            lines.append(f"- Warning: {cleanup['warning']}")
        else:
            lines.append(f"- Removed stale material count: `{cleanup.get('removed_material_count', 0)}`")
            lines.append(f"- Repaired bound shader count: `{cleanup.get('repaired_bound_shader_count', 0)}`")
            for material in cleanup.get("removed_materials") or []:
                lines.append(f"- Removed `{material}`")
    lines.append("")
    return "\n".join(lines)


def _emit_report(report: dict[str, Any], report_path: Path | None, markdown_report_path: Path | None) -> None:
    emit_json_report(report, report_path, markdown_report_path, _report_markdown(report))


def _base_report(
    args: argparse.Namespace,
    spec: dict[str, Any],
    base_url: str | None,
    command: list[str],
    output_usd_path: Path,
) -> dict[str, Any]:
    return {
        "asset_path": str(args.asset_path.resolve()),
        "skill": _skill_name(),
        "agent": spec["agent"],
        "tool": "NVIDIA Omniverse Content Agents service API",
        "passed": False,
        "status": "FAIL",
        "operation": "service_pipeline",
        "base_url": base_url,
        "session_id": None,
        "output_directory": str(args.output_directory.resolve()),
        "output_usd_path": str(output_usd_path),
        "upload_asset_path": None,
        "upload_dependency_count": 0,
        "upload_info": None,
        "material_upload_info": None,
        "material_output_cleanup": None,
        "physics_upload_info": None,
        "upload_packaging": None,
        "command": command,
        "prompt": args.prompt,
        "checks": [],
        "artifacts": [],
        "service_status": None,
        "service_results": None,
        "usd_topology": None,
        "material_optimizer": None,
        "physics_optimizer": None,
        "attempts": [],
        "warnings": [],
        "errors": [],
        "next_step": spec["next_step"],
    }


def _command(
    args: argparse.Namespace,
    *,
    agent_key: str,
    asset_path: Path,
    output_directory: Path,
    base_url: str | None,
    token: str | None,
) -> list[str]:
    command = ["python3", str(Path(__file__).resolve()), str(asset_path), str(output_directory), "--base-url", base_url or "<missing>"]
    if token:
        command.extend(["--token", "<redacted>"])
    if args.prompt:
        command.extend(["--prompt", args.prompt])
    if agent_key == "material":
        if args.optimize_usd:
            command.append("--optimize-usd")
        else:
            command.append("--no-optimize-usd")
        if args.skip_instances:
            command.append("--skip-instances")
        if args.skip_prototypes:
            command.append("--skip-prototypes")
        if args.skip_existing_materials:
            command.append("--skip-existing-materials")
        if args.layer_only:
            command.append("--layer-only")
        if not args.material_output_cleanup:
            command.append("--no-material-output-cleanup")
    elif agent_key == "physics":
        if args.render_backend:
            command.extend(["--render-backend", args.render_backend])
        if args.optimize_usd:
            command.append("--optimize-usd")
        if args.enable_deinstance:
            command.append("--enable-deinstance")
        else:
            command.append("--disable-deinstance")
        if args.enable_split:
            command.append("--enable-split")
        if args.convert_output_to_usd:
            command.append("--convert-output-to-usd")
        if not args.auto_optimize_composed_usd:
            command.append("--no-auto-optimize-composed-usd")
    elif agent_key == "texture" and args.material_textures:
        command.extend(["--material-textures", args.material_textures])
    return command


def run(args: argparse.Namespace) -> dict[str, Any]:
    spec = _spec()
    agent_key = spec["agent_key"]
    asset_path = args.asset_path.resolve()
    output_directory = args.output_directory.resolve()
    base_url, base_url_source = _resolve_base_url(args.base_url, spec)
    token = args.token or _env_or_file_first(spec["token_env"])
    output_usd_path = _required_output_path(agent_key, spec, asset_path, output_directory)
    report = _base_report(args, spec, base_url, [], output_usd_path)
    checks = report["checks"]

    if preflight_required() and args.base_url is None:
        preflight_check = preflight_status_check(_skill_name(), agent_key)
        checks.append(preflight_check)
        if not preflight_check["passed"]:
            report["status"] = "BLOCKED"
            report["errors"] = [preflight_check["message"]]
            return report

    checks.append(_check("asset_exists", asset_path.exists(), "Asset path exists" if asset_path.exists() else "Asset path does not exist"))
    if not asset_path.exists():
        report["errors"] = [check["message"] for check in checks if not check["passed"]]
        return report

    supported = asset_path.suffix.lower() in USD_EXTENSIONS
    checks.append(
        _check(
            "supported_usd_extension",
            supported,
            "Asset uses a supported USD extension" if supported else "Asset must be .usd, .usda, .usdc, or .usdz",
        )
    )
    if not supported:
        report["errors"] = [check["message"] for check in checks if not check["passed"]]
        return report

    if agent_key == "material":
        topology = _inspect_usd_topology(asset_path)
        report["usd_topology"] = topology
        optimizer = _apply_material_auto_optimizer(args, topology)
        report["material_optimizer"] = optimizer
        if optimizer["auto_disabled_optimizer"]:
            checks.append(
                _check(
                    "material_instance_traversal_enabled",
                    True,
                    "Disabled Material Agent optimize_usd and kept skip_instances=false for instance/prototype-only USD topology",
                    "info",
                )
            )
        elif topology.get("inspected"):
            checks.append(
                _check(
                    "material_optimizer_default_enabled",
                    True,
                    "Using Material Agent optimize_usd path after USD topology inspection",
                    "info",
                )
            )
        else:
            checks.append(
                _check(
                    "material_optimizer_inspection_skipped",
                    True,
                    str(topology.get("reason") or "USD topology inspection was skipped; using Material Agent optimize_usd default"),
                    "info",
                )
            )
    elif agent_key == "physics":
        topology = _inspect_usd_topology(asset_path)
        report["usd_topology"] = topology
        optimizer = _apply_physics_auto_optimizer(args, topology)
        report["physics_optimizer"] = optimizer
        if optimizer["auto_enabled"]:
            checks.append(
                _check(
                    "physics_auto_optimizer_enabled",
                    True,
                    "Enabled optimize_usd, deinstance, and split for composed USD topology: "
                    + ", ".join(optimizer["auto_reasons"]),
                    "info",
                )
            )
        elif topology.get("inspected"):
            checks.append(
                _check(
                    "physics_auto_optimizer_not_needed",
                    True,
                    "No GeomSubset, instance, or prototype topology detected for automatic Physics Agent optimization",
                    "info",
                )
            )
        else:
            checks.append(
                _check(
                    "physics_auto_optimizer_inspection_skipped",
                    True,
                    str(topology.get("reason") or "USD topology inspection was skipped"),
                    "info",
                )
            )

    report["command"] = _command(
        args,
        agent_key=agent_key,
        asset_path=asset_path,
        output_directory=output_directory,
        base_url=base_url,
        token=token,
    )

    checks.append(
        _check(
            "base_url_available",
            bool(base_url),
            f"Using Content Agents service {base_url}"
            if base_url
            else f"Set --base-url or one of {', '.join(spec['default_env'])}",
        )
    )
    if base_url_source:
        checks.append(_check(f"base_url_from_{base_url_source}", True, f"Resolved base URL from {base_url_source}", "info"))
    if not base_url:
        report["status"] = "BLOCKED"
        report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
        return report

    if agent_key == "texture" and args.material_textures:
        try:
            json.loads(args.material_textures)
        except json.JSONDecodeError as exc:
            checks.append(_check("material_textures_json_valid", False, f"Invalid --material-textures JSON: {exc}"))
            report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
            return report
        checks.append(_check("material_textures_json_valid", True, "Material texture config JSON is valid", "info"))

    output_directory.mkdir(parents=True, exist_ok=True)
    material_upload_info: dict[str, Any] | None = None
    if agent_key == "material":
        asset_path, material_upload_info = _stage_material_upload_asset(asset_path)
        report["material_upload_info"] = material_upload_info
        if material_upload_info.get("warning"):
            checks.append(_check("material_upload_prep_skipped", True, material_upload_info["warning"], "info"))
        elif material_upload_info.get("staged"):
            if material_upload_info.get("stripped_mdl_source_assets"):
                checks.append(
                    _check(
                        "material_upload_mdl_source_assets_stripped",
                        True,
                        "Staged Material Agent upload without "
                        f"{material_upload_info['stripped_mdl_source_assets']} MDL sourceAsset references",
                        "info",
                    )
                )
            if material_upload_info.get("cleared_unresolved_service_asset_paths"):
                checks.append(
                    _check(
                        "material_upload_unresolved_service_asset_paths_cleared",
                        True,
                        "Staged Material Agent upload without "
                        f"{material_upload_info['cleared_unresolved_service_asset_paths']} service-internal asset paths",
                        "info",
                    )
                )

    physics_upload_info: dict[str, Any] | None = None
    if agent_key == "physics":
        asset_path, physics_upload_info = _stage_physics_upload_asset(asset_path)
        report["physics_upload_info"] = physics_upload_info
        if physics_upload_info.get("warning"):
            checks.append(_check("physics_upload_prep_skipped", True, physics_upload_info["warning"], "info"))
        elif physics_upload_info.get("staged"):
            if physics_upload_info.get("stripped_mdl_source_assets"):
                checks.append(
                    _check(
                        "physics_upload_mdl_source_assets_stripped",
                        True,
                        "Staged Physics Agent upload without "
                        f"{physics_upload_info['stripped_mdl_source_assets']} MDL sourceAsset references",
                        "info",
                    )
                )
            if physics_upload_info.get("cleared_unresolved_service_asset_paths"):
                checks.append(
                    _check(
                        "physics_upload_unresolved_service_asset_paths_cleared",
                        True,
                        "Staged Physics Agent upload without "
                        f"{physics_upload_info['cleared_unresolved_service_asset_paths']} service-internal asset paths",
                        "info",
                    )
                )

    try:
        upload_asset_path, upload_info = _prepare_upload_asset(asset_path, output_directory)
    except Exception as exc:
        checks.append(_check("upload_asset_prepared", False, str(exc)))
        report["upload_asset_path"] = str(asset_path)
        report["upload_packaging"] = "failed"
        report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
        return report

    report["upload_asset_path"] = str(upload_asset_path)
    report["upload_packaging"] = upload_info["packaging"]
    report["upload_dependency_count"] = upload_info["dependency_count"]
    report["upload_info"] = upload_info
    if upload_info["inspection_error"]:
        checks.append(_check("upload_dependency_inspection_skipped", True, upload_info["inspection_error"], "info"))
    elif upload_info["packaging"] == "usdz":
        checks.append(
            _check(
                "upload_asset_packaged",
                True,
                f"Packaged {upload_info['dependency_count']} USD dependencies into {upload_asset_path} for Content Agents upload",
                "info",
            )
        )
    elif upload_info["packaging"] == "already_usdz":
        checks.append(_check("upload_asset_already_packaged", True, "Input asset is already a USDZ package", "info"))
    else:
        checks.append(_check("upload_asset_single_file", True, "No external USD dependencies detected for upload", "info"))

    session_id: str | None = None
    try:
        session_id = _post_pipeline(upload_asset_path, base_url, token, _service_fields(args, agent_key), args.request_timeout)
        report["session_id"] = session_id
        checks.append(_check("session_started", True, f"Started Content Agents session {session_id}", "info"))
        service_status = _wait_for_status(
            base_url,
            token,
            session_id,
            timeout=args.timeout,
            poll_interval=args.poll_interval,
            request_timeout=args.request_timeout,
        )
        report["service_status"] = service_status
        poll_warnings = service_status.get("poll_warnings")
        if isinstance(poll_warnings, list):
            for warning in poll_warnings:
                report["warnings"].append(f"Recovered transient status poll error: {warning}")
        state = str(service_status.get("status", "")).lower()
        checks.append(_check("session_completed", state in TERMINAL_SUCCESS, f"Content Agents session status: {service_status.get('status')}"))
        try:
            report["service_results"] = _json_request(
                "GET",
                urljoin(f"{base_url.rstrip('/')}/", f"pipeline/{session_id}/results"),
                token=token,
                timeout=args.request_timeout,
            )
        except Exception as exc:
            report["warnings"].append(f"Could not fetch service results: {exc}")
    except Exception as exc:
        checks.append(_check("service_pipeline_completed", False, str(exc)))
        report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
        retry_report = _maybe_retry_material_without_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        retry_report = _maybe_repair_and_retry_physics_scene_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        retry_report = _maybe_retry_physics_without_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        return report

    if any(check["severity"] == "error" and not check["passed"] for check in checks):
        report["errors"] = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
        retry_report = _maybe_retry_material_without_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        retry_report = _maybe_repair_and_retry_physics_scene_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        retry_report = _maybe_retry_physics_without_optimizer(report, args)
        if retry_report is not None:
            return retry_report
        return report

    artifacts = report["artifacts"]
    required_artifact = _download_artifact(
        base_url,
        token,
        session_id,
        spec["output_label"],
        spec["output_endpoint"],
        output_usd_path,
        True,
        args.request_timeout * 2,
        allow_response_usd_suffix=agent_key == "physics",
        wait_timeout=args.artifact_timeout,
        poll_interval=args.poll_interval,
    )
    artifacts.append(required_artifact)
    if required_artifact.get("retry_count"):
        report["warnings"].append(
            f"Required artifact {spec['output_label']} became available after "
            f"{required_artifact['retry_count']} retry attempt(s)."
        )
    if required_artifact["downloaded"] and required_artifact["path"]:
        output_usd_path = Path(required_artifact["path"])
        report["output_usd_path"] = str(output_usd_path)

    if agent_key == "material" and args.material_output_cleanup and required_artifact["downloaded"] and output_usd_path:
        cleanup = cleanup_material_output(output_usd_path)
        report["material_output_cleanup"] = cleanup
        if cleanup.get("warning"):
            checks.append(_check("material_output_cleanup_warning", True, cleanup["warning"], "info"))
            report["warnings"].append(str(cleanup["warning"]))
        elif cleanup.get("skipped_reason"):
            checks.append(_check("material_output_cleanup_skipped", True, str(cleanup["skipped_reason"]), "info"))
        elif cleanup.get("removed_material_count") or cleanup.get("repaired_bound_shader_count"):
            checks.append(
                _check(
                    "material_output_broken_source_assets_cleaned",
                    True,
                    "Removed "
                    f"{cleanup.get('removed_material_count', 0)} unbound material subtree(s) and repaired "
                    f"{cleanup.get('repaired_bound_shader_count', 0)} bound shader(s) with broken sourceAsset references",
                    "info",
                )
            )
        else:
            checks.append(
                _check(
                    "material_output_cleanup_noop",
                    True,
                    "No unbound material subtrees with broken sourceAsset shader references were found",
                    "info",
                )
            )
        if cleanup.get("kept_bound_invalid_shader_count"):
            report["warnings"].append(
                "Material output cleanup found broken sourceAsset shader references on bound materials and left them unchanged."
            )
    elif agent_key == "material" and not args.material_output_cleanup:
        report["material_output_cleanup"] = {
            "attempted": False,
            "path": str(output_usd_path),
            "skipped_reason": "disabled by --no-material-output-cleanup",
        }

    for artifact_name, endpoint, suffix, required in spec["optional_artifacts"]:
        artifact = _download_artifact(
            base_url,
            token,
            session_id,
            artifact_name,
            endpoint,
            output_directory / f"{asset_path.stem}_{agent_key}_{artifact_name}{suffix}",
            required,
            args.request_timeout * 2,
        )
        artifacts.append(artifact)
        if not artifact["required"] and not artifact["downloaded"]:
            report["warnings"].append(f"Optional artifact {artifact_name} was not downloaded: {artifact['error']}")

    required_missing = [artifact for artifact in artifacts if artifact["required"] and not artifact["downloaded"]]
    checks.append(
        _check(
            "required_artifacts_downloaded",
            not required_missing,
            "Downloaded required output artifact" if not required_missing else "; ".join(artifact["error"] or artifact["name"] for artifact in required_missing),
        )
    )

    if agent_key == "physics" and args.convert_output_to_usd and not required_missing:
        converted, message, converted_path = _convert_physics_output_to_usd(output_usd_path, output_usd_path.with_suffix(".usd"))
        checks.append(_check("physics_output_converted_to_usd", converted, message))
        if converted:
            report["output_usd_path"] = str(converted_path)
            artifacts.append(
                {
                    "name": "physics_usd_crate",
                    "url": "local:usda-to-usd",
                    "path": str(converted_path),
                    "required": True,
                    "downloaded": True,
                    "content_type": "model/vnd.usd",
                    "error": None,
                }
            )

    errors = [check["message"] for check in checks if check["severity"] == "error" and not check["passed"]]
    report["errors"] = errors
    report["passed"] = not errors
    report["status"] = "PASS" if not errors else "FAIL"
    if errors:
        report["output_usd_path"] = None
    return report


def _parser() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(description="Portable Content Agents service wrapper.")
    parser.add_argument("asset_path", type=Path)
    parser.add_argument("output_directory", type=Path)
    parser.add_argument("--base-url")
    parser.add_argument(
        "--token",
        help=(
            "Last-resort bearer token fallback. Prefer service-specific token "
            "environment variables or *_FILE variables so secrets do not appear "
            "in process arguments."
        ),
    )
    parser.add_argument("--prompt")
    parser.add_argument("--timeout", type=int, default=1800)
    parser.add_argument("--request-timeout", type=int, default=120)
    parser.add_argument("--poll-interval", type=float, default=2.0)
    parser.add_argument(
        "--artifact-timeout",
        type=float,
        default=180.0,
        help="Seconds to retry required artifact downloads after a terminal service status.",
    )
    parser.add_argument("--report", type=Path)
    parser.add_argument("--markdown-report", type=Path)
    parser.add_argument("--email")
    optimize_usd = parser.add_mutually_exclusive_group()
    optimize_usd.add_argument("--optimize-usd", dest="optimize_usd", action="store_true")
    optimize_usd.add_argument("--no-optimize-usd", dest="optimize_usd", action="store_false")
    parser.set_defaults(optimize_usd=None)
    parser.add_argument("--skip-instances", action="store_true")
    parser.add_argument("--skip-prototypes", action="store_true")
    parser.add_argument("--skip-existing-materials", action="store_true")
    parser.add_argument("--layer-only", action="store_true")
    parser.add_argument(
        "--no-material-output-cleanup",
        dest="material_output_cleanup",
        action="store_false",
        help=(
            "Disable the post-Material-Agent cleanup that removes unbound material subtrees "
            "and repairs bound shaders with broken sourceAsset references from downloaded USD outputs."
        ),
    )
    parser.set_defaults(material_output_cleanup=True)
    parser.add_argument("--render-backend", choices=("warp", "ovrtx", "remote"))
    deinstance = parser.add_mutually_exclusive_group()
    deinstance.add_argument("--enable-deinstance", dest="enable_deinstance", action="store_true")
    deinstance.add_argument("--disable-deinstance", dest="enable_deinstance", action="store_false")
    parser.set_defaults(enable_deinstance=True)
    parser.add_argument("--enable-split", action="store_true")
    auto_optimize = parser.add_mutually_exclusive_group()
    auto_optimize.add_argument("--auto-optimize-composed-usd", dest="auto_optimize_composed_usd", action="store_true")
    auto_optimize.add_argument("--no-auto-optimize-composed-usd", dest="auto_optimize_composed_usd", action="store_false")
    parser.set_defaults(auto_optimize_composed_usd=True)
    parser.add_argument("--convert-output-to-usd", action="store_true")
    parser.add_argument("--material-textures")
    return parser


def main(argv: list[str] | None = None) -> int:
    args = _parser().parse_args(argv)
    report = run(args)
    _emit_report(report, args.report, args.markdown_report)
    return 0 if report["passed"] else 1


if __name__ == "__main__":
    raise SystemExit(main())

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