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sha256:ac8fbfed2c37d1ca2407a94e44246384e901f8464e5dd3395d9f360a2ade04ff +size 27120 diff --git a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/harbor-trajectory-4.json b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/harbor-trajectory-4.json new file mode 100644 index 0000000000000000000000000000000000000000..862bce9b4ed04f4827ead2dbfde73a6e177aa352 --- /dev/null +++ b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/harbor-trajectory-4.json @@ -0,0 +1,2345 @@ +{ + "schema_version": "ATIF-v1.7", + "session_id": "01a15bb7-fdd5-7255-9f5b-bb98d763dec5", + "agent": { + "name": "pi", + "version": "0.85.1", + "model_name": "harbor-endpoint/gpt-6.1-sol" + }, + "steps": [ + { + "step_id": 1, + "timestamp": "2026-10-20T23:49:08.950Z", + "source": "user", + "message": [ + { + "type": "text", + "text": "\nReconstruct the supplied object as /output/asset.usd.\nNominal dimensions in canonical metres XYZ: [0.6357795000076294, 0.5118491649627686, 0.30237919092178345]\nRead /task/contract.md, /task/tool-docs.md and /task/scoring-policy.json. Identify the rigid parts, joints and their motion before authoring, then reconstruct appearance and mechanical structure. Use Python/PXR. Do not use Blender. Validate and inspect the NVIDIA findings before submitting.\n" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_1.png" + } + } + ], + "extra": { + "pi_event_id": "4b905c0c", + "pi_parent_id": "b78c0cf6" + } + }, + { + "step_id": 2, + "timestamp": "2026-10-20T23:49:13.200Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_EBGnIucqUh8GnFS5KL7dRnE1|fc_0516a57b3bf4c875016ad7fdf9028487d281f2278e487d604e", + "function_name": "read", + "arguments": { + "path": "/task/contract.md", + "offset": 1, + "limit": 2000 + } + }, + { + "tool_call_id": "call_oCrZHsB5XqrRoAcnIrSWnQYo|fc_0516a57b3bf4c875016ad7fdf9029887d280bd9154e2f9010f", + "function_name": "read", + "arguments": { + "path": "/task/tool-docs.md", + "offset": 1, + "limit": 2000 + } + }, + { + "tool_call_id": "call_6BoU08GYkdT83Ex2Xvh9MsPl|fc_0516a57b3bf4c875016ad7fdf902a487d2bab01f8e57d0e84d", + "function_name": "read", + "arguments": { + "path": "/task/scoring-policy.json", + "offset": 1, + "limit": 2000 + } + }, + { + "tool_call_id": "call_cXUiKoFZfjHHTovyvDev0yh3|fc_0516a57b3bf4c875016ad7fdf902ac87d28687da2235bb0162", + "function_name": "bash", + "arguments": { + "command": "ls -la /output && ls -la /task", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_EBGnIucqUh8GnFS5KL7dRnE1|fc_0516a57b3bf4c875016ad7fdf9028487d281f2278e487d604e", + "content": "# Reconstruction contract\n\nReconstruct the supplied object at /output/asset.usd using Python/PXR. Include\nits local USD and texture dependencies and place authoring scripts in /tmp.\nRead the supplied dimensions, image and scoring-policy.json.\n\nThe evaluation reports three independent scores:\n\n- Formal fidelity: NVIDIA SimReady-Foundation Robotics-Prop 4.0.0. Each of its\n 46 mandatory requirements counts once, with 95 * passed / 46 points and five\n further points when all pass. The 51 optional requirements are reported separately.\n- Visual fidelity: reference-scale shape, colours, textures and surface appearance.\n- Kinematic fidelity: the object's connected rigid parts, joint types, hinge or\n sliding axes, attachment locations and allowed ranges of motion.\n\nIdentify the object's parts and their mechanical relationships before authoring.\nKeep parts that move relative to one another as distinct rigid bodies and author\nthe corresponding UsdPhysics joints. Specify each joint's connected bodies,\nlocal positions, local orientations, axis and appropriate motion limits. For\nexample, folding eyewear needs hinged temples rather than one rigid mesh.\nUse fixed joints for genuine fixed attachments and keep genuinely rigid objects\nrigid. Base this structure on the supplied observations and the object's function.\n\nCheck that joint frames meet at each attachment, that movable parts can travel\nthrough their intended range and that the bodies and joints have the appropriate\nenabled and kinematic states. Preserve the observed shape and materials while\nconstructing this mechanical structure.\n\nUse validate_candidate to inspect the NVIDIA findings and repair the candidate.\nThe final submission freezes the authored files for evaluation.", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "call_oCrZHsB5XqrRoAcnIrSWnQYo|fc_0516a57b3bf4c875016ad7fdf9029887d280bd9154e2f9010f", + "content": "# Authoring tools\n\nget_task_thumbnail returns the reference image. validate_candidate accepts {\"request_id\":\"check-1\"} and returns the current score, remaining validation calls and nvidia_validator_report.file_path. Search that JSON file with rg for a requirement ID or candidate prim path. get_validation_report reads a selected range of the same report.\n\nUse a new request ID after each repair. submit_asset accepts {\"request_id\":\"final\"} and stops authoring. The model has 64 inference requests, with provider-native output limits. Captures appear in the final report.", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "call_6BoU08GYkdT83Ex2Xvh9MsPl|fc_0516a57b3bf4c875016ad7fdf902a487d2bab01f8e57d0e84d", + "content": "{\n \"benchmark_output_token_cap\": null,\n \"composite_scores\": {\n \"formal\": \"SimReady Robotics-Prop mandatory requirements\",\n \"kinematic\": \"joint recovery and allowed relative motion correspondence\",\n \"visual\": \"geometric mean of shape and appearance material correspondence\"\n },\n \"limits\": {\n \"agent_seconds\": 231000,\n \"final_seconds\": 600,\n \"inference_requests\": 64,\n \"preview_requests\": 12,\n \"preview_seconds\": 90,\n \"validation_calls\": 5,\n \"validation_seconds\": 120,\n \"views_per_preview\": 4\n },\n \"model_call_budget\": 64,\n \"reward_reporting\": {\n \"formula\": \"95 * passed / fixed_applicable + 5_if_all_pass\",\n \"harbor_key\": \"simready_reward\",\n \"scale\": [\n 0,\n 100\n ]\n },\n \"semantic_labels\": {\n \"criterion\": \"mandatory NVIDIA SL IDs only\",\n \"required\": true,\n \"scoring\": true\n },\n \"validator_scoring\": {\n \"all_pass_bonus_percent\": 5,\n \"applicability\": \"fixed_profile_and_task_before_candidate\",\n \"applicable_requirement_ids\": [\n \"com.nvidia.simready.HI.010\",\n \"com.nvidia.simready.NP.002\",\n \"com.nvidia.simready.NP.003\",\n \"com.nvidia.simready.NP.004\",\n \"com.nvidia.simready.NP.005\",\n \"com.nvidia.simready.NP.007\",\n \"com.nvidia.simready.NP.008\",\n \"com.nvidia.simready.RB.001\",\n \"com.nvidia.simready.RB.007\",\n \"com.nvidia.simready.RB.010\",\n \"com.nvidia.simready.RB.COL.001\",\n \"com.nvidia.simready.RB.COL.002\",\n \"com.nvidia.simready.RB.COL.003\",\n \"com.nvidia.simready.SL.001\",\n \"com.nvidia.simready.SL.002\",\n \"com.nvidia.simready.SL.003\",\n \"com.nvidia.simready.SL.MAT.001\",\n \"com.nvidia.simready.SL.QCODE.001\",\n \"com.nvidia.simready.SL.TIME.001\",\n \"com.nvidia.simready.SR.002\",\n \"com.nvidia.simready.SR.004\",\n \"com.nvidia.simready.UN.006\",\n \"com.nvidia.simready.UN.007\",\n \"com.nvidia.simready.VG.008\",\n \"com.nvidia.simready.VG.025\",\n \"com.nvidia.simready.VG.MESH.001\",\n \"com.nvidia.simready.VM.MAT.001\",\n \"com.nvidia.simready.VM.PS.002\",\n \"com.nvidia.simready.VM.TEX.001\",\n \"com.nvidia.simready.VM.TEX.003\",\n \"com.nvidia.usd.AA.001\",\n \"com.nvidia.usd.AA.002\",\n \"com.nvidia.usd.HI.001\",\n \"com.nvidia.usd.HI.003\",\n \"com.nvidia.usd.HI.004\",\n \"com.nvidia.usd.RB.003\",\n \"com.nvidia.usd.RB.005\",\n \"com.nvidia.usd.RB.009\",\n \"com.nvidia.usd.RB.COL.004\",\n \"com.nvidia.usd.VG.002\",\n \"com.nvidia.usd.VG.014\",\n \"com.nvidia.usd.VG.027\",\n \"com.nvidia.usd.VG.028\",\n \"com.nvidia.usd.VG.029\",\n \"com.nvidia.usd.VM.BIND.001\",\n \"com.nvidia.usd.VM.PS.001\"\n ],\n \"base_credit_percent\": 95,\n \"early_stop_penalty_percent\": 0,\n \"optional_requirements\": \"report_only\",\n \"policy_id\": \"NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1\",\n \"process_shaping_percent\": 0,\n \"profile\": {\n \"id\": \"Robotics-Prop\",\n \"version\": \"4.0.0\"\n },\n \"profile_inventory_sha256\": \"5a8dccd559cd3625025cedd08f7e2c174df32b8bbe0b17da9c94a588c86da13c\",\n \"report_only_mandatory_ids\": [],\n \"schema\": \"simready-validator-scoring-policy-v1\",\n \"scope\": \"all_mandatory_profile\",\n \"scoring_unit\": \"one_mandatory_requirement_ID\",\n \"stop_bonus_percent\": 0,\n \"unknown\": \"null_score_fixed_denominator\"\n }\n}", + "extra": { + "tool_name": "read", + "is_error": false + } + }, + { + "source_call_id": "call_cXUiKoFZfjHHTovyvDev0yh3|fc_0516a57b3bf4c875016ad7fdf902ac87d28687da2235bb0162", + "content": "total 0\ndrwxrwxrwx 2 actor actor 40 Oct 20 23:49 .\ndrwxr-xr-x 1 root root 56 Oct 20 23:49 ..\ntotal 776\ndr-xr-xr-x 2 actor actor 160 Oct 20 23:49 .\ndrwxr-xr-x 1 root root 56 Oct 20 23:49 ..\n-r--r--r-- 1 actor actor 1746 Oct 20 23:49 contract.md\n-r--r--r-- 1 actor actor 452 Oct 20 23:49 instruction.md\n-r--r--r-- 1 actor actor 3305 Oct 20 23:49 scoring-policy.json\n-r--r--r-- 1 actor actor 435 Oct 20 23:49 simready-bench-native-output-policy.ts\n-r--r--r-- 1 actor actor 772740 Oct 20 23:49 thumbnail.png\n-r--r--r-- 1 actor actor 572 Oct 20 23:49 tool-docs.md", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 2668, + "completion_tokens": 128, + "cached_tokens": 0, + "extra": { + "cache_write_tokens": 2665, + "reasoning_tokens": 0, + "pi_total_tokens": 2796 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "4bfd83d9", + "pi_parent_id": "4b905c0c", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fdf5b5c487d28ec352228250552e", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 3, + "timestamp": "2026-10-20T23:49:36.822Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_SMkmvJgNOT5ajAn1IQx2gCDC|fc_0516a57b3bf4c875016ad7fe1065b887d2910c7c61e1e1fbdd", + "function_name": "mcp", + "arguments": { + "server": "benchmark" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_SMkmvJgNOT5ajAn1IQx2gCDC|fc_0516a57b3bf4c875016ad7fe1065b887d2910c7c61e1e1fbdd", + "content": "benchmark (4 tools):\n\n- benchmark_get_task_thumbnail - Read the supplied task thumbnail and public brief.\n- benchmark_validate_candidate - Validate a frozen candidate and return NVIDIA...\n- benchmark_submit_asset - End authoring and freeze the submitted asset....\n- benchmark_get_validation_report - Read a requested range of a prior NVIDIA report....", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 4574, + "completion_tokens": 1054, + "cached_tokens": 2665, + "extra": { + "cache_write_tokens": 1906, + "reasoning_tokens": 1034, + "pi_total_tokens": 5628 + } + }, + 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'nvm']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 5702, + "completion_tokens": 67, + "cached_tokens": 4571, + "extra": { + "cache_write_tokens": 1128, + "reasoning_tokens": 0, + "pi_total_tokens": 5769 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "7cb351c9", + "pi_parent_id": "128d2a4d", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe11e36087d2a08b7edc05f9b89d", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 5, + "timestamp": "2026-10-20T23:49:44.792Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "The reference appears to be an open corrugated-cardboard box with white outer faces, a kraft-coloured interior, and exposed corrugation at the rim. I\u2019ll model the bottom and folded walls as one rigid assembly; there\u2019s no visible articulated mechanism or loose lid that calls for a movable joint.", + "reasoning_content": "**Validating mandatory info**\n\nI need to make sure to validate the mandatory information. I'll inspect the installed simready for its schema requirements, ensuring that nothing is hidden or overlooked. It\u2019s important to check that everything aligns with the expectations, so I can proceed confidently. I\u2019m curious about any specific guidelines I should follow during this validation process, so I\u2019ll stay attentive and thorough! 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Each new request consumes one validation call. Repeating a request ID returns its existing result.\n\nShape:\n{ request_id: string; }", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 7926, + "completion_tokens": 1574, + "cached_tokens": 6310, + "extra": { + "cache_write_tokens": 1613, + "reasoning_tokens": 1552, + "pi_total_tokens": 9500 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "27a0139d", + "pi_parent_id": "ec123ecf", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe1cc30c87d2aae5e3042425063a", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 8, + "timestamp": "2026-10-20T23:50:28.488Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_M8GB9RJRQTY3LDZDGO15KY71|fc_0516a57b3bf4c875016ad7fe4329a887d2b056f81293f01041", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nfrom pxr import Usd, Plug, UsdPhysics\nprint([p.name for p in Plug.Registry().GetAllPlugins() if 'semantic' in p.name.lower() or 'physx' in p.name.lower()]);\nimport importlib.util\nfor x in ['pxr.PhysxSchema','pxr.Semantics','numpy','PIL','scipy']: print(x, importlib.util.find_spec(x))\nPY\nls -la /opt/simready/runtime", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_M8GB9RJRQTY3LDZDGO15KY71|fc_0516a57b3bf4c875016ad7fe4329a887d2b056f81293f01041", + "content": "['usdSemantics']\npxr.PhysxSchema None\npxr.Semantics None\nnumpy ModuleSpec(name='numpy', loader=<_frozen_importlib_external.SourceFileLoader object at 0x7cb7c39d2ff0>, origin='/usr/local/lib/python3.12/dist-packages/numpy/__init__.py', submodule_search_locations=['/usr/local/lib/python3.12/dist-packages/numpy'])\nPIL ModuleSpec(name='PIL', loader=<_frozen_importlib_external.SourceFileLoader object at 0x7cb7c39d3d40>, origin='/usr/local/lib/python3.12/dist-packages/PIL/__init__.py', submodule_search_locations=['/usr/local/lib/python3.12/dist-packages/PIL'])\nscipy None\ntotal 0\ndr-xr-xr-x 3 actor actor 60 Oct 20 23:49 .\ndrwxr-xr-x 1 root root 29 Oct 20 22:14 ..\ndr-xr-xr-x 3 actor actor 80 Oct 20 23:49 simready_bench", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 9555, + "completion_tokens": 162, + "cached_tokens": 7923, + "extra": { + "cache_write_tokens": 1629, + "reasoning_tokens": 31, + "pi_total_tokens": 9717 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "603a03a8", + "pi_parent_id": "0ef1f731", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe408aec87d285ef05970a92da59", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 9, + "timestamp": "2026-10-20T23:50:31.394Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_pWjyFMQI5Bwm0GW2b0f9hTu6|fc_0516a57b3bf4c875016ad7fe4664c087d29b2a696fa90a35c2", + "function_name": "bash", + "arguments": { + "command": "find /opt/simready/runtime -maxdepth 4 -type f | head -40; python - <<'PY'\nfrom pxr import UsdSemantics\nprint(dir(UsdSemantics))\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_pWjyFMQI5Bwm0GW2b0f9hTu6|fc_0516a57b3bf4c875016ad7fe4664c087d29b2a696fa90a35c2", + "content": "/opt/simready/runtime/simready_bench/__init__.py\n/opt/simready/runtime/simready_bench/engine/actor_relay.py\n/opt/simready/runtime/simready_bench/engine/actor_mcp.py\n/opt/simready/runtime/simready_bench/engine/__init__.py\n['LabelsAPI', 'LabelsQuery', 'Tokens', '_CanApplyResult', '__MFB_FULL_PACKAGE_NAME', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__spec__']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 9965, + "completion_tokens": 67, + "cached_tokens": 9552, + "extra": { + "cache_write_tokens": 410, + "reasoning_tokens": 0, + "pi_total_tokens": 10032 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "300bdef7", + "pi_parent_id": "af4e827e", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe45631487d2a904e21b98d492fa", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 10, + "timestamp": "2026-10-20T23:50:35.338Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_34m8tGo3wpJUms0gjLMLkge5|fc_0516a57b3bf4c875016ad7fe4a1cac87d291c90f809fa65cb1", + "function_name": "bash", + "arguments": { + "command": "which usdrecord || true; which usdview || true; python - <<'PY'\nfrom pxr import UsdSemantics\nprint(UsdSemantics.LabelsAPI.__doc__)\nprint(dir(UsdSemantics.LabelsAPI))\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_34m8tGo3wpJUms0gjLMLkge5|fc_0516a57b3bf4c875016ad7fe4a1cac87d291c90f809fa65cb1", + "content": "None\n['Apply', 'CanApply', 'ComputeInheritedTaxonomies', 'CreateLabelsAttr', 'Get', 'GetAll', 'GetDirectTaxonomies', 'GetLabelsAttr', 'GetPath', 'GetPrim', 'GetSchemaAttributeNames', 'GetSchemaClassPrimDefinition', 'GetSchemaKind', 'IsAPISchema', 'IsAppliedAPISchema', 'IsConcrete', 'IsMultipleApplyAPISchema', 'IsSemanticsLabelsAPIPath', 'IsTyped', '_GetStaticTfType', '__bool__', '__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__instance_size__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__']", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 10175, + "completion_tokens": 97, + "cached_tokens": 9962, + "extra": { + "cache_write_tokens": 210, + "reasoning_tokens": 20, + "pi_total_tokens": 10272 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "f7914f2c", + "pi_parent_id": "f98140c5", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe484b4c87d29e9e9e7b8ec034f9", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 11, + "timestamp": "2026-10-20T23:50:39.575Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_CIpT3y3zHETkloCpN3UAjMsb|fc_0516a57b3bf4c875016ad7fe4f150087d2b9d077cee4a75029", + "function_name": "bash", + "arguments": { + "command": "pip list | grep -Ei 'usd|render|OpenGL|trimesh|mitsuba|pillow|torch|opencv|vtk|numpy'", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_CIpT3y3zHETkloCpN3UAjMsb|fc_0516a57b3bf4c875016ad7fe4f150087d2b9d077cee4a75029", + "content": "/bin/bash: line 1: pip: command not found\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 10517, + "completion_tokens": 76, + "cached_tokens": 10172, + "extra": { + "cache_write_tokens": 342, + "reasoning_tokens": 21, + "pi_total_tokens": 10593 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "8c52edb8", + "pi_parent_id": "f8fcb94f", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe4c371887d28430a9276f99aab2", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 12, + "timestamp": "2026-10-20T23:52:14.539Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "The silhouette also suggests a lower long wall on one side, with the two end panels ramping up from it to the full-height opposite wall. I\u2019ll preserve that profile, along with the folded white rim and exposed corrugated edges.", + "reasoning_content": "**Designing a shape grid**\n\nI\u2019m thinking about creating a shape grid with specific measurements, like x positions at 96 and z12 with a white exterior and kraft interior. The top should have a rounded cap and avoid complexity. I want to ensure corner seams are visible with a dark tan line for detail. The end profiles need specific dimensions too. I\u2019ll keep the edges smooth and rounded, maintaining simplicity while achieving the desired design features.\n\n**Structuring the box design**\n\nI'm working on a box design with specific measurements. The outer x front should be at +L/2, and the inner part at +L/2-t. I'll use a white exterior with a kraft interior, and the bottom will be at z0. The long y walls will extend from x +/-L/2-t, ensuring that the end faces butt against each other. The side at y=-W/2 will connect neatly, and there will be a cap that extends just slightly below the top for a polished finish.", + "tool_calls": [ + { + "tool_call_id": "call_qlwwpyNcCiGDyq0tBPql4dRc|fc_0516a57b3bf4c875016ad7fe70f71887d29f4074244469dd73", + "function_name": "write", + "arguments": { + "path": "/tmp/create_asset.py", + "content": "from pxr import Usd, UsdGeom, UsdShade, UsdPhysics, Sdf, Gf, Vt, Kind, UsdSemantics\nimport os, math\nimport numpy as np\nfrom PIL import Image, ImageFilter\nOUT='/output'; os.makedirs(OUT+'/textures',exist_ok=True)\nL,W,H=0.6357795000076294,0.5118491649627686,0.30237919092178345\nLOW=.1405; RAMP=.130; T=.0042\nrng=np.random.default_rng(42)\n# Paper fibres and gentle, elongated discoloration. Textures are tileable.\nN=1536\ndef noise(sx,sy):\n a=rng.random((sy,sx))*255\n return np.array(Image.fromarray(a.astype('uint8')).resize((N,N),Image.Resampling.BICUBIC),float)/255-.5\nfor typ in ['white','kraft']:\n if typ=='white':\n var=.023*noise(80,115)+.018*noise(280,500)+.018*noise(600,850)+.022*noise(25,50)\n fiber=noise(700,45)*.010\n base=np.array([.868,.860,.849])\n else:\n var=.08*noise(140,35)+.055*noise(700,100)+.032*noise(400,500)+.030*noise(45,24)\n fiber=noise(1000,80)*.023\n base=np.array([.840,.738,.532])\n rgb=np.clip(base[None,None,:]+(var+fiber)[:,:,None]*np.array([.85,1,1.12])[None,None,:],0,1)\n Image.fromarray((rgb*255).astype('uint8'),'RGB').save(OUT+'/textures/'+typ+'_paper.png')\n # Microsurface normals, very shallow paper grain.\n h=(noise(750,750)*.55+noise(1000,120)*.35)\n dx=np.roll(h,-1,axis=1)-np.roll(h,1,axis=1); dy=np.roll(h,-1,axis=0)-np.roll(h,1,axis=0)\n nn=np.stack([-dx*.14,-dy*.14,np.ones_like(dx)],axis=-1); nn/=np.linalg.norm(nn,axis=-1,keepdims=True)\n Image.fromarray(((nn*.5+.5)*255).astype('uint8'),'RGB').save(OUT+'/textures/'+typ+'_normal.png')\n\nstage=Usd.Stage.CreateNew(OUT+'/asset.usd')\nUsdGeom.SetStageUpAxis(stage,UsdGeom.Tokens.z); UsdGeom.SetStageMetersPerUnit(stage,1)\nstage.SetStartTimeCode(0); stage.SetEndTimeCode(0)\nstage.GetRootLayer().documentation='Open corrugated cardboard display tray. SI metres, Z up. One glued/folded rigid assembly; no articulated parts.'\nroot=UsdGeom.Xform.Define(stage,'/CardboardTray'); stage.SetDefaultPrim(root.GetPrim()); Usd.ModelAPI(root).SetKind(Kind.Tokens.component)\nUsd.ModelAPI(root).SetAssetName('White corrugated display tray')\nUsd.ModelAPI(root).SetAssetIdentifier('asset.usd')\nroot.GetPrim().SetCustomDataByKey('description','Open-top white-faced corrugated cardboard tray; one low long wall, two ramp-shouldered end panels and one tall long wall.')\nroot.GetPrim().SetCustomDataByKey('mechanicalStructure','Single fixed folded and glued corrugated board assembly; no freely moving parts or joints.')\nUsdSemantics.LabelsAPI.Apply(root.GetPrim(),'class').CreateLabelsAttr(['box','cardboard_box','container'])\nUsdSemantics.LabelsAPI.Apply(root.GetPrim(),'material').CreateLabelsAttr(['corrugated_cardboard','paper'])\n# Legacy semantics for simulation consumers.\nroot.GetPrim().AddAppliedSchema('SemanticsAPI:Semantics')\nroot.GetPrim().CreateAttribute('semantics:Semantics:semanticType',Sdf.ValueTypeNames.String).Set('class')\nroot.GetPrim().CreateAttribute('semantics:Semantics:semanticData',Sdf.ValueTypeNames.String).Set('cardboard_box')\nrb=UsdPhysics.RigidBodyAPI.Apply(root.GetPrim()); rb.CreateRigidBodyEnabledAttr(True); rb.CreateKinematicEnabledAttr(False)\nmass=UsdPhysics.MassAPI.Apply(root.GetPrim()); mass.CreateMassAttr(.58); mass.CreateCenterOfMassAttr(Gf.Vec3f(0,-.018,.092)); mass.CreateDiagonalInertiaAttr(Gf.Vec3f(.0158,.0238,.0336)); mass.CreatePrincipalAxesAttr(Gf.Quatf(1))\nlooks=UsdGeom.Scope.Define(stage,'/CardboardTray/Looks')\ndef material(name,color,roughness=.9,texture=None):\n mat=UsdShade.Material.Define(stage,'/CardboardTray/Looks/'+name)\n sh=UsdShade.Shader.Define(stage,str(mat.GetPath())+'/Surface'); sh.CreateIdAttr('UsdPreviewSurface')\n sh.CreateInput('diffuseColor',Sdf.ValueTypeNames.Color3f).Set(Gf.Vec3f(*color))\n sh.CreateInput('roughness',Sdf.ValueTypeNames.Float).Set(roughness)\n sh.CreateInput('metallic',Sdf.ValueTypeNames.Float).Set(0)\n sh.CreateInput('ior',Sdf.ValueTypeNames.Float).Set(1.45)\n sh.CreateInput('opacity',Sdf.ValueTypeNames.Float).Set(1)\n mat.CreateSurfaceOutput().ConnectToSource(sh.ConnectableAPI(),'surface')\n if texture:\n st=UsdShade.Shader.Define(stage,str(mat.GetPath())+'/UV'); st.CreateIdAttr('UsdPrimvarReader_float2'); st.CreateInput('varname',Sdf.ValueTypeNames.Token).Set('st')\n tex=UsdShade.Shader.Define(stage,str(mat.GetPath())+'/PaperColor'); tex.CreateIdAttr('UsdUVTexture'); tex.CreateInput('file',Sdf.ValueTypeNames.Asset).Set(Sdf.AssetPath('textures/'+texture+'_paper.png')); tex.CreateInput('sourceColorSpace',Sdf.ValueTypeNames.Token).Set('sRGB')\n tex.CreateInput('st',Sdf.ValueTypeNames.Float2).ConnectToSource(st.ConnectableAPI(),'result')\n tex.CreateInput('wrapS',Sdf.ValueTypeNames.Token).Set('repeat'); tex.CreateInput('wrapT',Sdf.ValueTypeNames.Token).Set('repeat')\n tex.CreateOutput('rgb',Sdf.ValueTypeNames.Float3)\n sh.GetInput('diffuseColor').ConnectToSource(tex.ConnectableAPI(),'rgb')\n normal=UsdShade.Shader.Define(stage,str(mat.GetPath())+'/PaperGrain'); normal.CreateIdAttr('UsdUVTexture'); normal.CreateInput('file',Sdf.ValueTypeNames.Asset).Set(Sdf.AssetPath('textures/'+texture+'_normal.png')); normal.CreateInput('sourceColorSpace',Sdf.ValueTypeNames.Token).Set('raw'); normal.CreateInput('st',Sdf.ValueTypeNames.Float2).ConnectToSource(st.ConnectableAPI(),'result'); normal.CreateInput('scale',Sdf.ValueTypeNames.Float4).Set((2,2,2,1)); normal.CreateInput('bias',Sdf.ValueTypeNames.Float4).Set((-1,-1,-1,0)); normal.CreateOutput('rgb',Sdf.ValueTypeNames.Float3)\n sh.CreateInput('normal',Sdf.ValueTypeNames.Normal3f).ConnectToSource(normal.ConnectableAPI(),'rgb')\n return mat\nwhite=material('WhitePaper',(.868,.860,.849),.86,'white')\nkraft=material('KraftLiner',(.840,.738,.532),.94,'kraft')\nedge=material('FlutedCore',(.62,.45,.235),.97)\nflute=material('ExposedFlute',(.80,.675,.444),.95)\nseam=material('CreaseShadow',(.25,.185,.108),1)\nphys=UsdShade.Material.Define(stage,'/CardboardTray/Looks/CardboardContact')\npm=UsdPhysics.MaterialAPI.Apply(phys.GetPrim()); pm.CreateStaticFrictionAttr(.70); pm.CreateDynamicFrictionAttr(.58); pm.CreateRestitutionAttr(.015)\nUsdShade.MaterialBindingAPI.Apply(root.GetPrim()).Bind(phys,materialPurpose='physics')\ngeom=UsdGeom.Xform.Define(stage,'/CardboardTray/Geometry')\ncoll=UsdGeom.Xform.Define(stage,'/CardboardTray/Colliders')\n\ndef mesh(name,points,faces,mat=white,uv_axes=(0,2),face_mats=None,collision=False):\n path=('/CardboardTray/Colliders/' if collision else '/CardboardTray/Geometry/')+name\n m=UsdGeom.Mesh.Define(stage,path)\n m.CreatePointsAttr(Vt.Vec3fArray([Gf.Vec3f(*p) for p in points])); m.CreateFaceVertexCountsAttr([len(f) for f in faces]); m.CreateFaceVertexIndicesAttr([i for f in faces for i in f]); m.CreateSubdivisionSchemeAttr('none'); m.CreateOrientationAttr('rightHanded'); m.CreateDoubleSidedAttr(False)\n m.CreateExtentAttr(UsdGeom.PointBased(m).ComputeExtent(m.GetPointsAttr().Get()))\n if not collision:\n # Independent face-varying UVs, metrically consistent paper texture.\n st=[]; normals=[]\n for f in faces:\n a=np.array(points[f[0]]); b=np.array(points[f[1]]); c=np.array(points[f[2]])\n n=np.cross(b-a,c-a); n=n/max(np.linalg.norm(n),1e-10)\n ax=np.argsort(np.abs(n))[:2]\n # Prefer sensible primary axes to keep grain directed down vertical panels.\n if abs(n[0])>.8: ax=[1,2]\n elif abs(n[1])>.8: ax=[0,2]\n elif abs(n[2])>.8: ax=[0,1]\n for i in f:\n st.append(Gf.Vec2f(points[i][ax[0]]/.44+.5,points[i][ax[1]]/.44+.5)); normals.append(Gf.Vec3f(*n))\n UsdGeom.PrimvarsAPI(m).CreatePrimvar('st',Sdf.ValueTypeNames.TexCoord2fArray,UsdGeom.Tokens.faceVarying).Set(st)\n m.CreateNormalsAttr(normals); m.SetNormalsInterpolation('faceVarying')\n UsdShade.MaterialBindingAPI.Apply(m.GetPrim()).Bind(mat)\n if face_mats:\n for mtl,idx in face_mats:\n subset=UsdShade.MaterialBindingAPI(m).CreateMaterialBindSubset(mtl.GetPrim().GetName(),idx)\n UsdShade.MaterialBindingAPI.Apply(subset.GetPrim()).Bind(mtl)\n UsdShade.MaterialBindingAPI(m).SetMaterialBindSubsetsFamilyType('nonOverlapping')\n else:\n m.CreatePurposeAttr('guide')\n UsdPhysics.CollisionAPI.Apply(m.GetPrim()).CreateCollisionEnabledAttr(True)\n UsdPhysics.MeshCollisionAPI.Apply(m.GetPrim()).CreateApproximationAttr('convexHull')\n UsdShade.MaterialBindingAPI.Apply(m.GetPrim()).Bind(phys,materialPurpose='physics')\n return m\n\ndef cube(name,lo,hi,mat=white,face_mats=None,collision=False):\n x,y,z=lo; X,Y,Z=hi\n pts=[(x,y,z),(X,y,z),(X,Y,z),(x,Y,z),(x,y,Z),(X,y,Z),(X,Y,Z),(x,Y,Z)]\n faces=[[0,3,2,1],[0,1,5,4],[1,2,6,5],[2,3,7,6],[3,0,4,7],[4,5,6,7]]\n return mesh(name,pts,faces,mat,face_mats=face_mats,collision=collision)\n# Bottom, with white underside and a continuous unprinted kraft floor.\ncube('BottomBoard',(-L/2+T,-W/2+T,0),(L/2-T,W/2-T,.0052),white,face_mats=[(kraft,[5]),(edge,[1,2,3,4])])\ncube('Bottom',(-L/2+T,-W/2+T,0),(L/2-T,W/2-T,.0052),collision=True)\n# Long side panels; outer faces white, the low wall folds white paper over its inner face.\n# Rounded top edge as a semicircular hem integral with each side, not a loose rigid part.\ndef long_wall(name,y_outer,thick,height,low=False):\n # profile in yz, in counterclockwise yz order, hemisphere on top.\n yc=y_outer + (thick/2 if y_outer<0 else -thick/2)\n r=thick/2; bottom=.001\n profile=[(yc-r,bottom),(yc+r,bottom),(yc+r,height-r)]\n for j in range(1,13):\n a=j*math.pi/12; profile.append((yc+r*math.cos(a),height-r+r*math.sin(a)))\n n=len(profile); a=-L/2+T+.00025; b=L/2-T-.00025\n pts=[(x,y,z) for x in (a,b) for y,z in profile]\n # yz polygon is CCW\n faces=[list(range(n-1,-1,-1)),list(range(n,2*n))]\n for i in range(n): faces.append([i,(i+1)%n,(i+1)%n+n,i+n])\n # n points, edge 0 is bottom, edge 1 is +y side, last edge is -y side.\n fm=[(edge,[0,1])]\n if not low:\n inner_index=3 if y_outer<0 else n+1\n fm.append((kraft,[inner_index]))\n mesh(name,pts,faces,white,face_mats=fm)\n lo=(a,yc-r,bottom); hi=(b,yc+r,height)\n cube(name+'Collider',lo,hi,collision=True)\nlong_wall('TallLongWall',-W/2,.0062,H,False)\nlong_wall('LowFoldedLongWall',W/2,.0062,LOW,True)\n# End walls have a sloped shoulder rising from the low wall, then a level top.\ndef height(y):\n return H if y<=W/2-RAMP else LOW+(H-LOW)*(W/2-y)/RAMP\n# outline yz CCW\nprofile=[(-W/2+.0002,.0007),(W/2-.0002,.0007),(W/2-.0002,LOW),(W/2-RAMP,H),(-W/2+.0002,H)]\ndef end_solid(name,x0,x1,mat,top_delta=0,collider=False,face_mats=None):\n p=[(y,z-(top_delta if i>=2 else 0)) for i,(y,z) in enumerate(profile)]\n n=len(p); pts=[(x,y,z) for x in (x0,x1) for y,z in p]\n faces=[list(range(n-1,-1,-1)),list(range(n,2*n))]+[[i,(i+1)%n,(i+1)%n+n,i+n] for i in range(n)]\n return mesh(name,pts,faces,mat,face_mats=face_mats,collision=collider)\nfor sign,label in [(-1,'Back'),(1,'Front')]:\n outer=sign*L/2; inner=outer-sign*T\n a,b=sorted([outer,inner])\n # Bulk, recessed from cut rim; liner sheets extend above the flute recess.\n end_solid(label+'PanelCore',a+.00035,b-.00035,edge,.0009)\n if sign>0:\n end_solid(label+'OuterWhiteLiner',b-.00036,b,white)\n end_solid(label+'InnerKraftLiner',a,a+.00036,kraft)\n else:\n end_solid(label+'OuterWhiteLiner',a,a+.00036,white)\n end_solid(label+'InnerKraftLiner',b-.00036,b,kraft)\n end_solid(label+'EndCollider',a,b,white,0,True)\n # Corrugation visible across the cut top: a thin sinuous paper web.\n samples=1250; y0=-W/2+.0006; y1=W/2-.0006; mid=(a+b)/2\n pts=[]; count=samples+1\n for i in range(count):\n y=y0+(y1-y0)*i/samples\n wav=math.sin((y-y0)*2*math.pi/.00365)\n x=mid+(T/2-.00046)*wav; w=.00016\n z=height(y)-.00011\n pts.extend([(x-w/2,y,z-.00065),(x+w/2,y,z-.00065),(x+w/2,y,z),(x-w/2,y,z)])\n faces=[[3,2,1,0]]\n for i in range(samples):\n q=i*4; r=q+4\n for j in range(4): faces.append([q+j,q+(j+1)%4,r+(j+1)%4,r+j])\n faces.append([samples*4+j for j in range(4)])\n mesh(label+'CutEdgeFluting',pts,faces,flute)\n# Lightly scored lines in the bottom where the side walls fold upward, not extra movable pieces.\n# Narrow toned strips are closed small solids.\nfor y,name in [(-W/2+.0070,'TallSideFloorCrease'),(W/2-.0070,'LowSideFloorCrease')]:\n cube(name,(-L/2+T+.001,y-.00024,.00512),(L/2-T-.001,y+.00024,.00524),edge)\n# Self-contained asset; no lights, cameras or ground plane are included.\nstage.GetRootLayer().Save()\nprint('Wrote',OUT+'/asset.usd')\n" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_qlwwpyNcCiGDyq0tBPql4dRc|fc_0516a57b3bf4c875016ad7fe70f71887d29f4074244469dd73", + "content": "Successfully wrote to /tmp/create_asset.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 10623, + "completion_tokens": 5483, + "cached_tokens": 10514, + "extra": { + "cache_write_tokens": 106, + "reasoning_tokens": 1279, + "pi_total_tokens": 16106 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "af49723d", + "pi_parent_id": "f92503e3", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fe5080a487d2981ab1c90f272123", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 13, + "timestamp": "2026-10-20T23:52:17.182Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_Ede2vXe4c7PUERV11TrUHj4X|fc_0516a57b3bf4c875016ad7feb0920c87d292d8f3d9c17fb8d5", + "function_name": "bash", + "arguments": { + "command": "python /tmp/create_asset.py", + "timeout": 120 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_Ede2vXe4c7PUERV11TrUHj4X|fc_0516a57b3bf4c875016ad7feb0920c87d292d8f3d9c17fb8d5", + "content": "Wrote /output/asset.usd", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 16124, + "completion_tokens": 27, + "cached_tokens": 10620, + "extra": { + "cache_write_tokens": 5501, + "reasoning_tokens": 0, + "pi_total_tokens": 16151 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "6ac96a8a", + "pi_parent_id": "65e5e83a", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7feaf64e887d2846378ce331010b5", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 14, + "timestamp": "2026-10-20T23:52:24.404Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_5n5Cf4zKKrDa0ul9IUh9Gmwd|fc_0516a57b3bf4c875016ad7feb7e81c87d2bca6162024abb9b6", + "function_name": "mcp", + "arguments": { + "tool": "benchmark_validate_candidate", + "args": { + "request_id": "check-1" + } + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_5n5Cf4zKKrDa0ul9IUh9Gmwd|fc_0516a57b3bf4c875016ad7feb7e81c87d2bca6162024abb9b6", + "content": "{\"request_id\":\"check-1\",\"snapshot_sha256\":\"512163acf3d6ce0f341aa92b17432f5e61b61ac4c0456fdaf9b6f519bd5d8bc5\",\"validation_calls_used\":1,\"validation_calls_remaining\":4,\"feedback\":{\"schema_version\":\"simready-validator-feedback-v1\",\"snapshot_sha256\":\"512163acf3d6ce0f341aa92b17432f5e61b61ac4c0456fdaf9b6f519bd5d8bc5\",\"reward\":82.6086956521739,\"simready\":{\"schema\":\"simready-validator-score-v1\",\"policy_id\":\"NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1\",\"status\":\"scored\",\"score_percent\":82.6086956521739,\"base_credit_percent\":82.6086956521739,\"completion_bonus\":0,\"passed_count\":40,\"failed_count\":6,\"unknown_count\":0,\"applicable_count\":46,\"official_conformance\":{\"profile\":{\"id\":\"Robotics-Prop\",\"version\":\"4.0.0\"},\"passed\":false,\"filtered\":false},\"checks\":[{\"requirement_id\":\"com.nvidia.simready.HI.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.008\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.MAT.001\",\"status\":\"fail\",\"finding_count\":6},{\"requirement_id\":\"com.nvidia.simready.SL.QCODE.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.TIME.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SR.002\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.SR.004\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.UN.006\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.UN.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.008\",\"status\":\"fail\",\"finding_count\":1},{\"requirement_id\":\"com.nvidia.simready.VG.025\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.MESH.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.MAT.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.PS.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.AA.001\",\"status\":\"fail\",\"finding_count\":5},{\"requirement_id\":\"com.nvidia.usd.AA.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.009\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.COL.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.014\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.027\",\"status\":\"fail\",\"finding_count\":5},{\"requirement_id\":\"com.nvidia.usd.VG.028\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.029\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.BIND.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.PS.001\",\"status\":\"pass\",\"finding_count\":0}]},\"nvidia_validator_report\":{\"available\":true,\"report_id\":\"6b3cad4458f4358a33962ced8da023be4224ee811dc64d4448d99a1168d1ad8e\",\"sha256\":\"6b3cad4458f4358a33962ced8da023be4224ee811dc64d4448d99a1168d1ad8e\",\"bytes\":219240,\"total_characters\":219240,\"issue_counts\":{\"issues\":19,\"soft_issues\":55,\"warnings\":0,\"infos\":0},\"complete_report_available\":true,\"delivery\":\"agent_file\",\"file_path\":\"/tmp/simready-validation-reports/6b3cad4458f4358a33962ced8da023be4224ee811dc64d4448d99a1168d1ad8e.json\",\"report\":null,\"retrieval_tool\":\"get_validation_report\",\"offset_unit\":\"Unicode_code_points\",\"search_hint\":\"rg -n -m 20 -M 240 --max-columns-preview -F -e -e ; use sed -n ,p for nearby lines\",\"redactions\":\"private host paths and credential patterns only; original diagnostic wording, suggestions and candidate USD sites retained\",\"file_available\":true,\"validation_calls_consumed\":0}},\"status\":\"completed\"}", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 16171, + "completion_tokens": 52, + "cached_tokens": 16121, + "extra": { + "cache_write_tokens": 47, + "reasoning_tokens": 21, + "pi_total_tokens": 16223 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "37ded789", + "pi_parent_id": "338764de", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7feb646dc87d2a9d47a0b617a61bb", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 15, + "timestamp": "2026-10-20T23:52:30.559Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_FLzliwjMOHFHgY29g1I3M8jy|fc_0516a57b3bf4c875016ad7febcef2c87d2b059ebf691d9efbf", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nimport json\np='/tmp/simready-validation-reports/6b3cad4458f4358a33962ced8da023be4224ee811dc64d4448d99a1168d1ad8e.json'\nd=json.load(open(p)); print(d.keys())\nfor k in d: print(k, type(d[k]))\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_FLzliwjMOHFHgY29g1I3M8jy|fc_0516a57b3bf4c875016ad7febcef2c87d2b059ebf691d9efbf", + "content": "dict_keys(['asset_path', 'asset_sha256', 'engine_dispatch_completed', 'features_summary', 'infos', 'infrastructure_errors', 'inventory', 'issues', 'logs', 'outcome', 'passed', 'profile_id', 'profile_version', 'rule_execution', 'soft_issues', 'warnings'])\nasset_path \nasset_sha256 \nengine_dispatch_completed \nfeatures_summary \ninfos \ninfrastructure_errors \ninventory \nissues \nlogs \noutcome \npassed \nprofile_id \nprofile_version \nrule_execution \nsoft_issues \nwarnings ", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 17864, + "completion_tokens": 106, + "cached_tokens": 16168, + "extra": { + "cache_write_tokens": 1693, + "reasoning_tokens": 0, + "pi_total_tokens": 17970 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "17ebea8f", + "pi_parent_id": "15008dd5", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7febb379487d28cecb1cc3f7feeba", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 16, + "timestamp": "2026-10-20T23:52:34.472Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_Mqwp2QW79uY56uWXzvFRw314|fc_0516a57b3bf4c875016ad7fec1113087d2a66b529c377bf038", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nimport json\np='/tmp/simready-validation-reports/6b3cad4458f4358a33962ced8da023be4224ee811dc64d4448d99a1168d1ad8e.json'\nd=json.load(open(p));print(json.dumps(d['issues'],indent=2))\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_Mqwp2QW79uY56uWXzvFRw314|fc_0516a57b3bf4c875016ad7fec1113087d2a66b529c377bf038", + "content": "[\n {\n \"asset\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"location\": \"SchemaBaseId(prim_id=PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=Sdf.Path('/CardboardTray/Colliders/Bottom'), spec_ids=EditTargetIdList(_values=[EditTargetId(layer_id=LayerId(identifier='/output/asset.usd'), path=Sdf.Path('/CardboardTray/Colliders/Bottom'), composed=PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=Sdf.Path('/CardboardTray/Colliders/Bottom'), spec_ids=EditTargetIdList(_values=[]), variant_selection_path=Sdf.Path.emptyPath))]), variant_selection_path=Sdf.Path('/CardboardTray/Colliders/Bottom')), schema_class=, instance_name='')\",\n \"message\": \"Either normals should be authored or subdivision should be set to Catmull-Clark or Loop \",\n \"prim_path\": \"/CardboardTray/Colliders/Bottom\",\n \"requirement_version\": \"1.0.0\",\n \"rule\": \"usd_validation_nvidia.rules._geometry.NormalsExistChecker\",\n \"rule_id\": \"com.nvidia.usd.VG.027\",\n \"severity\": \"failure\",\n \"suggestions\": []\n },\n {\n \"asset\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"location\": \"SchemaBaseId(prim_id=PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=Sdf.Path('/CardboardTray/Colliders/TallLongWallCollider'), 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to Catmull-Clark or Loop \",\n \"prim_path\": \"/CardboardTray/Colliders/BackEndCollider\",\n \"requirement_version\": \"1.0.0\",\n \"rule\": \"usd_validation_nvidia.rules._geometry.NormalsExistChecker\",\n \"rule_id\": \"com.nvidia.usd.VG.027\",\n \"severity\": \"failure\",\n \"suggestions\": []\n },\n {\n \"asset\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"location\": \"SchemaBaseId(prim_id=PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=Sdf.Path('/CardboardTray/Colliders/FrontEndCollider'), spec_ids=EditTargetIdList(_values=[EditTargetId(layer_id=LayerId(identifier='/output/asset.usd'), path=Sdf.Path('/CardboardTray/Colliders/FrontEndCollider'), composed=PrimId(stage_id=StageId(root_layer=LayerId(identifier='/output/asset.usd')), path=Sdf.Path('/CardboardTray/Colliders/FrontEndCollider'), spec_ids=EditTargetIdList(_values=[]), variant_selection_path=Sdf.Path.emptyPath))]), 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\"asset\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"location\": \"LayerId(identifier='/output/asset.usd')\",\n \"message\": \"Dependent Reference \\\"textures/white_paper.png\\\" should begin with \\\"./\\\" or \\\"../\\\".\",\n \"prim_path\": null,\n \"requirement_version\": \"1.0.0\",\n \"rule\": \"usd_validation_nvidia.rules._atomic_asset.AnchoredAssetPathsChecker\",\n \"rule_id\": \"com.nvidia.usd.AA.001\",\n \"severity\": \"failure\",\n \"suggestions\": []\n },\n {\n \"asset\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"location\": \"StageId(root_layer=LayerId(identifier='/output/asset.usd'))\",\n \"message\": \"Required metadata fields are missing: author, asset_name, asset_type, asset_license, category, source_file, usd_date_generated, qcode, rigid_body_count, asset_extents, mass. Fields may be authored in root-layer customLayerData (including SimReady_Metadata) and/or the same-directory sidecar JSON.\",\n \"prim_path\": null,\n \"requirement_version\": \"0.1.0\",\n \"rule\": \"simready.foundation.tier_core.capabilities.core.sim_ready.validation.MetadataUnion\",\n \"rule_id\": \"com.nvidia.simready.SR.004\",\n \"severity\": \"failure\",\n \"suggestions\": []\n }\n]", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 18155, + "completion_tokens": 99, + "cached_tokens": 17861, + "extra": { + "cache_write_tokens": 291, + "reasoning_tokens": 0, + "pi_total_tokens": 18254 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "aa9e2eec", + "pi_parent_id": "ff785c92", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7febfa58887d2a3e1d51c3134d8ed", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 17, + "timestamp": "2026-10-20T23:52:39.601Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Checking rendering options**\n\nIt sounds like I'm looking to create a thumbnail with my own render. I might need to explore whether I can use a specific rendering option like usd pxr UsdImagingGL, but it looks like that might not be available right now. I\u2019ll have to figure out alternative ways to achieve my goal. It's a bit of a puzzle, but I'm sure there\u2019s a solution out there!", + "tool_calls": [ + { + "tool_call_id": "call_3rlzKxJtPFNYTFBlo9fHaQ0Z|fc_0516a57b3bf4c875016ad7fec6c27487d29fcd06d4ae9411c2", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nimport importlib.util\nfor name in ['pxr.UsdImagingGL','pxr.UsdAppUtils','OpenGL','trimesh','pyrender','mitsuba','moderngl','cv2']: print(name,importlib.util.find_spec(name))\nPY\nwhich Xvfb; ls /usr/local/bin | head -60", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_3rlzKxJtPFNYTFBlo9fHaQ0Z|fc_0516a57b3bf4c875016ad7fec6c27487d29fcd06d4ae9411c2", + "content": "pxr.UsdImagingGL None\npxr.UsdAppUtils None\nOpenGL None\ntrimesh None\npyrender None\nmitsuba None\nmoderngl None\ncv2 None\nnode\nnpm\nnpx\nopencode\npi\npython", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22111, + "completion_tokens": 127, + "cached_tokens": 18152, + "extra": { + "cache_write_tokens": 3956, + "reasoning_tokens": 24, + "pi_total_tokens": 22238 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "8f89eed9", + "pi_parent_id": "ad68c3f0", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fec45fbc87d2be670bef7bd0b3a0", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 18, + "timestamp": "2026-10-20T23:52:43.155Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Considering installation methods**\n\nI\u2019m wondering if I can install via `uv`. Maybe I should use `python -m pip`, but I\u2019m not entirely sure if that\u2019s the right approach. It seems like I need to double-check whether it\u2019s the best method to use or if there\u2019s a better way. I wonder if there are any additional steps I might need to be aware of during this process. Let\u2019s figure this out together!", + "tool_calls": [ + { + "tool_call_id": "call_x9HfBw2jsTnuhWgz4jQXENRu|fc_0516a57b3bf4c875016ad7fecac76c87d28232184db0cacafa", + "function_name": "bash", + "arguments": { + "command": "python -m pip --version; ls /usr/bin | grep -Ei 'usd|render|egl|xvfb'; cat /opt/simready/python-requirements.txt | head -60", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_x9HfBw2jsTnuhWgz4jQXENRu|fc_0516a57b3bf4c875016ad7fecac76c87d28232184db0cacafa", + "content": "pip 24.0 from /usr/local/lib/python3.12/dist-packages/pip (python 3.12)\nusd-core==26.8 --hash=sha256:204fb1ef1fc977b827c491f4e9fa39b57518504ed0cacfe12e026e95123cacf1\nPillow==13.0.0 --hash=sha256:42d63be3af4f9b951b199b0a9d23365d37ab14687e6d77b74940432c8515c4ca\nnumpy==2.2.6 --hash=sha256:fd83c01228a688733f1ded5201c678f0c53ecc1006ffbc404db9f7a899ac6249\npip==24.0 --hash=sha256:ba0d021a166865d2265246961bec0152ff124de910c5cc39f1156ce3fa7c69dc", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 22307, + "completion_tokens": 79, + "cached_tokens": 22108, + "extra": { + "cache_write_tokens": 196, + "reasoning_tokens": 15, + "pi_total_tokens": 22386 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "63b8f41e", + "pi_parent_id": "b7496526", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fec8752087d2bcab5b2a944b54c9", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 19, + "timestamp": "2026-10-20T23:52:49.625Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Installing mitsuba for rendering**\n\nI'm thinking about installing Mitsuba, as it's about 62MB, and time-wise, it should be fine if my internet allows. While I could generate a raster with PIL, I'll need to inspect the material shape and geometry for accuracy. Mitsuba can texture render with an image floor, and I can use convex polygons for custom triangulation. I might need to export to PLY along with texture and convert mesh data based on USD assignments for Mitsuba. Let's get started with the installation!", + "tool_calls": [ + { + "tool_call_id": "call_62QbYFTB7IFna2ASRIEnvoJ1|fc_0516a57b3bf4c875016ad7fed1044887d2bf30dc19275bb08b", + "function_name": "bash", + "arguments": { + "command": "python -m pip install mitsuba --disable-pip-version-check -q", + "timeout": 180 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_62QbYFTB7IFna2ASRIEnvoJ1|fc_0516a57b3bf4c875016ad7fed1044887d2bf30dc19275bb08b", + "content": "error: externally-managed-environment\n\n\u00d7 This environment is externally managed\n\u2570\u2500> To install Python packages system-wide, try apt install\n python3-xyz, where xyz is the package you are trying to\n install.\n \n If you wish to install a non-Debian-packaged Python package,\n create a virtual environment using python3 -m venv path/to/venv.\n Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make\n sure you have python3-full installed.\n \n If you wish to install a non-Debian packaged Python application,\n it may be easiest to use pipx install xyz, which will manage a\n virtual environment for you. Make sure you have pipx installed.\n \n See /usr/share/doc/python3.12/README.venv for more information.\n\nnote: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.\nhint: See PEP 668 for the detailed specification.\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 22617, + "completion_tokens": 138, + "cached_tokens": 22304, + "extra": { + "cache_write_tokens": 310, + "reasoning_tokens": 100, + "pi_total_tokens": 22755 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2003c1be", + "pi_parent_id": "28c5eeb6", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fecc8c9487d284c16d75eb7334c4", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 20, + "timestamp": "2026-10-20T23:52:54.828Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_pJJv8m40qHnQyGtDwS56UkKe|fc_0516a57b3bf4c875016ad7fed612ac87d2b604cbd60c310ca5", + "function_name": "bash", + "arguments": { + "command": "python -m pip install mitsuba --disable-pip-version-check --break-system-packages -q", + "timeout": 180 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_pJJv8m40qHnQyGtDwS56UkKe|fc_0516a57b3bf4c875016ad7fed612ac87d2b604cbd60c310ca5", + "content": "WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError(': Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/mitsuba/\nWARNING: Retrying (Retry(total=3, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError(': Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/mitsuba/\nWARNING: Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError(': Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/mitsuba/\nWARNING: Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError(': Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/mitsuba/\nWARNING: Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError(': Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/mitsuba/\nERROR: Could not find a version that satisfies the requirement mitsuba (from versions: none)\nERROR: No matching distribution found for mitsuba\n\n\nCommand exited with code 1", + "extra": { + "tool_name": "bash", + "is_error": true + } + } + ] + }, + "metrics": { + "prompt_tokens": 23009, + "completion_tokens": 41, + "cached_tokens": 22614, + "extra": { + "cache_write_tokens": 392, + "reasoning_tokens": 0, + "pi_total_tokens": 23050 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "063b9bb4", + "pi_parent_id": "393f4004", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fed502f887d2a748cd4ef7cd1c35", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 21, + "timestamp": "2026-10-20T23:53:44.839Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Implementing polygon profile**\n\nI'm working on profiling a polygon. I need to ensure the edges at the outer corners are rounded, avoiding any awkward low corners. There's a taper at the sides from 51,632 to 61,521, indicating a top offset of about 10. I'll implement a Python raster with stage geometry and reasonable diffuse shading. The light direction impacts how bright different sides will look. Finally, I'll need to calculate the camera's position to accurately project the image.\n\n**Positioning the camera**\n\nI\u2019m figuring out the camera's position for the image. The x-coordinate must be positive while the y-coordinate should be negative. I\u2019ve determined the camera orientation and checked the right vector to ensure it\u2019s projecting positively. I need to also confirm that the left wall connects to the near end on the correct side. I think the best camera position could be (-1,-1.1,.95), placing it to the left and adjusting the axes to get the correct projection lengths based on the overall dimensions.", + "tool_calls": [ + { + "tool_call_id": "call_YPwzim1iK4a8JOn5TaBAcHTM|fc_0516a57b3bf4c875016ad7ff016a4c87d2ae54fa45f7f05c0c", + "function_name": "edit", + "arguments": { + "path": "/tmp/create_asset.py", + "edits": [ + { + "oldText": "Usd.ModelAPI(root).SetAssetIdentifier('asset.usd')", + "newText": "Usd.ModelAPI(root).SetAssetIdentifier('./asset.usd')\nstage.GetRootLayer().customLayerData={'author':'OpenAI','asset_name':'White corrugated display tray','asset_type':'prop','asset_license':'CC0-1.0','category':'container','source_file':'Procedural Python PXR reconstruction','usd_date_generated':'2026-07-02','qcode':'Q188075','rigid_body_count':1,'asset_extents':Vt.DoubleArray([L,W,H]),'mass':.58}" + }, + { + "oldText": "Sdf.AssetPath('textures/'+texture+'_paper.png')", + "newText": "Sdf.AssetPath('./textures/'+texture+'_paper.png')" + }, + { + "oldText": "Sdf.AssetPath('textures/'+texture+'_normal.png')", + "newText": "Sdf.AssetPath('./textures/'+texture+'_normal.png')" + }, + { + "oldText": " mat=UsdShade.Material.Define(stage,'/CardboardTray/Looks/'+name)\n sh=", + "newText": " mat=UsdShade.Material.Define(stage,'/CardboardTray/Looks/'+name)\n UsdSemantics.LabelsAPI.Apply(mat.GetPrim(),'material').CreateLabelsAttr(['paper','corrugated_cardboard'])\n sh=" + }, + { + "oldText": "phys=UsdShade.Material.Define(stage,'/CardboardTray/Looks/CardboardContact')\npm=", + "newText": "phys=UsdShade.Material.Define(stage,'/CardboardTray/Looks/CardboardContact')\nUsdSemantics.LabelsAPI.Apply(phys.GetPrim(),'material').CreateLabelsAttr(['corrugated_cardboard'])\npm=" + }, + { + "oldText": " else:\n m.CreatePurposeAttr('guide')", + "newText": " else:\n normals=[]\n for f in faces:\n a,b,c=[np.array(points[i]) for i in f[:3]]\n n=np.cross(b-a,c-a); n=n/max(np.linalg.norm(n),1e-10)\n normals.extend([Gf.Vec3f(*n)]*len(f))\n m.CreateNormalsAttr(normals); m.SetNormalsInterpolation('faceVarying')\n m.CreatePurposeAttr('guide')" + }, + { + "oldText": "cube('Bottom',(-L/2+T,-W/2+T,0),(L/2-T,W/2-T,.0052),collision=True)", + "newText": "cube('Bottom',(-L/2+T+.0001,-W/2+T+.0001,.00005),(L/2-T-.0001,W/2-T-.0001,.00515),collision=True)" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_YPwzim1iK4a8JOn5TaBAcHTM|fc_0516a57b3bf4c875016ad7ff016a4c87d2ae54fa45f7f05c0c", + "content": "Successfully replaced 7 block(s) in /tmp/create_asset.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 23499, + "completion_tokens": 2149, + "cached_tokens": 23006, + "extra": { + "cache_write_tokens": 490, + "reasoning_tokens": 1552, + "pi_total_tokens": 25648 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "98ca9a82", + "pi_parent_id": "d5980878", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7fedf844087d2af16dea580f1f5bb", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 22, + "timestamp": "2026-10-20T23:54:15.891Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Considering AO building**\n\nI'm thinking about constructing Ambient Occlusion (AO) based on the distances from the floor to the walls, adjusting it'll exp negative 0.015 and reducing by 0.15. The interior's white sides need to be considered too; shadows on the floor aren't super critical, but I still want to make sure they look good. It feels like a balance between achieving a realistic look and not overcomplicating things. Let's see how this goes!", + "tool_calls": [ + { + "tool_call_id": "call_tlciCbDHsiaT4UaDtBbM6YzY|fc_0516a57b3bf4c875016ad7ff11fd5487d289f226e1aaad33ab", + "function_name": "write", + "arguments": { + "path": "/tmp/render_asset.py", + "content": "from pxr import Usd, UsdGeom, UsdShade\nimport numpy as np, math, os\nfrom PIL import Image,ImageDraw,ImageFilter\nstage=Usd.Stage.Open('/output/asset.usd')\nsize=1024\ncam=np.array([-1.,-.96,1.34]); cam/=np.linalg.norm(cam)\nright=np.cross(np.array([0.,0.,1.]),cam);right/=np.linalg.norm(right)\nup=np.cross(cam,right)\n# cam direction points out of screen; larger depth is nearer.\nbasis=np.array([right,-up,cam]); center=np.array([0,0,.146]); scale=1040\n\ndef project(p):\n q=(np.array(p)-center)@basis.T\n q[:,:2]=q[:,:2]*scale+size/2\n return q\n\ndef srgb_to_linear(rgb):return np.where(rgb<=.04045,rgb/12.92,((rgb+.055)/1.055)**2.4)\ndef linear_to_srgb(rgb):return np.where(rgb<=.0031308,rgb*12.92,1.055*np.maximum(rgb,0)**(1/2.4)-.055)\nmaterials={}; textures={}\nfor prim in stage.Traverse():\n if not prim.IsA(UsdShade.Material):continue\n name=prim.GetName();surf=stage.GetPrimAtPath(str(prim.GetPath())+'/Surface')\n if not surf: continue\n color=surf.GetAttribute('inputs:diffuseColor').Get();color=np.array(color)\n tex=stage.GetPrimAtPath(str(prim.GetPath())+'/PaperColor')\n if tex:\n path=tex.GetAttribute('inputs:file').Get().resolvedPath\n textures[name]=srgb_to_linear(np.asarray(Image.open(path).convert('RGB'),float)/255)\n materials[name]=color\nzbuffer=np.full((size,size),-np.inf)\nbg=np.full((size,size,3),.027)\n# Soft contact shadow under the actual footprint.\nmask=Image.new('L',(size,size)); draw=ImageDraw.Draw(mask)\nP=project([[-.318,-.256,0],[.318,-.256,0],[.318,.256,0],[-.318,.256,0]])\ndraw.polygon([(p[0]+8,p[1]+12) for p in P],fill=200)\nmask=mask.filter(ImageFilter.GaussianBlur(19));shad=np.asarray(mask,dtype=float)/255\nimage=bg*(1-shad[:,:,None]*.65)\nlight=np.array([-.38,-.65,1.]);light/=np.linalg.norm(light)\nfor prim in stage.Traverse():\n if not prim.IsA(UsdGeom.Mesh) or '/Colliders/' in str(prim.GetPath()):continue\n m=UsdGeom.Mesh(prim);points=np.array(m.GetPointsAttr().Get(),float);proj=project(points)\n indices=np.array(m.GetFaceVertexIndicesAttr().Get());counts=np.array(m.GetFaceVertexCountsAttr().Get());uv=np.array(UsdGeom.PrimvarsAPI(m).GetPrimvar('st').Get())\n mat=UsdShade.MaterialBindingAPI(prim).ComputeBoundMaterial()[0].GetPrim().GetName()\n face_mats=[mat]*len(counts)\n for child in prim.GetChildren():\n if child.IsA(UsdGeom.Subset):\n sm=UsdShade.MaterialBindingAPI(child).ComputeBoundMaterial()[0]\n for ix in UsdGeom.Subset(child).GetIndicesAttr().Get(): face_mats[ix]=sm.GetPrim().GetName()\n offset=0\n for fi,count in enumerate(counts):\n ids=indices[offset:offset+count]; uvs=uv[offset:offset+count];offset+=count\n p=points[ids]; n=np.cross(p[1]-p[0],p[2]-p[0]);n/=max(np.linalg.norm(n),1e-14)\n if n@cam<0: continue\n shade=.56+.44*max(n@light,0)\n col=materials[face_mats[fi]]\n tex=textures.get(face_mats[fi])\n for j in range(1,count-1):\n ix=[0,j,j+1]; pp=proj[ids[ix]];wp=points[ids[ix]]; tuv=uvs[ix]\n x0=max(0,math.floor(min(pp[:,0]))); x1=min(size-1,math.ceil(max(pp[:,0])))\n y0=max(0,math.floor(min(pp[:,1]))); y1=min(size-1,math.ceil(max(pp[:,1])))\n if x0>x1 or y0>y1:continue\n xx,yy=np.meshgrid(np.arange(x0,x1+1)+.5,np.arange(y0,y1+1)+.5)\n a,b,c=pp\n den=(b[1]-c[1])*(a[0]-c[0])+(c[0]-b[0])*(a[1]-c[1])\n if abs(den)<1e-12:continue\n w0=((b[1]-c[1])*(xx-c[0])+(c[0]-b[0])*(yy-c[1]))/den\n w1=((c[1]-a[1])*(xx-c[0])+(a[0]-c[0])*(yy-c[1]))/den;w2=1-w0-w1\n zz=w0*a[2]+w1*b[2]+w2*c[2]\n keep=(w0>=-1e-8)&(w1>=-1e-8)&(w2>=-1e-8)&(zz>zbuffer[y0:y1+1,x0:x1+1])\n if not keep.any():continue\n weights=np.stack([w0[keep],w1[keep],w2[keep]],axis=1)\n if tex is not None:\n tuv=weights@tuv; u=((tuv[:,0]%1)*tex.shape[1]).astype(int)%tex.shape[1];v=(((1-tuv[:,1])%1)*tex.shape[0]).astype(int)%tex.shape[0]; colors=tex[v,u]\n else: colors=np.tile(col,(keep.sum(),1))\n shading=np.full((keep.sum(),1),shade)\n pos=weights@wp\n if n[2]>.8:\n d1=np.minimum(np.abs(pos[:,0]-.3137),np.abs(pos[:,0]+.3137))\n d2=np.minimum(np.abs(pos[:,1]-.2497),np.abs(pos[:,1]+.2497))\n d=np.minimum(d1,d2)\n shading*=1-.18*np.exp(-d[:,None]/.010)\n colors=colors*shading\n image[y0:y1+1,x0:x1+1][keep]=colors\n zbuffer[y0:y1+1,x0:x1+1][keep]=zz[keep]\nimg=Image.fromarray((np.clip(linear_to_srgb(image),0,1)*255).astype('uint8'))\nimg.save('/tmp/preview.png');os.makedirs('/output/.thumbs/256x256',exist_ok=True);img.resize((256,256),Image.Resampling.LANCZOS).save('/output/.thumbs/256x256/asset.usd.png')\nprint('rendered /tmp/preview.png')\n" + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_tlciCbDHsiaT4UaDtBbM6YzY|fc_0516a57b3bf4c875016ad7ff11fd5487d289f226e1aaad33ab", + "content": "Successfully wrote to /tmp/render_asset.py", + "extra": { + "tool_name": "write", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 25672, + "completion_tokens": 1945, + "cached_tokens": 23496, + "extra": { + "cache_write_tokens": 2173, + "reasoning_tokens": 239, + "pi_total_tokens": 27617 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2ce7e7d0", + "pi_parent_id": "579386f3", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff09a03887d29127a2b16a914e55", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 23, + "timestamp": "2026-10-20T23:54:19.802Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_eLYSRiAFRSAoGnsvi3dhXAKD|fc_0516a57b3bf4c875016ad7ff2b03ec87d281b2ceaadf63b8bf", + "function_name": "bash", + "arguments": { + "command": "python /tmp/create_asset.py && python /tmp/render_asset.py", + "timeout": 180 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_eLYSRiAFRSAoGnsvi3dhXAKD|fc_0516a57b3bf4c875016ad7ff2b03ec87d281b2ceaadf63b8bf", + "content": "Wrote /output/asset.usd\nrendered /tmp/preview.png", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 27635, + "completion_tokens": 34, + "cached_tokens": 25669, + "extra": { + "cache_write_tokens": 1963, + "reasoning_tokens": 0, + "pi_total_tokens": 27669 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "eb8fd884", + "pi_parent_id": "ab398c97", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff29f30487d2ac045301143c3492", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 24, + "timestamp": "2026-10-20T23:54:28.409Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_lgkpUFrAZkom2WVeu257Zuyf|fc_0516a57b3bf4c875016ad7ff33c8dc87d2901c98138f4b875b", + "function_name": "read", + "arguments": { + "path": "/tmp/preview.png", + "offset": 1, + "limit": 1 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_lgkpUFrAZkom2WVeu257Zuyf|fc_0516a57b3bf4c875016ad7ff33c8dc87d2901c98138f4b875b", + "content": [ + { + "type": "text", + "text": "Read image file [image/png]" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_3.png" + } + } + ], + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 27697, + "completion_tokens": 29, + "cached_tokens": 27632, + "extra": { + "cache_write_tokens": 62, + "reasoning_tokens": 0, + "pi_total_tokens": 27726 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "d891a78f", + "pi_parent_id": "7312ce10", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff328ac487d294c80eaf30ab2340", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 25, + "timestamp": "2026-10-20T23:55:12.482Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "The first NVIDIA validation passed 40 of 46 mandatory checks. The remaining findings concern material labels, metadata, relative dependency paths, collider normals, a coincident floor collider, and the missing thumbnail. I\u2019ve inspected the report and am correcting those items without changing the single-rigid-body structure.", + "reasoning_content": "**Considering corner design**\n\nI\u2019m looking at the design differences between current hard straight 90\u00b0 front corners and the reference corners, which have rounded edges. The reference cardboard near the right bottom has a radius of about 8px, or 0.006m. It's interesting to note the contrast, especially with how the top corner is rounded too, particularly on the front-right. I\u2019m curious about the implications this has for both functionality and aesthetics in the design.", + "tool_calls": [ + { + "tool_call_id": "call_4QXpjvnhnY0KSiY7JvVd5jZh|fc_0516a57b3bf4c875016ad7ff5fc53887d294d003c5b85cf6d4", + "function_name": "mcp", + "arguments": { + "tool": "benchmark_validate_candidate", + "args": { + "request_id": "check-2" + } + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_4QXpjvnhnY0KSiY7JvVd5jZh|fc_0516a57b3bf4c875016ad7ff5fc53887d294d003c5b85cf6d4", + "content": "{\"request_id\":\"check-2\",\"snapshot_sha256\":\"49686ec3e25d3d1aebd83c4229586dc37b975c78beeea6d582a32c9db040ddb1\",\"validation_calls_used\":2,\"validation_calls_remaining\":3,\"feedback\":{\"schema_version\":\"simready-validator-feedback-v1\",\"snapshot_sha256\":\"49686ec3e25d3d1aebd83c4229586dc37b975c78beeea6d582a32c9db040ddb1\",\"reward\":100.0,\"simready\":{\"schema\":\"simready-validator-score-v1\",\"policy_id\":\"NVIDIA-Robotics-Prop-4.0.0-mandatory-95-plus-5-v1\",\"status\":\"scored\",\"score_percent\":100.0,\"base_credit_percent\":95.0,\"completion_bonus\":5,\"passed_count\":46,\"failed_count\":0,\"unknown_count\":0,\"applicable_count\":46,\"official_conformance\":{\"profile\":{\"id\":\"Robotics-Prop\",\"version\":\"4.0.0\"},\"passed\":true,\"filtered\":false},\"checks\":[{\"requirement_id\":\"com.nvidia.simready.HI.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.NP.008\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.010\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.RB.COL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.MAT.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.QCODE.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SL.TIME.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SR.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.SR.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.UN.006\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.UN.007\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.008\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.025\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VG.MESH.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.MAT.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.PS.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.simready.VM.TEX.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.AA.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.AA.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.HI.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.003\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.005\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.009\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.RB.COL.004\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.002\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.014\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.027\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.028\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VG.029\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.BIND.001\",\"status\":\"pass\",\"finding_count\":0},{\"requirement_id\":\"com.nvidia.usd.VM.PS.001\",\"status\":\"pass\",\"finding_count\":0}]},\"nvidia_validator_report\":{\"available\":true,\"report_id\":\"97a181c035fac6fb496a6e9a32d5c3f51a14cdaf59de8f8b831ba2a55f6935de\",\"sha256\":\"97a181c035fac6fb496a6e9a32d5c3f51a14cdaf59de8f8b831ba2a55f6935de\",\"bytes\":199710,\"total_characters\":199710,\"issue_counts\":{\"issues\":0,\"soft_issues\":55,\"warnings\":0,\"infos\":0},\"complete_report_available\":true,\"delivery\":\"agent_file\",\"file_path\":\"/tmp/simready-validation-reports/97a181c035fac6fb496a6e9a32d5c3f51a14cdaf59de8f8b831ba2a55f6935de.json\",\"report\":null,\"retrieval_tool\":\"get_validation_report\",\"offset_unit\":\"Unicode_code_points\",\"search_hint\":\"rg -n -m 20 -M 240 --max-columns-preview -F -e -e ; use sed -n ,p for nearby lines\",\"redactions\":\"private host paths and credential patterns only; original diagnostic wording, suggestions and candidate USD sites retained\",\"file_available\":true,\"validation_calls_consumed\":0}},\"status\":\"completed\"}", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 28972, + "completion_tokens": 1800, + "cached_tokens": 27694, + "extra": { + "cache_write_tokens": 1275, + "reasoning_tokens": 1703, + "pi_total_tokens": 30772 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "da2b9885", + "pi_parent_id": "fadcc9fc", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff355ef087d29b11ba36b006645d", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 26, + "timestamp": "2026-10-20T23:55:19.664Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_owx0qd6jJsSrbM4eptSvut3t|fc_0516a57b3bf4c875016ad7ff66686887d283fad8fb3547a957", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nimport json\np='/tmp/simready-validation-reports/97a181c035fac6fb496a6e9a32d5c3f51a14cdaf59de8f8b831ba2a55f6935de.json'\nd=json.load(open(p));print('Issues:',d['issues']);print('Soft issues:')\nfor it in d['soft_issues']:print(it['rule_id'],it.get('prim_path'),it['message'])\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_owx0qd6jJsSrbM4eptSvut3t|fc_0516a57b3bf4c875016ad7ff66686887d283fad8fb3547a957", + "content": "Issues: []\nSoft issues:\ncom.nvidia.simready.SR.001 None Required metadata fields are missing: SimReady_Metadata. Fields must be authored directly in the root layer's customLayerData.\ncom.nvidia.simready.RB.MB.001 None Not enough physics rigid bodies found under the default prim. Found 1, expected at least 2.\ncom.nvidia.simready.NVM.002 /CardboardTray/Looks/WhitePaper Required attribute \"omni:simready:nonvisual:base\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.003 /CardboardTray/Looks/WhitePaper Required attribute \"omni:simready:nonvisual:coating\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.001 /CardboardTray/Looks/WhitePaper Required attribute \"omni:simready:nonvisual:attributes\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.002 /CardboardTray/Looks/FlutedCore Required attribute \"omni:simready:nonvisual:base\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.003 /CardboardTray/Looks/FlutedCore Required attribute \"omni:simready:nonvisual:coating\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.001 /CardboardTray/Looks/FlutedCore Required attribute \"omni:simready:nonvisual:attributes\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.002 /CardboardTray/Looks/KraftLiner Required attribute \"omni:simready:nonvisual:base\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.003 /CardboardTray/Looks/KraftLiner Required attribute \"omni:simready:nonvisual:coating\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.001 /CardboardTray/Looks/KraftLiner Required attribute \"omni:simready:nonvisual:attributes\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.002 /CardboardTray/Looks/ExposedFlute Required attribute \"omni:simready:nonvisual:base\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.003 /CardboardTray/Looks/ExposedFlute Required attribute \"omni:simready:nonvisual:coating\" for nonvisual material doesn't exist.\ncom.nvidia.simready.NVM.001 /CardboardTray/Looks/ExposedFlute Required attribute \"omni:simready:nonvisual:attributes\" for nonvisual material doesn't exist.\ncom.nvidia.simready.ISA.001 /CardboardTray Incomplete Isaac Sim composition: performance robot layout; missing layers: base, geometries, instances, materials.\ncom.nvidia.simready.GSP.001 /CardboardTray Asset must have at least one grasp vector prim.\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/BottomBoard GPrim '/CardboardTray/Geometry/BottomBoard' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/TallLongWall GPrim '/CardboardTray/Geometry/TallLongWall' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/LowFoldedLongWall GPrim '/CardboardTray/Geometry/LowFoldedLongWall' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/BackPanelCore GPrim '/CardboardTray/Geometry/BackPanelCore' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/BackOuterWhiteLiner GPrim '/CardboardTray/Geometry/BackOuterWhiteLiner' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/BackInnerKraftLiner GPrim '/CardboardTray/Geometry/BackInnerKraftLiner' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/BackCutEdgeFluting GPrim '/CardboardTray/Geometry/BackCutEdgeFluting' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/FrontPanelCore GPrim '/CardboardTray/Geometry/FrontPanelCore' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/FrontOuterWhiteLiner GPrim '/CardboardTray/Geometry/FrontOuterWhiteLiner' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/FrontInnerKraftLiner GPrim '/CardboardTray/Geometry/FrontInnerKraftLiner' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/FrontCutEdgeFluting GPrim '/CardboardTray/Geometry/FrontCutEdgeFluting' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/TallSideFloorCrease GPrim '/CardboardTray/Geometry/TallSideFloorCrease' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.DISP.001 /CardboardTray/Geometry/LowSideFloorCrease GPrim '/CardboardTray/Geometry/LowSideFloorCrease' does not resolve a 'primvars:displayColor', authored on the prim or inherited from an ancestor\ncom.nvidia.simready.NP.006 None Asset 'asset' has no metadata. Metadata must be stored in custom layer data as 'SimReady_Metadata' or a sidecar JSON file.\ncom.nvidia.simready.VM.PBR.003 /CardboardTray/Looks/WhitePaper/UV input 'varname' on '/CardboardTray/Looks/WhitePaper/UV' has type token, nodedef declares string\ncom.nvidia.simready.VM.BIND.002 /CardboardTray/Looks/WhitePaper/UV Type mismatch for: inputs:varname\texpected: string\tactual: token\ncom.nvidia.simready.VM.PBR.003 /CardboardTray/Looks/KraftLiner/UV input 'varname' on '/CardboardTray/Looks/KraftLiner/UV' has type token, nodedef declares string\ncom.nvidia.simready.VM.BIND.002 /CardboardTray/Looks/KraftLiner/UV Type mismatch for: inputs:varname\texpected: string\tactual: token\ncom.nvidia.simready.VM.PBR.001 /CardboardTray/Looks/WhitePaper material '/CardboardTray/Looks/WhitePaper' is bound for rendering but connects no OpenPBR final surface: it connects outputs:surface, and not 'outputs:mtlx:surface'\ncom.nvidia.simready.VM.PBR.001 /CardboardTray/Looks/KraftLiner material '/CardboardTray/Looks/KraftLiner' is bound for rendering but connects no OpenPBR final surface: it connects outputs:surface, and not 'outputs:mtlx:surface'\ncom.nvidia.simready.VM.PBR.001 /CardboardTray/Looks/FlutedCore material '/CardboardTray/Looks/FlutedCore' is bound for rendering but connects no OpenPBR final surface: it connects outputs:surface, and not 'outputs:mtlx:surface'\ncom.nvidia.simready.VM.MDL.003 /CardboardTray/Looks/WhitePaper material '/CardboardTray/Looks/WhitePaper' is bound for rendering and connects no 'outputs:mdl:surface', so the asset does not have an MDL final surface on the geometry it renders: it connects outputs:surface\ncom.nvidia.simready.VM.MDL.003 /CardboardTray/Looks/KraftLiner material '/CardboardTray/Looks/KraftLiner' is bound for rendering and connects no 'outputs:mdl:surface', so the asset does not have an MDL final surface on the geometry it renders: it connects outputs:surface\ncom.nvidia.simready.VM.MDL.003 /CardboardTray/Looks/FlutedCore material '/CardboardTray/Looks/FlutedCore' is bound for rendering and connects no 'outputs:mdl:surface', so the asset does not have an MDL final surface on the geometry it renders: it connects outputs:surface\ncom.nvidia.simready.VM.PBR.001 /CardboardTray/Looks/ExposedFlute material '/CardboardTray/Looks/ExposedFlute' is bound for rendering but connects no OpenPBR final surface: it connects outputs:surface, and not 'outputs:mtlx:surface'\ncom.nvidia.simready.VM.MDL.003 /CardboardTray/Looks/ExposedFlute material '/CardboardTray/Looks/ExposedFlute' is bound for rendering and connects no 'outputs:mdl:surface', so the asset does not have an MDL final surface on the geometry it renders: it connects outputs:surface\ncom.nvidia.simready.MUJOCO.COL.001 /CardboardTray/Colliders/Bottom MuJoCo collider '/CardboardTray/Colliders/Bottom' must apply MjcCollisionAPI.\ncom.nvidia.simready.MUJOCO.COL.001 /CardboardTray/Colliders/TallLongWallCollider MuJoCo collider '/CardboardTray/Colliders/TallLongWallCollider' must apply MjcCollisionAPI.\ncom.nvidia.simready.MUJOCO.COL.001 /CardboardTray/Colliders/LowFoldedLongWallCollider MuJoCo collider '/CardboardTray/Colliders/LowFoldedLongWallCollider' must apply MjcCollisionAPI.\ncom.nvidia.simready.MUJOCO.COL.001 /CardboardTray/Colliders/BackEndCollider MuJoCo collider '/CardboardTray/Colliders/BackEndCollider' must apply MjcCollisionAPI.\ncom.nvidia.simready.MUJOCO.COL.001 /CardboardTray/Colliders/FrontEndCollider MuJoCo collider '/CardboardTray/Colliders/FrontEndCollider' must apply MjcCollisionAPI.\ncom.nvidia.simready.RV.007 /CardboardTray Default prim must declare a 'MuJoCo' physics runtime variant set.\ncom.nvidia.simready.RV.004 /CardboardTray Default prim must declare a 'Newton' physics runtime variant set.\ncom.nvidia.simready.NEWTON.COL.001 /CardboardTray/Colliders/Bottom Newton mesh collider '/CardboardTray/Colliders/Bottom' must apply either NewtonMeshCollisionAPI or NewtonSDFCollisionAPI.\ncom.nvidia.simready.NEWTON.COL.001 /CardboardTray/Colliders/TallLongWallCollider Newton mesh collider '/CardboardTray/Colliders/TallLongWallCollider' must apply either NewtonMeshCollisionAPI or NewtonSDFCollisionAPI.\ncom.nvidia.simready.NEWTON.COL.001 /CardboardTray/Colliders/LowFoldedLongWallCollider Newton mesh collider '/CardboardTray/Colliders/LowFoldedLongWallCollider' must apply either NewtonMeshCollisionAPI or NewtonSDFCollisionAPI.\ncom.nvidia.simready.NEWTON.COL.001 /CardboardTray/Colliders/BackEndCollider Newton mesh collider '/CardboardTray/Colliders/BackEndCollider' must apply either NewtonMeshCollisionAPI or NewtonSDFCollisionAPI.\ncom.nvidia.simready.NEWTON.COL.001 /CardboardTray/Colliders/FrontEndCollider Newton mesh collider '/CardboardTray/Colliders/FrontEndCollider' must apply either NewtonMeshCollisionAPI or NewtonSDFCollisionAPI.\ncom.nvidia.simready.RV.001 /CardboardTray Default prim must declare a 'PhysX' physics runtime variant set.", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 32411, + "completion_tokens": 156, + "cached_tokens": 28969, + "extra": { + "cache_write_tokens": 3439, + "reasoning_tokens": 21, + "pi_total_tokens": 32567 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "a8b2e892", + "pi_parent_id": "0a8bec10", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff63aa6087d2b61e84295ad0bad1", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 27, + "timestamp": "2026-10-20T23:55:33.442Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Mapping image perspective**\n\nI'm figuring out how to approximate a perspective warp to map a quadrilateral in an image to normalized dimensions. I want to gain a better understanding of the base colors and the grain present in the image. It seems essential to focus on the area that is cropped near the floor to ensure everything aligns well. There\u2019s quite a bit to unpack, but I\u2019m on the right track!", + "tool_calls": [ + { + "tool_call_id": "call_zFgvTJcROikQ1tOCaYT8vkqN|fc_0516a57b3bf4c875016ad7ff74a67887d2b1e9271f4051499d", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nfrom PIL import Image\nim=Image.open('/task/thumbnail.png');im.crop((365,404,623,566)).resize((774,486)).save('/tmp/floor_ref.png')\nPY", + "timeout": 30 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_zFgvTJcROikQ1tOCaYT8vkqN|fc_0516a57b3bf4c875016ad7ff74a67887d2b1e9271f4051499d", + "content": "(no output)", + "extra": { + "tool_name": "bash", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 35246, + "completion_tokens": 544, + "cached_tokens": 32408, + "extra": { + "cache_write_tokens": 2835, + "reasoning_tokens": 471, + "pi_total_tokens": 35790 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "fdaccd1a", + "pi_parent_id": "f5ad1af5", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff68f59487d2b54a1ff02f3e0ee0", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 28, + "timestamp": "2026-10-20T23:55:36.510Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "tool_calls": [ + { + "tool_call_id": "call_P8nptDGnY9OjDdGfSvWU2zOo|fc_0516a57b3bf4c875016ad7ff77ca5487d2acf1dedb11dcc293", + "function_name": "read", + "arguments": { + "path": "/tmp/floor_ref.png", + "offset": 1, + "limit": 1 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_P8nptDGnY9OjDdGfSvWU2zOo|fc_0516a57b3bf4c875016ad7ff77ca5487d2acf1dedb11dcc293", + "content": [ + { + "type": "text", + "text": "Read image file [image/png]" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_4.png" + } + } + ], + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 35804, + "completion_tokens": 30, + "cached_tokens": 35243, + "extra": { + "cache_write_tokens": 558, + "reasoning_tokens": 0, + "pi_total_tokens": 35834 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "0e6a5926", + "pi_parent_id": "1110e17b", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff76872487d2a899805884092e88", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 29, + "timestamp": "2026-10-20T23:56:20.041Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Evaluating shader output**\n\nI need to evaluate the light color output for a white wall, which I'm assuming is .86 coming from .868, and it's near 1. For this, I'll use the kraft base values of .89, .80, and .625. The floor might yield a comparable output of .89 as well. It's all about balancing those values to see how they interact within the shader context. I want to get this right!\n**Evaluating shading and mapping**\n\nI\u2019m analyzing the shading and color choices, aiming for well-lit shades and a consistent reference. A slight lighter tone looks better \u2014 something like .89, .795, .61. I notice the current variance might not be sufficient. The texture is higher than the reference, but I want to ensure it still appears white. Fixing the floor plane mapping really changes the overall look. I need to generate rounded ends and corner rolls, adjusting dimensions for accuracy.\n\n**Adjusting dimensions and metadata**\n\nI'm working on adjustments for the low side, leaning the top inward by .006, which gives me a near-offset that aligns closely with the target. I notice I might need to update some coordinates and make sure the dimensions are fitting correctly, particularly the ramps and sides. Having small adjustments for corners and UV materials is critical, so I can consider using meaningful JSON strings in the metadata, ensuring it aligns with SimReady standards. It feels like I\u2019m getting closer!\n\n**Setting metadata and naming**\n\nI\u2019m thinking about how existing fields can duplicate, and I need to ensure the metadata is correct, specifically using 'SimReady_Metadata' as a dictionary. It looks like the asset_name might need to match \"asset,\" and I should confirm that it aligns with the file name, especially since there\u2019s an optional parameter, NP.006. If the name isn\u2019t matching right now, it might cause some issues. Rounding the end profile through a function should help with the orientation \u2014 just need to keep everything in check!\n**Adjusting silhouette and texture**\n\nI think we can start by rounding the edges of the end sheet to enhance the silhouette a bit. Just a slight change could improve the overall look. I also feel that revising the texture will be sufficient to make a noticeable difference. It's all in those little details that often go a long way, so I want to make sure I'm considering every aspect of this carefully!", + "tool_calls": [ + { + "tool_call_id": "call_hGPtaMZuSqhMUStRBbKuwHv6|fc_0516a57b3bf4c875016ad7ff99b3c087d282fe10ab398ca2e6", + "function_name": "edit", + "arguments": { + "path": "/tmp/create_asset.py", + "edits": [ + { + "oldText": "var=.023*noise(80,115)+.018*noise(280,500)+.018*noise(600,850)+.022*noise(25,50)", + "newText": "var=.023*noise(115,80)+.018*noise(500,280)+.018*noise(850,600)+.022*noise(50,25)" + }, + { + "oldText": "var=.08*noise(140,35)+.055*noise(700,100)+.032*noise(400,500)+.030*noise(45,24)\n fiber=noise(1000,80)*.023\n base=np.array([.840,.738,.532])", + "newText": "var=.065*noise(140,35)+.040*noise(700,100)+.025*noise(400,500)+.030*noise(45,24)\n fiber=noise(1000,80)*.013\n base=np.array([.890,.795,.610])" + }, + { + "oldText": " sh.CreateInput('diffuseColor',Sdf.ValueTypeNames.Color3f).Set(Gf.Vec3f(*color))", + "newText": " sh.CreateInput('diffuseColor',Sdf.ValueTypeNames.Color3f).Set(Gf.Vec3f(*color))\n mat.GetPrim().CreateAttribute('omni:simready:nonvisual:base',Sdf.ValueTypeNames.String).Set('paper')" + }, + { + "oldText": "Sdf.ValueTypeNames.Token).Set('st')", + "newText": "Sdf.ValueTypeNames.String).Set('st')" + }, + { + "oldText": "kraft=material('KraftLiner',(.840,.738,.532),.94,'kraft')", + "newText": "kraft=material('KraftLiner',(.890,.795,.610),.94,'kraft')" + }, + { + "oldText": "elif abs(n[2])>.8: ax=[0,1]", + "newText": "elif abs(n[2])>.8: ax=[1,0]" + }, + { + "oldText": " UsdShade.MaterialBindingAPI.Apply(m.GetPrim()).Bind(mat)\n if face_mats:", + "newText": " UsdShade.MaterialBindingAPI.Apply(m.GetPrim()).Bind(mat)\n display=stage.GetPrimAtPath(str(mat.GetPath())+'/Surface').GetAttribute('inputs:diffuseColor').Get()\n m.CreateDisplayColorAttr([display])\n if face_mats:" + }, + { + "oldText": "profile=[(-W/2+.0002,.0007),(W/2-.0002,.0007),(W/2-.0002,LOW),(W/2-RAMP,H),(-W/2+.0002,H)]", + "newText": "radius=.0045\nprofile=[(-W/2+radius,0),(W/2-radius,0)]\nfor j in range(1,7):\n angle=-math.pi/2+j*math.pi/12\n profile.append((W/2-radius+radius*math.cos(angle),radius+radius*math.sin(angle)))\nprofile.extend([(W/2,LOW),(W/2-RAMP,H),(-W/2+.0005,H),(-W/2,H-.0005),(-W/2,radius)])\nfor j in range(1,6):\n angle=math.pi+j*math.pi/12\n profile.append((-W/2+radius+radius*math.cos(angle),radius+radius*math.sin(angle)))" + }, + { + "oldText": "p=[(y,z-(top_delta if i>=2 else 0)) for i,(y,z) in enumerate(profile)]", + "newText": "p=[(y,z-(top_delta if z>.02 else 0)) for i,(y,z) in enumerate(profile)]" + }, + { + "oldText": "# Self-contained asset; no lights, cameras or ground plane are included.\nstage.GetRootLayer().Save()", + "newText": "# Self-contained asset; no lights, cameras or ground plane are included.\nmetadata=dict(stage.GetRootLayer().customLayerData)\nmetadata['SimReady_Metadata']=dict(metadata)\nstage.GetRootLayer().customLayerData=metadata\nstage.GetRootLayer().Save()" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_hGPtaMZuSqhMUStRBbKuwHv6|fc_0516a57b3bf4c875016ad7ff99b3c087d282fe10ab398ca2e6", + "content": "Successfully replaced 10 block(s) in /tmp/create_asset.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 36332, + "completion_tokens": 2416, + "cached_tokens": 35801, + "extra": { + "cache_write_tokens": 528, + "reasoning_tokens": 1499, + "pi_total_tokens": 38748 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "1bb7303b", + "pi_parent_id": "aab1790c", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad7ff7996c487d2b2f6539528f23218", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 30, + "timestamp": "2026-10-20T23:56:25.928Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Reviewing nonvisual parameters**\n\nI'm analyzing the optional nonvisual value 'paper' and wondering if it's expected to be an asset reference instead of a string. It's tricky\u2014should I avoid adding unnecessary options that aren't fully formed? I removed nonvisual creation afterward, but now I think maybe the optional base needs to be an enum. Current tool feedback has nonvisual attributes absent, so it might be better to remove it entirely to avoid confusion. I need to stick to established standards and run the render accordingly.", + "tool_calls": [ + { + "tool_call_id": "call_1uQSeWRZqA9lsZrsHXVsmaqi|fc_0516a57b3bf4c875016ad7ffa91ba087d2a890bd5db83966d8", + "function_name": "edit", + "arguments": { + "path": "/tmp/create_asset.py", + "edits": [ + { + "oldText": " mat.GetPrim().CreateAttribute('omni:simready:nonvisual:base',Sdf.ValueTypeNames.String).Set('paper')\n", + "newText": "" + } + ] + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_1uQSeWRZqA9lsZrsHXVsmaqi|fc_0516a57b3bf4c875016ad7ffa91ba087d2a890bd5db83966d8", + "content": "Successfully replaced 1 block(s) in /tmp/create_asset.py.", + "extra": { + "tool_name": "edit", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 38772, + "completion_tokens": 162, + "cached_tokens": 36329, + "extra": { + "cache_write_tokens": 2440, + "reasoning_tokens": 93, + "pi_total_tokens": 38934 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": 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":0}]},\"nvidia_validator_report\":{\"available\":true,\"report_id\":\"5b3f461187e3411dd07091f5448bfd23c74879d6654709f5905d45aa84720a42\",\"sha256\":\"5b3f461187e3411dd07091f5448bfd23c74879d6654709f5905d45aa84720a42\",\"bytes\":185264,\"total_characters\":185264,\"issue_counts\":{\"issues\":0,\"soft_issues\":36,\"warnings\":0,\"infos\":0},\"complete_report_available\":true,\"delivery\":\"agent_file\",\"file_path\":\"/tmp/simready-validation-reports/5b3f461187e3411dd07091f5448bfd23c74879d6654709f5905d45aa84720a42.json\",\"report\":null,\"retrieval_tool\":\"get_validation_report\",\"offset_unit\":\"Unicode_code_points\",\"search_hint\":\"rg -n -m 20 -M 240 --max-columns-preview -F -e -e ; use sed -n ,p for nearby lines\",\"redactions\":\"private host paths and credential patterns only; original diagnostic wording, suggestions and candidate USD sites retained\",\"file_available\":true,\"validation_calls_consumed\":0}},\"status\":\"completed\"}", + "extra": { + "tool_name": "mcp", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 44270, + "completion_tokens": 40, + "cached_tokens": 44205, + "extra": { + "cache_write_tokens": 62, + "reasoning_tokens": 9, + "pi_total_tokens": 44310 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "a3c421b6", + "pi_parent_id": "99d818fa", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad800121e9c87d2b20b1857eec103e0", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 41, + "timestamp": "2026-10-20T23:58:21.103Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "", + "reasoning_content": "**Inspecting final report**\n\nI need to complete a final inspection report, and it looks like there won\u2019t be any more modifications. I should check the scene for any bugs, especially focusing on fluting at the top cap and ensuring the wave normals are corrected. It seems like that\u2019s a good plan to finalize everything! I'm feeling a bit excited to wrap this up successfully and ensure everything is in order.", + "tool_calls": [ + { + "tool_call_id": "call_BA2AzwuG9eBBqoSBUOynQXao|fc_0516a57b3bf4c875016ad8001cb7fc87d294b25e7642b77e28", + "function_name": "bash", + "arguments": { + "command": "python - <<'PY'\nimport json, os\np='/tmp/simready-validation-reports/5b3f461187e3411dd07091f5448bfd23c74879d6654709f5905d45aa84720a42.json'\nd=json.load(open(p));print('NVIDIA report:',d['outcome'],'passed=',d['passed']);print('Mandatory issues:',len(d['issues']),'warnings:',len(d['warnings']));print('Optional finding IDs:',sorted({i['rule_id'] for i in d['soft_issues']}))\nfor root,dirs,files in os.walk('/output'):\n for f in files: print(os.path.join(root,f),os.path.getsize(os.path.join(root,f)))\nPY", + "timeout": 30 + } + }, + { + "tool_call_id": "call_PdOHAyy251H4Ub5KNFkmYAKt|fc_0516a57b3bf4c875016ad8001cb81087d291ca4597d175621f", + "function_name": "read", + "arguments": { + "path": "/tmp/preview.png", + "offset": 1, + "limit": 1 + } + } + ], + "observation": { + "results": [ + { + "source_call_id": "call_BA2AzwuG9eBBqoSBUOynQXao|fc_0516a57b3bf4c875016ad8001cb7fc87d294b25e7642b77e28", + "content": "NVIDIA report: success passed= True\nMandatory issues: 0 warnings: 0\nOptional finding IDs: ['com.nvidia.simready.GSP.001', 'com.nvidia.simready.ISA.001', 'com.nvidia.simready.MUJOCO.COL.001', 'com.nvidia.simready.NEWTON.COL.001', 'com.nvidia.simready.NVM.001', 'com.nvidia.simready.NVM.002', 'com.nvidia.simready.NVM.003', 'com.nvidia.simready.RB.MB.001', 'com.nvidia.simready.RV.001', 'com.nvidia.simready.RV.004', 'com.nvidia.simready.RV.007', 'com.nvidia.simready.VM.MDL.003', 'com.nvidia.simready.VM.PBR.001']\n/output/asset.usd 703554\n/output/.thumbs/256x256/asset.usd.png 43830\n/output/textures/kraft_normal.png 2443944\n/output/textures/kraft_paper.png 1503943\n/output/textures/white_normal.png 2442787\n/output/textures/white_paper.png 1722086", + "extra": { + "tool_name": "bash", + "is_error": false + } + }, + { + "source_call_id": "call_PdOHAyy251H4Ub5KNFkmYAKt|fc_0516a57b3bf4c875016ad8001cb81087d291ca4597d175621f", + "content": [ + { + "type": "text", + "text": "Read image file [image/png]" + }, + { + "type": "image", + "source": { + "media_type": "image/png", + "path": "images/pi_image_7.png" + } + } + ], + "extra": { + "tool_name": "read", + "is_error": false + } + } + ] + }, + "metrics": { + "prompt_tokens": 45937, + "completion_tokens": 257, + "cached_tokens": 44267, + "extra": { + "cache_write_tokens": 1667, + "reasoning_tokens": 29, + "pi_total_tokens": 46194 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "18068524", + "pi_parent_id": "32e71366", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad80017fe1887d29d6aa21fe4decc81", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + }, + { + "step_id": 42, + "timestamp": "2026-10-20T23:58:27.096Z", + "source": "agent", + "model_name": "harbor-endpoint/gpt-6.1-sol", + "message": "The asset matches the supplied XYZ dimensions exactly and has no unresolved dependencies. I checked the final preview and NVIDIA report: all 46 mandatory requirements pass, with no mandatory findings or warnings. The tray remains one rigid body with compound colliders and no artificial joints.", + "reasoning_content": "**Reviewing design details**\n\nI'm noting that the reference for the front left low wall shape with the shoulder reference looks correct. The material pattern seems to resemble OSB with a light, broad white appearance, which is fine based on the image nearby. I also think we shouldn\u2019t overspend on this project, so it\u2019s important to keep that in mind as I prepare to submit everything. I want to make sure everything is accurate and ready!", + "tool_calls": [ + { + "tool_call_id": "call_n38Kpdf6h4fHidwp3djsjfPR|fc_0516a57b3bf4c875016ad800221f2087d2a4544b2c6fdc93b6", + "function_name": "mcp", + "arguments": { + "tool": "benchmark_submit_asset", + "args": { + "request_id": "final" + } + } + } + ], + "observation": { + "results": [] + }, + "metrics": { + "prompt_tokens": 47702, + "completion_tokens": 133, + "cached_tokens": 45934, + "extra": { + "cache_write_tokens": 1765, + "reasoning_tokens": 45, + "pi_total_tokens": 47835 + } + }, + "llm_call_count": 1, + "extra": { + "pi_event_id": "2670b999", + "pi_parent_id": "f3523a72", + "provider": "harbor-endpoint", + "api": "openai-responses", + "response_id": "resp_0516a57b3bf4c875016ad8001e93bc87d2ae31ff19a5d96aa0", + "response_model": null, + "stop_reason": "toolUse", + "raw_stop_reason": "completed" + } + } + ], + "final_metrics": { + "total_prompt_tokens": 1062333, + "total_completion_tokens": 21815, + 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from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_002_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_003_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_003_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_003_NEWTON' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_003_NEWTON-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_003_PHYSX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_003_PHYSX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_003_PHYSX' version '0.2.0' from 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/opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_003_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_NEWTON' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_NEWTON-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_PHYSX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_PHYSX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_PHYSX' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_PHYSX-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_PHYSX' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_PHYSX-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_PHYSX' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_PHYSX-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_NEWTON' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_NEWTON-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_PHYSX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_PHYSX' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_PHYSX' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_ROBOT_PHYSX' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_ROBOT_PHYSX-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_004_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_004_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_005_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_005_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_006_MDL' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_006_MDL-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_006_MDL' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_006_MDL-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_006_OPENPBR' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_006_OPENPBR-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_006_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_006_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_006_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_006_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_007_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_007_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_010_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_010_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_011_RTX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_011_RTX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_011_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_011_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_021_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_021_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_021_ISAAC' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_021_ISAAC-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_021_ISAAC' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_021_ISAAC-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_ISAAC' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_ISAAC-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_NEWTON' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_NEWTON-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_PHYSX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_PHYSX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_PHYSX' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_PHYSX-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_022_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_022_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_023_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_023_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_024_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_024_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_024_NEWTON' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_024_NEWTON-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_024_PHYSX' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_024_PHYSX-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_024_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_024_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_025_ROS' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_025_ROS-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_028_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_028_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_028_MUJOCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_028_MUJOCO-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_028_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_028_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_030_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_030_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_031_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_031_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_032_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_032_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_033_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_033_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_033_STANDARD' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_033_STANDARD-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_033_STANDARD' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_033_STANDARD-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_033_STANDARD' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_033_STANDARD-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_040_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_040_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_041_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_041_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_042_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_042_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_043_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_043_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_044_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_044_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_045_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_045_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_046_STANDARD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_046_STANDARD-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.2.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.3.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_100_ISAAC' version '0.4.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_100_ISAAC-0.4.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering feature 'FET_101_ISAAC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/features/FET_101_ISAAC-0.1.0.json" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-COCO' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-Cityscapes' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-ADE20K' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-PascalVOC' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-SUNRGBD' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Open-Taxonomy-ImageNet1K' version '0.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/open_taxonomy_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-NoBOM' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Package-Candidate' version '1.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/package_profiles.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '2.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Body' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_body.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '2.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robot-Gripper' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robot_gripper.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.1.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.2.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '3.3.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Registering profile 'Robotics-Prop' version '4.0.0' from /opt/simready/venv/lib/python3.12/site-packages/simready/foundation/tier_core/profiles/robotics_prop.toml" + }, + { + "level": "WARNING", + "logger": "root", + "message": "DeprecationWarning: Use find() instead" + }, + { + "level": "WARNING", + "logger": "root", + "message": "File /opt/simready/venv/lib/python3.12/site-packages/simready/validate/api.py, line 485, in _build_features_validation_summary" + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.RB.MB.001'] did not pass for feature FET_004_STANDARD." + }, + { + "level": "INFO", + "logger": "simready.validate", + "message": "Optional requirements ['com.nvidia.simready.NVM.001', 'com.nvidia.simready.NVM.002', 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sha256:92a78ac0c3b06b8db6b3b80599aa58f7e0dbcbf84c8aaf998acb4bc5c43f0dff +size 103520 diff --git a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/reference-side-4.png b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/reference-side-4.png new file mode 100644 index 0000000000000000000000000000000000000000..58b08e0dc3707f1b4d687f9e94d60e245cf2cb9d --- /dev/null +++ b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/evidence/box_cardboard_open_a01/reconstruction-4/reference-side-4.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5b7b5111fd0ed17c3d676ece44807e874e5bf895656086124af34509731558c8 +size 38146 diff --git a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html index 7767453f0743cfc5e1b85e507f1699e3045717ff..ca1c8a82b6cd5532851498e700a1e3eebde10aac 100644 --- a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html +++ b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html @@ -1 +1 @@ -SimReadyBench results

SimReadyBench results

Formal fidelity measures SimReady Robotics-Prop requirements. Visual fidelity combines shape and appearance materials. Kinematic fidelity measures joint recovery and motion correspondence. Each score is reported independently.

18 of 100 reconstruction attempts completed.

Scores CSV | Detailed results JSON

Results by asset

AssetModelHarnessSkillsRepetitionStatusFormal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
accessory_eyeglasses_a01gpt-6.1-solpinone1completed100% (46/46)40.21% (0.804287/2)0% (0/2)72.55% (37/51)52.24% (0.5224/1)19.32% (0.772785/4)0% (0/29)13.91% (2134/15341)5030782.55685.581496445302581526703Not measuredNot measuredNot measured
accessory_eyeglasses_a01gpt-6.1-solpinone2completed100% (46/46)66.28% (1.32561/2)0% (0/2)64.71% (33/51)79.03% (0.790262/1)37.83% (1.51339/4)62.07% (18/29)56.49% (8666/15341)4030578.87501.9977861228121000673Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone1completed100% (46/46)80.4% (1.60807/2)N/A70.59% (36/51)82.18% (0.821836/1)82.18% (0.821836/1)N/A44.95% (6444/14336)2930431.15384.2755840016418574818Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)83.63% (0.836295/1)83.63% (0.836295/1)N/A34.05% (4881/14336)2920407.12352.8557454016108590648Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone3completed100% (46/46)0% (0/2)N/A74.51% (38/51)77.87% (0.778707/1)77.87% (0.778707/1)N/A30.91% (4431/14336)3230463.45405.8171765617729735385Not measuredNot measuredNot measured
bucket_utility_red_a01gpt-6.1-solpinone1completed100% (46/46)41.49% (0.829812/2)0.01% (0.000121476/1)76.47% (39/51)54.74% (0.547449/1)28.71% (0.574159/2)63.64% (7/11)31.4% (5136/16356)4340805.12716.051649778315561681334Not measuredNot measuredNot measured
bucket_utility_red_a01gpt-6.1-solpinone2completed100% (46/46)43.33% (0.866571/2)0.34% (0.00336069/1)70.59% (36/51)58.21% (0.58211/1)29.27% (0.585487/2)54.55% (6/11)32.31% (5285/16356)3520532.75470.8378965220782810434Not measuredNot measuredNot measured
chair_office_amf_black_a01gpt-6.1-solpinone1completed100% (46/46)76.44% (1.52878/2)0% (0/1)68.63% (35/51)74.46% (0.744639/1)21.7% (0.216991/1)N/A31.78% (5207/16384)3430703.39625.7189808527574925659Not measuredNot measuredNot measured
chair_office_amf_black_a01gpt-6.1-solpinone2completed100% (46/46)43.66% (0.873218/2)N/A68.63% (35/51)59.83% (0.598322/1)59.83% (0.598322/1)N/A23.96% (3925/16384)4030633.2558.551060920244431085363Not measuredNot measuredNot measured
cleaning_cloth_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)97.57% (0.975744/1)97.57% (0.975744/1)N/A14.29% (2048/14336)3720634.25500.9687451721134895651Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone1completed100% (46/46)80.72% (1.61437/2)N/A74.51% (38/51)81.71% (0.817125/1)81.71% (0.817125/1)N/A29.9% (4899/16384)3630562.03496.6689682921319918148Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone2completed100% (46/46)90.98% (1.81958/2)N/A74.51% (38/51)90.94% (0.909423/1)90.94% (0.909423/1)N/A68.26% (11184/16384)3220366.66320.6752012414220534344Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone3completed100% (46/46)0% (0/2)N/A66.67% (34/51)81.06% (0.810559/1)81.06% (0.810559/1)N/A49.19% (8060/16384)2920383.45331.6752314214382537524Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone4completed100% (46/46)86.65% (1.73301/2)N/A74.51% (38/51)87.47% (0.874685/1)87.47% (0.874685/1)N/A64.38% (10548/16384)3130427.21364.4558386517011600876Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone1completed100% (46/46)88.94% (1.77876/2)N/A68.63% (35/51)83.03% (0.83032/1)83.03% (0.83032/1)N/A68.05% (9755/14336)3520585.38498.6968569820938706636Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)92.25% (0.922452/1)92.25% (0.922452/1)N/A13.35% (1914/14336)3530476.47420.9479247518052810527Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone3completed100% (46/46)94.44% (1.88877/2)0% (0/1)76.47% (39/51)93.91% (0.939092/1)50% (0.5/1)N/A65.85% (9440/14336)2820476.92398.7663111317682648795Not measuredNot measuredNot measured
food_beverage_coffeeCup_a01gpt-6.1-solpinone1completed100% (46/46)72.53% (1.45061/2)100% (1/1)74.51% (38/51)95.87% (0.95874/1)95.2% (1.90396/2)88.89% (8/9)31.53% (6458/20480)4730595.82538.511221647216701243317Not measuredNot measuredNot measured

accessory_eyeglasses_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)40.21% (0.804287/2)0% (0/2)72.55% (37/51)52.24% (0.5224/1)19.32% (0.772785/4)0% (0/29)13.91% (2134/15341)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
5030782.55685.581496445302581526703Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape52.240.5224/111100
Rigid parts19.320.772785/444100
Joints00/292929100
Materials13.912134/15341153411534162.42

Appearance materials

Score (%)Earned/eligibleStatus
30.96634/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/11/1100
Moving joints00/44/4100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_arm_02_joint_00Not measured0Not measuredmissing_joint
/RootNode/Joints/joint_arm_01_joint_00Not measured0Not measuredmissing_joint
/RootNode/Joints/joint_glass_01_joint_00Not measured0Not measuredmissing_joint

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
55.9149.0220483.349.1922.17

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/arm_01_obj_00/Sunglasses/RightTemple0
/RootNode/Geometry/arm_02_obj_00/Sunglasses/LeftTemple0
/RootNode/Geometry/base_01_obj_00Not measured0
/RootNode/Geometry/glass_01_obj_00/Sunglasses/Front77.28

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
320/29

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled3/44/4
body_kinematic3/44/4

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity0/33/3
joint_enabled0/33/3
body0_enabled0/33/3
body0_kinematic0/33/3
body1_enabled0/33/3
body1_kinematic0/33/3
anchors0/33/3
axes0/22/2
relative_orientation0/33/3
limits0/22/2
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1004/204849.02
visual:metallic126/100512.54
visual:opacity1004/204849.02

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

accessory_eyeglasses_a01: Reference: front
Reference: front | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
accessory_eyeglasses_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
accessory_eyeglasses_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
accessory_eyeglasses_a01: Reference: side
Reference: side | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

accessory_eyeglasses_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)66.28% (1.32561/2)0% (0/2)64.71% (33/51)79.03% (0.790262/1)37.83% (1.51339/4)62.07% (18/29)56.49% (8666/15341)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4030578.87501.9977861228121000673Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape79.030.790262/111100
Rigid parts37.831.51339/444100
Joints62.0718/292929100
Materials56.498666/15341153411534162.42

Appearance materials

Score (%)Earned/eligibleStatus
55.591138.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/11/1100
Moving joints7.960.318493/44/4100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_arm_02_joint_00/Sunglasses/RightFoldingHinge7.749.06measured_motion
/RootNode/Joints/joint_arm_01_joint_00/Sunglasses/LeftFoldingHinge8.188.77measured_motion
/RootNode/Joints/joint_glass_01_joint_00Not measured0Not measuredmissing_joint

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
81.5476.6620483.343.457.18

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/arm_01_obj_00/Sunglasses/LeftTemple55.43
/RootNode/Geometry/arm_02_obj_00/Sunglasses/RightTemple52.82
/RootNode/Geometry/base_01_obj_00/Sunglasses/FrontAssembly43.09
/RootNode/Geometry/glass_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
3218/29

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled3/44/4
body_kinematic3/44/4

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity2/33/3
joint_enabled2/33/3
body0_enabled2/33/3
body0_kinematic2/33/3
body1_enabled2/33/3
body1_kinematic2/33/3
anchors0/33/3
axes2/22/2
relative_orientation2/33/3
limits2/22/2
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1570/204876.66
physics:density0/20480
physics:dynamicFriction1259/204861.47
physics:restitution1306/204863.77
physics:staticFriction1259/204861.47
visual:assignment1570/204876.66
visual:metallic132/100513.13
visual:opacity1570/204876.66

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

accessory_eyeglasses_a01: Reference: front
Reference: front | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
accessory_eyeglasses_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
accessory_eyeglasses_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
accessory_eyeglasses_a01: Reference: side
Reference: side | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

box_cardboard_open_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)80.4% (1.60807/2)N/A70.59% (36/51)82.18% (0.821836/1)82.18% (0.821836/1)N/A44.95% (6444/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2930431.15384.2755840016418574818Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape82.180.821836/111100
Rigid parts82.180.821836/111100
JointsNot applicable0/0000
Materials44.956444/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
78.661611/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
86.0478.6620489.76.3912.84

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardTray82.18

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1611/204878.66
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1611/204878.66
visual:assignment1611/204878.66
visual:opacity1611/204878.66

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

box_cardboard_open_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)83.63% (0.836295/1)83.63% (0.836295/1)N/A34.05% (4881/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2920407.12352.8557454016108590648Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape83.630.836295/111100
Rigid parts83.630.836295/111100
JointsNot applicable0/0000
Materials34.054881/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
88.2879.4420489.76.1312.98

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardBox83.63

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1627/204879.44
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1627/204879.44
visual:assignment1627/204879.44
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

box_cardboard_open_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)77.87% (0.778707/1)77.87% (0.778707/1)N/A30.91% (4431/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3230463.45405.8171765617729735385Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape77.870.778707/111100
Rigid parts77.870.778707/111100
JointsNot applicable0/0000
Materials30.914431/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
84.6272.1220489.77.0914.29

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardTray77.87

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1477/204872.12
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1477/204872.12
visual:assignment1477/204872.12
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

bucket_utility_red_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)41.49% (0.829812/2)0.01% (0.000121476/1)76.47% (39/51)54.74% (0.547449/1)28.71% (0.574159/2)63.64% (7/11)31.4% (5136/16356)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4340805.12716.051649778315561681334Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape54.740.547449/111100
Rigid parts28.710.574159/222100
Joints63.647/111111100
Materials31.45136/16356163561635666.55

Appearance materials

Score (%)Earned/eligibleStatus
31.45644/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving joints0.010.000364428/33/3100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_handle_a01_01_joint_00/Bucket/Joints/Bail_Swing0.02316.54measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
48.5862.720486.388.3114.26

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_bucket_utility_a01_obj_00/Bucket/Body56.03
/RootNode/Geometry/sm_handle_a01_01_obj_00/Bucket/Bail1.39

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
127/11

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
axes0/11/1
relative_orientation1/11/1
limits0/11/1
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1284/204862.7
physics:density0/20480
physics:dynamicFriction1257/204861.38
physics:restitution27/20481.32
physics:staticFriction0/20480
visual:assignment1284/204862.7
visual:diffuseColor0/20200
visual:opacity1284/204862.7

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

bucket_utility_red_a01: Reference: front
Reference: front | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
bucket_utility_red_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
bucket_utility_red_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
bucket_utility_red_a01: Reference: side
Reference: side | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

bucket_utility_red_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)43.33% (0.866571/2)0.34% (0.00336069/1)70.59% (36/51)58.21% (0.58211/1)29.27% (0.585487/2)54.55% (6/11)32.31% (5285/16356)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3520532.75470.8378965220782810434Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape58.210.58211/111100
Rigid parts29.270.585487/222100
Joints54.556/111111100
Materials32.315285/16356163561635666.55

Appearance materials

Score (%)Earned/eligibleStatus
32.25660.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving joints0.340.0100821/33/3100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_handle_a01_01_joint_00/Bucket/Joints/BailHinge0.566.31measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
53.2764.1620486.386.8811.39

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_bucket_utility_a01_obj_00/Bucket/Body58.02
/RootNode/Geometry/sm_handle_a01_01_obj_00/Bucket/Bail0.53

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
126/11

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
axes0/11/1
relative_orientation0/11/1
limits0/11/1
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1314/204864.16
physics:density0/20480
physics:dynamicFriction1314/204864.16
physics:restitution29/20481.42
physics:staticFriction0/20480
visual:assignment1314/204864.16
visual:diffuseColor0/20200
visual:opacity1314/204864.16

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

bucket_utility_red_a01: Reference: front
Reference: front | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
bucket_utility_red_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
bucket_utility_red_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
bucket_utility_red_a01: Reference: side
Reference: side | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

chair_office_amf_black_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)76.44% (1.52878/2)0% (0/1)68.63% (35/51)74.46% (0.744639/1)21.7% (0.216991/1)N/A31.78% (5207/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3430703.39625.7189808527574925659Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape74.460.744639/111100
Rigid parts21.70.216991/111100
JointsNot applicable0/0000
Materials31.785207/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
78.471607/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
70.8578.47204812.2918.1539.56

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_chair_office_amf_a01_obj_00/Chair/SteelFrame21.7

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
020/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment193/20489.42
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution193/20489.42
physics:staticFriction0/20480
visual:assignment1607/204878.47
visual:diffuseColor1607/204878.47
visual:opacity1607/204878.47

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

chair_office_amf_black_a01: Reference: front
Reference: front | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
chair_office_amf_black_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
chair_office_amf_black_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
chair_office_amf_black_a01: Reference: side
Reference: side | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

chair_office_amf_black_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)43.66% (0.873218/2)N/A68.63% (35/51)59.83% (0.598322/1)59.83% (0.598322/1)N/A23.96% (3925/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4030633.2558.551060920244431085363Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape59.830.598322/111100
Rigid parts59.830.598322/111100
JointsNot applicable0/0000
Materials23.963925/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
31.86652.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
56.263.96204812.2924.1353.74

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_chair_office_amf_a01_obj_00/Chair59.83

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1310/204863.96
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1310/204863.96
visual:diffuseColor1305/204863.72
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

chair_office_amf_black_a01: Reference: front
Reference: front | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
chair_office_amf_black_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
chair_office_amf_black_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
chair_office_amf_black_a01: Reference: side
Reference: side | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

cleaning_cloth_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)97.57% (0.975744/1)97.57% (0.975744/1)N/A14.29% (2048/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3720634.25500.9687451721134895651Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape97.570.975744/111100
Rigid parts97.570.975744/111100
JointsNot applicable0/0000
Materials14.292048/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
95.2610020484.523.89

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/cleaningCloth_01_obj_00/Cloth97.57

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment2048/2048100
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

cleaning_cloth_a01: Reference: front
Reference: front | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
cleaning_cloth_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
cleaning_cloth_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
cleaning_cloth_a01: Reference: side
Reference: side | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

container_bottle_glass_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)80.72% (1.61437/2)N/A74.51% (38/51)81.71% (0.817125/1)81.71% (0.817125/1)N/A29.9% (4899/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3630562.03496.6689682921319918148Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape81.710.817125/111100
Rigid parts81.710.817125/111100
JointsNot applicable0/0000
Materials29.94899/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
79.741633/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
83.7979.7420484.513.587.77

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Vessel81.71

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1633/204879.74
visual:metallic1633/204879.74
visual:opacity1633/204879.74

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

container_bottle_glass_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)90.98% (1.81958/2)N/A74.51% (38/51)90.94% (0.909423/1)90.94% (0.909423/1)N/A68.26% (11184/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3220366.66320.6752012414220534344Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape90.940.909423/111100
Rigid parts90.940.909423/111100
JointsNot applicable0/0000
Materials68.2611184/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
91.021864/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
90.8791.0220484.512.825.2

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Bottle90.94

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1864/204891.02
physics:density0/20480
physics:dynamicFriction1864/204891.02
physics:restitution1864/204891.02
physics:staticFriction0/20480
visual:assignment1864/204891.02
visual:metallic1864/204891.02
visual:opacity1864/204891.02

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

container_bottle_glass_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A66.67% (34/51)81.06% (0.810559/1)81.06% (0.810559/1)N/A49.19% (8060/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2920383.45331.6752314214382537524Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape81.060.810559/111100
Rigid parts81.060.810559/111100
JointsNot applicable0/0000
Materials49.198060/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
83.5478.7120484.513.839

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Vessel81.06

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1612/204878.71
physics:density0/20480
physics:dynamicFriction1612/204878.71
physics:restitution1612/204878.71
physics:staticFriction1612/204878.71
visual:assignment1612/204878.71
visual:metallic0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

container_bottle_glass_a01 / gpt-6.1-sol / repetition 4

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone4completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)86.65% (1.73301/2)N/A74.51% (38/51)87.47% (0.874685/1)87.47% (0.874685/1)N/A64.38% (10548/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3130427.21364.4558386517011600876Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape87.470.874685/111100
Rigid parts87.470.874685/111100
JointsNot applicable0/0000
Materials64.3810548/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
85.841758/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
89.1685.8420484.513.237.86

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Bottle87.47

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1758/204885.84
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution1758/204885.84
physics:staticFriction1758/204885.84
visual:assignment1758/204885.84
visual:metallic1758/204885.84
visual:opacity1758/204885.84

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 4
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 4
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 4
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 4

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)88.94% (1.77876/2)N/A68.63% (35/51)83.03% (0.83032/1)83.03% (0.83032/1)N/A68.05% (9755/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3520585.38498.6968569820938706636Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape83.030.83032/111100
Rigid parts83.030.83032/111100
JointsNot applicable0/0000
Materials68.059755/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
95.261951/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
73.5895.2620486.885.0811.45

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Body83.03

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1951/204895.26
physics:density1951/204895.26
physics:dynamicFriction0/20480
physics:restitution1951/204895.26
physics:staticFriction0/20480
visual:assignment1951/204895.26
visual:opacity1951/204895.26

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)92.25% (0.922452/1)92.25% (0.922452/1)N/A13.35% (1914/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3530476.47420.9479247518052810527Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape92.250.922452/111100
Rigid parts92.250.922452/111100
JointsNot applicable0/0000
Materials13.351914/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
91.0693.4620486.883.778.01

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Body92.25

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1914/204893.46
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)94.44% (1.88877/2)0% (0/1)76.47% (39/51)93.91% (0.939092/1)50% (0.5/1)N/A65.85% (9440/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2820476.92398.7663111317682648795Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape93.910.939092/111100
Rigid parts500.5/111100
JointsNot applicable0/0000
Materials65.859440/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
94.971945/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
92.8794.9720486.883.217.52

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Shaft84.74

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
020/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1850/204890.33
physics:density0/20480
physics:dynamicFriction1850/204890.33
physics:restitution1850/204890.33
physics:staticFriction0/20480
visual:assignment1945/204894.97
visual:opacity1945/204894.97

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

food_beverage_coffeeCup_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)72.53% (1.45061/2)100% (1/1)74.51% (38/51)95.87% (0.95874/1)95.2% (1.90396/2)88.89% (8/9)31.53% (6458/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4730595.82538.511221647216701243317Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape95.870.95874/111100
Rigid parts95.21.90396/222100
Joints88.898/999100
Materials31.536458/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
54.871123.75/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints1002/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_food_beverage_coffeeCup_a01_lid_joint_00/CoffeeCup/LidSnapFit1000measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
95.995.8520482.681.142.12

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_beverage_coffeeCup_a01_body_obj_00/CoffeeCup/Body94.28
/RootNode/Geometry/sm_food_beverage_coffeeCup_a01_lid_obj_00/CoffeeCup/Lid96.12

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
118/9

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
relative_orientation1/11/1
joint_count1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1963/204895.85
visual:diffuseColor491/204823.97
visual:metallic1963/204895.85
visual:opacity1963/204895.85
visual:roughness78/20483.81

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

food_beverage_coffeeCup_a01: Reference: front
Reference: front | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
food_beverage_coffeeCup_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reference: side
Reference: side | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1
\ No newline at end of file +SimReadyBench results

SimReadyBench results

Formal fidelity measures SimReady Robotics-Prop requirements. Visual fidelity combines shape and appearance materials. Kinematic fidelity measures joint recovery and motion correspondence. Each score is reported independently.

19 of 100 reconstruction attempts completed.

Scores CSV | Detailed results JSON

Results by asset

AssetModelHarnessSkillsRepetitionStatusFormal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
accessory_eyeglasses_a01gpt-6.1-solpinone1completed100% (46/46)40.21% (0.804287/2)0% (0/2)72.55% (37/51)52.24% (0.5224/1)19.32% (0.772785/4)0% (0/29)13.91% (2134/15341)5030782.55685.581496445302581526703Not measuredNot measuredNot measured
accessory_eyeglasses_a01gpt-6.1-solpinone2completed100% (46/46)66.28% (1.32561/2)0% (0/2)64.71% (33/51)79.03% (0.790262/1)37.83% (1.51339/4)62.07% (18/29)56.49% (8666/15341)4030578.87501.9977861228121000673Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone1completed100% (46/46)80.4% (1.60807/2)N/A70.59% (36/51)82.18% (0.821836/1)82.18% (0.821836/1)N/A44.95% (6444/14336)2930431.15384.2755840016418574818Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)83.63% (0.836295/1)83.63% (0.836295/1)N/A34.05% (4881/14336)2920407.12352.8557454016108590648Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone3completed100% (46/46)0% (0/2)N/A74.51% (38/51)77.87% (0.778707/1)77.87% (0.778707/1)N/A30.91% (4431/14336)3230463.45405.8171765617729735385Not measuredNot measuredNot measured
box_cardboard_open_a01gpt-6.1-solpinone4completed100% (46/46)76.59% (1.53173/2)N/A74.51% (38/51)77.8% (0.778012/1)77.8% (0.778012/1)N/A43.08% (6176/14336)4130576.55510.911062333218151084148Not measuredNot measuredNot measured
bucket_utility_red_a01gpt-6.1-solpinone1completed100% (46/46)41.49% (0.829812/2)0.01% (0.000121476/1)76.47% (39/51)54.74% (0.547449/1)28.71% (0.574159/2)63.64% (7/11)31.4% (5136/16356)4340805.12716.051649778315561681334Not measuredNot measuredNot measured
bucket_utility_red_a01gpt-6.1-solpinone2completed100% (46/46)43.33% (0.866571/2)0.34% (0.00336069/1)70.59% (36/51)58.21% (0.58211/1)29.27% (0.585487/2)54.55% (6/11)32.31% (5285/16356)3520532.75470.8378965220782810434Not measuredNot measuredNot measured
chair_office_amf_black_a01gpt-6.1-solpinone1completed100% (46/46)76.44% (1.52878/2)0% (0/1)68.63% (35/51)74.46% (0.744639/1)21.7% (0.216991/1)N/A31.78% (5207/16384)3430703.39625.7189808527574925659Not measuredNot measuredNot measured
chair_office_amf_black_a01gpt-6.1-solpinone2completed100% (46/46)43.66% (0.873218/2)N/A68.63% (35/51)59.83% (0.598322/1)59.83% (0.598322/1)N/A23.96% (3925/16384)4030633.2558.551060920244431085363Not measuredNot measuredNot measured
cleaning_cloth_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)97.57% (0.975744/1)97.57% (0.975744/1)N/A14.29% (2048/14336)3720634.25500.9687451721134895651Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone1completed100% (46/46)80.72% (1.61437/2)N/A74.51% (38/51)81.71% (0.817125/1)81.71% (0.817125/1)N/A29.9% (4899/16384)3630562.03496.6689682921319918148Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone2completed100% (46/46)90.98% (1.81958/2)N/A74.51% (38/51)90.94% (0.909423/1)90.94% (0.909423/1)N/A68.26% (11184/16384)3220366.66320.6752012414220534344Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone3completed100% (46/46)0% (0/2)N/A66.67% (34/51)81.06% (0.810559/1)81.06% (0.810559/1)N/A49.19% (8060/16384)2920383.45331.6752314214382537524Not measuredNot measuredNot measured
container_bottle_glass_a01gpt-6.1-solpinone4completed100% (46/46)86.65% (1.73301/2)N/A74.51% (38/51)87.47% (0.874685/1)87.47% (0.874685/1)N/A64.38% (10548/16384)3130427.21364.4558386517011600876Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone1completed100% (46/46)88.94% (1.77876/2)N/A68.63% (35/51)83.03% (0.83032/1)83.03% (0.83032/1)N/A68.05% (9755/14336)3520585.38498.6968569820938706636Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone2completed100% (46/46)0% (0/2)N/A74.51% (38/51)92.25% (0.922452/1)92.25% (0.922452/1)N/A13.35% (1914/14336)3530476.47420.9479247518052810527Not measuredNot measuredNot measured
engineComponent_camshaft_a01gpt-6.1-solpinone3completed100% (46/46)94.44% (1.88877/2)0% (0/1)76.47% (39/51)93.91% (0.939092/1)50% (0.5/1)N/A65.85% (9440/14336)2820476.92398.7663111317682648795Not measuredNot measuredNot measured
food_beverage_coffeeCup_a01gpt-6.1-solpinone1completed100% (46/46)72.53% (1.45061/2)100% (1/1)74.51% (38/51)95.87% (0.95874/1)95.2% (1.90396/2)88.89% (8/9)31.53% (6458/20480)4730595.82538.511221647216701243317Not measuredNot measuredNot measured

accessory_eyeglasses_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)40.21% (0.804287/2)0% (0/2)72.55% (37/51)52.24% (0.5224/1)19.32% (0.772785/4)0% (0/29)13.91% (2134/15341)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
5030782.55685.581496445302581526703Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape52.240.5224/111100
Rigid parts19.320.772785/444100
Joints00/292929100
Materials13.912134/15341153411534162.42

Appearance materials

Score (%)Earned/eligibleStatus
30.96634/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/11/1100
Moving joints00/44/4100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_arm_02_joint_00Not measured0Not measuredmissing_joint
/RootNode/Joints/joint_arm_01_joint_00Not measured0Not measuredmissing_joint
/RootNode/Joints/joint_glass_01_joint_00Not measured0Not measuredmissing_joint

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
55.9149.0220483.349.1922.17

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/arm_01_obj_00/Sunglasses/RightTemple0
/RootNode/Geometry/arm_02_obj_00/Sunglasses/LeftTemple0
/RootNode/Geometry/base_01_obj_00Not measured0
/RootNode/Geometry/glass_01_obj_00/Sunglasses/Front77.28

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
320/29

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled3/44/4
body_kinematic3/44/4

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity0/33/3
joint_enabled0/33/3
body0_enabled0/33/3
body0_kinematic0/33/3
body1_enabled0/33/3
body1_kinematic0/33/3
anchors0/33/3
axes0/22/2
relative_orientation0/33/3
limits0/22/2
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1004/204849.02
visual:metallic126/100512.54
visual:opacity1004/204849.02

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

accessory_eyeglasses_a01: Reference: front
Reference: front | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
accessory_eyeglasses_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
accessory_eyeglasses_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
accessory_eyeglasses_a01: Reference: side
Reference: side | pi | none | repetition 1
accessory_eyeglasses_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

accessory_eyeglasses_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)66.28% (1.32561/2)0% (0/2)64.71% (33/51)79.03% (0.790262/1)37.83% (1.51339/4)62.07% (18/29)56.49% (8666/15341)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4030578.87501.9977861228121000673Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape79.030.790262/111100
Rigid parts37.831.51339/444100
Joints62.0718/292929100
Materials56.498666/15341153411534162.42

Appearance materials

Score (%)Earned/eligibleStatus
55.591138.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/11/1100
Moving joints7.960.318493/44/4100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_arm_02_joint_00/Sunglasses/RightFoldingHinge7.749.06measured_motion
/RootNode/Joints/joint_arm_01_joint_00/Sunglasses/LeftFoldingHinge8.188.77measured_motion
/RootNode/Joints/joint_glass_01_joint_00Not measured0Not measuredmissing_joint

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
81.5476.6620483.343.457.18

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/arm_01_obj_00/Sunglasses/LeftTemple55.43
/RootNode/Geometry/arm_02_obj_00/Sunglasses/RightTemple52.82
/RootNode/Geometry/base_01_obj_00/Sunglasses/FrontAssembly43.09
/RootNode/Geometry/glass_01_obj_00Not measured0

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
3218/29

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled3/44/4
body_kinematic3/44/4

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity2/33/3
joint_enabled2/33/3
body0_enabled2/33/3
body0_kinematic2/33/3
body1_enabled2/33/3
body1_kinematic2/33/3
anchors0/33/3
axes2/22/2
relative_orientation2/33/3
limits2/22/2
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1570/204876.66
physics:density0/20480
physics:dynamicFriction1259/204861.47
physics:restitution1306/204863.77
physics:staticFriction1259/204861.47
visual:assignment1570/204876.66
visual:metallic132/100513.13
visual:opacity1570/204876.66

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

accessory_eyeglasses_a01: Reference: front
Reference: front | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
accessory_eyeglasses_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
accessory_eyeglasses_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
accessory_eyeglasses_a01: Reference: side
Reference: side | pi | none | repetition 2
accessory_eyeglasses_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

box_cardboard_open_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)80.4% (1.60807/2)N/A70.59% (36/51)82.18% (0.821836/1)82.18% (0.821836/1)N/A44.95% (6444/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2930431.15384.2755840016418574818Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape82.180.821836/111100
Rigid parts82.180.821836/111100
JointsNot applicable0/0000
Materials44.956444/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
78.661611/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
86.0478.6620489.76.3912.84

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardTray82.18

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1611/204878.66
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1611/204878.66
visual:assignment1611/204878.66
visual:opacity1611/204878.66

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 1
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

box_cardboard_open_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)83.63% (0.836295/1)83.63% (0.836295/1)N/A34.05% (4881/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2920407.12352.8557454016108590648Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape83.630.836295/111100
Rigid parts83.630.836295/111100
JointsNot applicable0/0000
Materials34.054881/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
88.2879.4420489.76.1312.98

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardBox83.63

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1627/204879.44
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1627/204879.44
visual:assignment1627/204879.44
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 2
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

box_cardboard_open_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)77.87% (0.778707/1)77.87% (0.778707/1)N/A30.91% (4431/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3230463.45405.8171765617729735385Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape77.870.778707/111100
Rigid parts77.870.778707/111100
JointsNot applicable0/0000
Materials30.914431/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
84.6272.1220489.77.0914.29

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardTray77.87

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1477/204872.12
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1477/204872.12
visual:assignment1477/204872.12
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 3
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

box_cardboard_open_a01 / gpt-6.1-sol / repetition 4

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone4completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)76.59% (1.53173/2)N/A74.51% (38/51)77.8% (0.778012/1)77.8% (0.778012/1)N/A43.08% (6176/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4130576.55510.911062333218151084148Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape77.80.778012/111100
Rigid parts77.80.778012/111100
JointsNot applicable0/0000
Materials43.086176/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
75.391544/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
80.3775.3920489.77.0813.23

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_box_a01_obj_00/CardboardTray77.8

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1544/204875.39
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction1544/204875.39
visual:assignment1544/204875.39
visual:opacity1544/204875.39

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

box_cardboard_open_a01: Reference: front
Reference: front | pi | none | repetition 4
box_cardboard_open_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 4
box_cardboard_open_a01: Reference: isometric
Reference: isometric | pi | none | repetition 4
box_cardboard_open_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 4
box_cardboard_open_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 4
box_cardboard_open_a01: Reference: side
Reference: side | pi | none | repetition 4
box_cardboard_open_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 4

bucket_utility_red_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)41.49% (0.829812/2)0.01% (0.000121476/1)76.47% (39/51)54.74% (0.547449/1)28.71% (0.574159/2)63.64% (7/11)31.4% (5136/16356)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4340805.12716.051649778315561681334Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape54.740.547449/111100
Rigid parts28.710.574159/222100
Joints63.647/111111100
Materials31.45136/16356163561635666.55

Appearance materials

Score (%)Earned/eligibleStatus
31.45644/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving joints0.010.000364428/33/3100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_handle_a01_01_joint_00/Bucket/Joints/Bail_Swing0.02316.54measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
48.5862.720486.388.3114.26

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_bucket_utility_a01_obj_00/Bucket/Body56.03
/RootNode/Geometry/sm_handle_a01_01_obj_00/Bucket/Bail1.39

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
127/11

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
axes0/11/1
relative_orientation1/11/1
limits0/11/1
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1284/204862.7
physics:density0/20480
physics:dynamicFriction1257/204861.38
physics:restitution27/20481.32
physics:staticFriction0/20480
visual:assignment1284/204862.7
visual:diffuseColor0/20200
visual:opacity1284/204862.7

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

bucket_utility_red_a01: Reference: front
Reference: front | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
bucket_utility_red_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
bucket_utility_red_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
bucket_utility_red_a01: Reference: side
Reference: side | pi | none | repetition 1
bucket_utility_red_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

bucket_utility_red_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)43.33% (0.866571/2)0.34% (0.00336069/1)70.59% (36/51)58.21% (0.58211/1)29.27% (0.585487/2)54.55% (6/11)32.31% (5285/16356)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3520532.75470.8378965220782810434Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape58.210.58211/111100
Rigid parts29.270.585487/222100
Joints54.556/111111100
Materials32.315285/16356163561635666.55

Appearance materials

Score (%)Earned/eligibleStatus
32.25660.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving joints0.340.0100821/33/3100
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_handle_a01_01_joint_00/Bucket/Joints/BailHinge0.566.31measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
53.2764.1620486.386.8811.39

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_bucket_utility_a01_obj_00/Bucket/Body58.02
/RootNode/Geometry/sm_handle_a01_01_obj_00/Bucket/Bail0.53

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
126/11

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
axes0/11/1
relative_orientation0/11/1
limits0/11/1
joint_count0/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1314/204864.16
physics:density0/20480
physics:dynamicFriction1314/204864.16
physics:restitution29/20481.42
physics:staticFriction0/20480
visual:assignment1314/204864.16
visual:diffuseColor0/20200
visual:opacity1314/204864.16

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

bucket_utility_red_a01: Reference: front
Reference: front | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
bucket_utility_red_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
bucket_utility_red_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
bucket_utility_red_a01: Reference: side
Reference: side | pi | none | repetition 2
bucket_utility_red_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

chair_office_amf_black_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)76.44% (1.52878/2)0% (0/1)68.63% (35/51)74.46% (0.744639/1)21.7% (0.216991/1)N/A31.78% (5207/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3430703.39625.7189808527574925659Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape74.460.744639/111100
Rigid parts21.70.216991/111100
JointsNot applicable0/0000
Materials31.785207/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
78.471607/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
70.8578.47204812.2918.1539.56

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_chair_office_amf_a01_obj_00/Chair/SteelFrame21.7

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
020/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment193/20489.42
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution193/20489.42
physics:staticFriction0/20480
visual:assignment1607/204878.47
visual:diffuseColor1607/204878.47
visual:opacity1607/204878.47

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

chair_office_amf_black_a01: Reference: front
Reference: front | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
chair_office_amf_black_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
chair_office_amf_black_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
chair_office_amf_black_a01: Reference: side
Reference: side | pi | none | repetition 1
chair_office_amf_black_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

chair_office_amf_black_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)43.66% (0.873218/2)N/A68.63% (35/51)59.83% (0.598322/1)59.83% (0.598322/1)N/A23.96% (3925/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4030633.2558.551060920244431085363Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape59.830.598322/111100
Rigid parts59.830.598322/111100
JointsNot applicable0/0000
Materials23.963925/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
31.86652.5/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
56.263.96204812.2924.1353.74

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_chair_office_amf_a01_obj_00/Chair59.83

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1310/204863.96
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1310/204863.96
visual:diffuseColor1305/204863.72
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

chair_office_amf_black_a01: Reference: front
Reference: front | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
chair_office_amf_black_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
chair_office_amf_black_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
chair_office_amf_black_a01: Reference: side
Reference: side | pi | none | repetition 2
chair_office_amf_black_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

cleaning_cloth_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)97.57% (0.975744/1)97.57% (0.975744/1)N/A14.29% (2048/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3720634.25500.9687451721134895651Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape97.570.975744/111100
Rigid parts97.570.975744/111100
JointsNot applicable0/0000
Materials14.292048/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
95.2610020484.523.89

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/cleaningCloth_01_obj_00/Cloth97.57

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment2048/2048100
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

cleaning_cloth_a01: Reference: front
Reference: front | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
cleaning_cloth_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
cleaning_cloth_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
cleaning_cloth_a01: Reference: side
Reference: side | pi | none | repetition 2
cleaning_cloth_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

container_bottle_glass_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)80.72% (1.61437/2)N/A74.51% (38/51)81.71% (0.817125/1)81.71% (0.817125/1)N/A29.9% (4899/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3630562.03496.6689682921319918148Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape81.710.817125/111100
Rigid parts81.710.817125/111100
JointsNot applicable0/0000
Materials29.94899/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
79.741633/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
83.7979.7420484.513.587.77

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Vessel81.71

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1633/204879.74
visual:metallic1633/204879.74
visual:opacity1633/204879.74

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 1
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

container_bottle_glass_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)90.98% (1.81958/2)N/A74.51% (38/51)90.94% (0.909423/1)90.94% (0.909423/1)N/A68.26% (11184/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3220366.66320.6752012414220534344Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape90.940.909423/111100
Rigid parts90.940.909423/111100
JointsNot applicable0/0000
Materials68.2611184/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
91.021864/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
90.8791.0220484.512.825.2

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Bottle90.94

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1864/204891.02
physics:density0/20480
physics:dynamicFriction1864/204891.02
physics:restitution1864/204891.02
physics:staticFriction0/20480
visual:assignment1864/204891.02
visual:metallic1864/204891.02
visual:opacity1864/204891.02

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 2
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

container_bottle_glass_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A66.67% (34/51)81.06% (0.810559/1)81.06% (0.810559/1)N/A49.19% (8060/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2920383.45331.6752314214382537524Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape81.060.810559/111100
Rigid parts81.060.810559/111100
JointsNot applicable0/0000
Materials49.198060/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
83.5478.7120484.513.839

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Vessel81.06

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1612/204878.71
physics:density0/20480
physics:dynamicFriction1612/204878.71
physics:restitution1612/204878.71
physics:staticFriction1612/204878.71
visual:assignment1612/204878.71
visual:metallic0/20480
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 3
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

container_bottle_glass_a01 / gpt-6.1-sol / repetition 4

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone4completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)86.65% (1.73301/2)N/A74.51% (38/51)87.47% (0.874685/1)87.47% (0.874685/1)N/A64.38% (10548/16384)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3130427.21364.4558386517011600876Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape87.470.874685/111100
Rigid parts87.470.874685/111100
JointsNot applicable0/0000
Materials64.3810548/16384163841638466.67

Appearance materials

Score (%)Earned/eligibleStatus
85.841758/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
89.1685.8420484.513.237.86

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/bottle_01_obj_00/Bottle87.47

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1758/204885.84
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution1758/204885.84
physics:staticFriction1758/204885.84
visual:assignment1758/204885.84
visual:metallic1758/204885.84
visual:opacity1758/204885.84

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

container_bottle_glass_a01: Reference: front
Reference: front | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 4
container_bottle_glass_a01: Reference: isometric
Reference: isometric | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 4
container_bottle_glass_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 4
container_bottle_glass_a01: Reference: side
Reference: side | pi | none | repetition 4
container_bottle_glass_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 4

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)88.94% (1.77876/2)N/A68.63% (35/51)83.03% (0.83032/1)83.03% (0.83032/1)N/A68.05% (9755/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3520585.38498.6968569820938706636Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape83.030.83032/111100
Rigid parts83.030.83032/111100
JointsNot applicable0/0000
Materials68.059755/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
95.261951/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
73.5895.2620486.885.0811.45

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Body83.03

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1951/204895.26
physics:density1951/204895.26
physics:dynamicFriction0/20480
physics:restitution1951/204895.26
physics:staticFriction0/20480
visual:assignment1951/204895.26
visual:opacity1951/204895.26

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 1
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 2

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone2completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)0% (0/2)N/A74.51% (38/51)92.25% (0.922452/1)92.25% (0.922452/1)N/A13.35% (1914/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
3530476.47420.9479247518052810527Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape92.250.922452/111100
Rigid parts92.250.922452/111100
JointsNot applicable0/0000
Materials13.351914/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
00/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraintsNot measured0/00/00
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
91.0693.4620486.883.778.01

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Body92.25

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
000/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1914/204893.46
visual:opacity0/20480

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 2
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 2
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 2
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 2
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 2

engineComponent_camshaft_a01 / gpt-6.1-sol / repetition 3

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone3completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)94.44% (1.88877/2)0% (0/1)76.47% (39/51)93.91% (0.939092/1)50% (0.5/1)N/A65.85% (9440/14336)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
2820476.92398.7663111317682648795Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape93.910.939092/111100
Rigid parts500.5/111100
JointsNot applicable0/0000
Materials65.859440/14336143361433658.33

Appearance materials

Score (%)Earned/eligibleStatus
94.971945/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints00/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
92.8794.9720486.883.217.52

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/camshaft_01_obj_00/Camshaft/Shaft84.74

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
020/0

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count0/11/1
joint_inventory_count0/11/1
body_enabled1/11/1
body_kinematic1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment1850/204890.33
physics:density0/20480
physics:dynamicFriction1850/204890.33
physics:restitution1850/204890.33
physics:staticFriction0/20480
visual:assignment1945/204894.97
visual:opacity1945/204894.97

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

engineComponent_camshaft_a01: Reference: front
Reference: front | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 3
engineComponent_camshaft_a01: Reference: isometric
Reference: isometric | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 3
engineComponent_camshaft_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 3
engineComponent_camshaft_a01: Reference: side
Reference: side | pi | none | repetition 3
engineComponent_camshaft_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 3

food_beverage_coffeeCup_a01 / gpt-6.1-sol / repetition 1

ModelHarnessSkillsRepetitionStatus
gpt-6.1-solpinone1completed
Formal fidelity (%)Visual fidelity (%)Kinematic fidelity (%)SimReady Robotics-Prop optionalShape (%)Rigid parts (%)Joints (%)Materials (%)
100% (46/46)72.53% (1.45061/2)100% (1/1)74.51% (38/51)95.87% (0.95874/1)95.2% (1.90396/2)88.89% (8/9)31.53% (6458/20480)

Requests, timing and costs

Model requestsValidation callsRequest errorsElapsed time (s)Model request time (s)Input tokensOutput tokensTotal tokensInference cost (USD)Compute cost (USD)Total cost (USD)
4730595.82538.511221647216701243317Not measuredNot measuredNot measured

46 of 46 mandatory requirements passed.

Direct USD reconstruction fidelity

ComponentFidelity (%)CreditMeasuredEligibleReference coverage (%)
Shape95.870.95874/111100
Rigid parts95.21.90396/222100
Joints88.898/999100
Materials31.536458/20480204802048083.33

Appearance materials

Score (%)Earned/eligibleStatus
54.871123.75/2048measured

Kinematic correspondence

FactorScore (%)Earned/eligibleMeasured/eligibleCoverage (%)
Fixed constraints1002/22/2100
Moving jointsNot measured0/00/00
Reference jointCandidate jointScore (%)Motion RMS (mm)Status
/RootNode/Joints/joint_sm_food_beverage_coffeeCup_a01_lid_joint_00/CoffeeCup/LidSnapFit1000measured_motion

Surface correspondence

Precision (%)Recall (%)Samples per directionDistance band (mm)RMS distance (mm)95th-percentile distance (mm)
95.995.8520482.681.142.12

Rigid-part correspondence

Reference bodyCandidate bodySurface correspondence (%)
/RootNode/Geometry/sm_food_beverage_coffeeCup_a01_body_obj_00/CoffeeCup/Body94.28
/RootNode/Geometry/sm_food_beverage_coffeeCup_a01_lid_obj_00/CoffeeCup/Lid96.12

Joint correspondence

Reference jointsCandidate jointsPassed/eligible checks
118/9

Rigid-structure checks

FeaturePassed/eligibleMeasured/eligible
body_count1/11/1
joint_inventory_count1/11/1
body_enabled2/22/2
body_kinematic2/22/2

Joint checks

FeaturePassed/eligibleMeasured/eligible
existence_type_connectivity1/11/1
joint_enabled1/11/1
body0_enabled1/11/1
body0_kinematic1/11/1
body1_enabled1/11/1
body1_kinematic1/11/1
anchors0/11/1
relative_orientation1/11/1
joint_count1/11/1

Material correspondence

PropertyCredit/eligibleCorrespondence (%)
physics:assignment0/20480
physics:density0/20480
physics:dynamicFriction0/20480
physics:restitution0/20480
physics:staticFriction0/20480
visual:assignment1963/204895.85
visual:diffuseColor491/204823.97
visual:metallic1963/204895.85
visual:opacity1963/204895.85
visual:roughness78/20483.81

Generated USD | Asset package manifest | NVIDIA validation findings | Harbor trajectory 1

Matched captures

food_beverage_coffeeCup_a01: Reference: front
Reference: front | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: front
Reconstruction: front | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reference: isometric
Reference: isometric | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: isometric
Reconstruction: isometric | pi | none | repetition 1
food_beverage_coffeeCup_a01: matched reference: reconstruction contact sheet
matched reference: reconstruction contact sheet | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reference: side
Reference: side | pi | none | repetition 1
food_beverage_coffeeCup_a01: Reconstruction: side
Reconstruction: side | pi | none | repetition 1
\ No newline at end of file diff --git a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/results.json b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/results.json index 5b0b6ce4071693620cbca68f02919e89bf7265de..6cb92d491e6f7dfa9bf5cc038c486f0c747dfb3b 100644 --- a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/results.json +++ b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/results.json @@ -1,7 +1,7 @@ { "schema": "simready-bench-portable-report-v1", "planned_conditions": 100, - "completed_conditions": 18, + "completed_conditions": 19, "partial": true, "settings": { "reference_assets": [ @@ -11453,6 +11453,2145 @@ }, "reasoning_effort": "high" }, + { + "condition_id": "condition-933256febfe4985da39451ac767cc2cf7bd34b525552b1245cf792250a8f2393", + "asset_id": "box_cardboard_open_a01", + "requested_model": "gpt-6.1-sol", + "harness_id": "pi", + "skill_set_id": "none", + "repetition": 3, + "status": "completed", + "formal_fidelity_percent": 100.0, + 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"bytes": 27120 + } + ], + "traces": [ + { + "kind": "agent_trajectory", + "path": "box_cardboard_open_a01/reconstruction-4/harbor-trajectory-4.json", + "sha256": "9da7221bbdaadec33801ef49aa246760fe86b5cbd54c6c9fa8ce426f250704e5", + "bytes": 165235 + } + ], + "nvidia_validator_report_file": { + "path": "evidence/box_cardboard_open_a01/reconstruction-4/nvidia-validator.json", + "complete": true, + "findings_truncated": false, + "sha256": "5b3f461187e3411dd07091f5448bfd23c74879d6654709f5905d45aa84720a42", + "bytes": 185264 + }, + "reasoning_effort": "high" + }, { "condition_id": "condition-985faa7e2b84f118dff65c810895a19c5c3c0cdb79fac1a8989559820f81669a", "asset_id": "bucket_utility_red_a01", diff --git a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.csv b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.csv index 1a285113e82857a1b9a9304b1a2557c255a0c434..1ed964cac9376ac40482f47a58e6ac74835c7a6c 100644 --- a/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.csv +++ b/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.csv @@ -4,6 +4,7 @@ condition-e6cdba5720a53864bb1be8577a689196092e0262f91241ec77ad601c5284cbb1,acces condition-b5d6b4fe33831596df5485708a01e30ad32e21cd4de8f9ff5594d4e5d20a2efc,box_cardboard_open_a01,gpt-6.1-sol,pi,none,1,completed,100.0,80.40357649810949,,100.0,46,46,0,0,100.0,100.0,5,70.58823529411765,36,15,0,51,51,1.0,70.58823529411765,70.58823529411765,82.18359722428106,82.18359722428106,,44.949776785714285,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,1.6080715299621897,2,2,1.0,80.40357649810949,80.40357649810949,not_applicable,0,0,0,0,,,78.662109375,measured,1611.0,2048,2048,1.0,78.662109375,78.662109375,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.8218359722428106,1,1,measured,0.8218359722428106,1,1,measured,0,0,0,not_applicable,6444,14336,14336,measured,0.8603515625,0.78662109375,2048,82.18359722428106,100.0,4,4,0,0,29,3,0,431.15402541682124,384.27109763398767,558400,16418,574818,,, condition-bf7d48bdde34ac9b89923e9ca2bff27f5e38460080eb7aa29147643bc5986f58,box_cardboard_open_a01,gpt-6.1-sol,pi,none,2,completed,100.0,0.0,,100.0,46,46,0,0,100.0,100.0,5,74.50980392156863,38,13,0,51,51,1.0,74.50980392156863,74.50980392156863,83.62945778748181,83.62945778748181,,34.047154017857146,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,0.0,2,2,1.0,0.0,0.0,not_applicable,0,0,0,0,,,0.0,measured,0.0,2048,2048,1.0,0.0,0.0,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.8362945778748181,1,1,measured,0.8362945778748181,1,1,measured,0,0,0,not_applicable,4881,14336,14336,measured,0.8828125,0.79443359375,2048,83.62945778748181,100.0,4,4,0,0,29,2,0,407.11550161987543,352.8515537455678,574540,16108,590648,,, condition-6ac444a05f1b7a179c749f4125336b2dd0141bfc0e4438c293ca405c465b2b0c,box_cardboard_open_a01,gpt-6.1-sol,pi,none,3,completed,100.0,0.0,,100.0,46,46,0,0,100.0,100.0,5,74.50980392156863,38,13,0,51,51,1.0,74.50980392156863,74.50980392156863,77.87069825739876,77.87069825739876,,30.908203125,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,0.0,2,2,1.0,0.0,0.0,not_applicable,0,0,0,0,,,0.0,measured,0.0,2048,2048,1.0,0.0,0.0,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.7787069825739876,1,1,measured,0.7787069825739876,1,1,measured,0,0,0,not_applicable,4431,14336,14336,measured,0.84619140625,0.72119140625,2048,77.87069825739876,100.0,4,4,0,0,32,3,0,463.4529142305255,405.8142865970731,717656,17729,735385,,, +condition-933256febfe4985da39451ac767cc2cf7bd34b525552b1245cf792250a8f2393,box_cardboard_open_a01,gpt-6.1-sol,pi,none,4,completed,100.0,76.586445808707,,100.0,46,46,0,0,100.0,100.0,5,74.50980392156863,38,13,0,51,51,1.0,74.50980392156863,74.50980392156863,77.80123432601881,77.80123432601881,,43.080357142857146,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,1.5317289161741399,2,2,1.0,76.586445808707,76.586445808707,not_applicable,0,0,0,0,,,75.390625,measured,1544.0,2048,2048,1.0,75.390625,75.390625,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.7780123432601882,1,1,measured,0.7780123432601882,1,1,measured,0,0,0,not_applicable,6176,14336,14336,measured,0.8037109375,0.75390625,2048,77.80123432601881,100.0,4,4,0,0,41,3,0,576.5532771758735,510.90728732571006,1062333,21815,1084148,,, condition-985faa7e2b84f118dff65c810895a19c5c3c0cdb79fac1a8989559820f81669a,bucket_utility_red_a01,gpt-6.1-sol,pi,none,1,completed,100.0,41.490614674649336,0.012147609470544126,100.0,46,46,0,0,100.0,100.0,5,76.47058823529412,39,12,0,51,51,1.0,76.47058823529412,76.47058823529412,54.7449196467749,28.707958484648398,63.63636363636363,31.401320616287602,1.0,1.0,1.0,0.66552734375,complete,measured,46,46,46,1.0,100.0,100.0,measured,0.8298122934929867,2,2,1.0,41.490614674649336,41.490614674649336,measured,0.00012147609470544127,1,1,1.0,0.012147609470544126,0.012147609470544126,31.4453125,measured,644.0,2048,2048,1.0,31.4453125,31.4453125,1,2,1,0,1,0.012147609470544126,measured,0.0003644282841163238,3,3,1.0,0.012147609470544126,0.012147609470544126,,not_applicable,0,0,0,0,,,0.547449196467749,1,1,measured,0.574159169692968,2,2,measured,7,11,11,measured,5136,16356,16356,measured,0.48583984375,0.626953125,2048,28.707958484648398,66.66666666666667,4,6,1,2,43,4,0,805.1181949768215,716.0515734348446,1649778,31556,1681334,,, condition-8315cfb49c5be1105af848c7511679c4614eebfd99671e97e7c13fc810fab3df,bucket_utility_red_a01,gpt-6.1-sol,pi,none,2,completed,100.0,43.32853189644649,0.3360690889494051,100.0,46,46,0,0,100.0,100.0,5,70.58823529411765,36,15,0,51,51,1.0,70.58823529411765,70.58823529411765,58.21100246881497,29.27434901254163,54.54545454545455,32.31230129616043,1.0,1.0,1.0,0.66552734375,complete,measured,46,46,46,1.0,100.0,100.0,measured,0.8665706379289299,2,2,1.0,43.32853189644649,43.32853189644649,measured,0.0033606908894940513,1,1,1.0,0.3360690889494051,0.3360690889494051,32.2509765625,measured,660.5,2048,2048,1.0,32.2509765625,32.2509765625,1,2,1,0,1,0.3360690889494051,measured,0.010082072668482154,3,3,1.0,0.3360690889494051,0.3360690889494051,,not_applicable,0,0,0,0,,,0.5821100246881497,1,1,measured,0.5854869802508326,2,2,measured,6,11,11,measured,5285,16356,16356,measured,0.53271484375,0.6416015625,2048,29.27434901254163,66.66666666666667,4,6,1,2,35,2,0,532.7502911277115,470.8266056403518,789652,20782,810434,,, condition-9f5e931b15962e1ecf175941db5dfd659c99c414a415c63b59e61b01d689903b,chair_office_amf_black_a01,gpt-6.1-sol,pi,none,1,completed,100.0,76.43915684635458,0.0,100.0,46,46,0,0,100.0,100.0,5,68.62745098039215,35,16,0,51,51,1.0,68.62745098039215,68.62745098039215,74.46391253474494,21.699124396135268,,31.781005859375,1.0,1.0,0,0.6666666666666666,complete,measured,46,46,46,1.0,100.0,100.0,measured,1.5287831369270917,2,2,1.0,76.43915684635458,76.43915684635458,measured,0.0,1,1,1.0,0.0,0.0,78.466796875,measured,1607.0,2048,2048,1.0,78.466796875,78.466796875,0,2,0,0,2,,not_applicable,0,0,0,0,,,0.0,measured,0,2,2,1.0,0.0,0.0,0.7446391253474494,1,1,measured,0.2169912439613527,1,1,measured,0,0,0,not_applicable,5207,16384,16384,measured,0.70849609375,0.78466796875,2048,21.699124396135268,50.0,2,4,0,2,34,3,0,703.3925981521606,625.7106681037694,898085,27574,925659,,, diff --git a/viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/box_cardboard_open_a01.csv b/viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/box_cardboard_open_a01.csv index ccaf017483c2b6fa482f90822d23f511bc168b13..79c80d91f3d5c6a96a69ed074cd8f960465ed863 100644 --- a/viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/box_cardboard_open_a01.csv +++ b/viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/box_cardboard_open_a01.csv @@ -2,3 +2,4 @@ condition_id,asset_id,requested_model,harness_id,skill_set_id,repetition,status, condition-b5d6b4fe33831596df5485708a01e30ad32e21cd4de8f9ff5594d4e5d20a2efc,box_cardboard_open_a01,gpt-6.1-sol,pi,none,1,completed,100.0,80.40357649810949,,100.0,46,46,0,0,100.0,100.0,5,70.58823529411765,36,15,0,51,51,1.0,70.58823529411765,70.58823529411765,82.18359722428106,82.18359722428106,,44.949776785714285,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,1.6080715299621897,2,2,1.0,80.40357649810949,80.40357649810949,not_applicable,0,0,0,0,,,78.662109375,measured,1611.0,2048,2048,1.0,78.662109375,78.662109375,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.8218359722428106,1,1,measured,0.8218359722428106,1,1,measured,0,0,0,not_applicable,6444,14336,14336,measured,0.8603515625,0.78662109375,2048,82.18359722428106,100.0,4,4,0,0,29,3,0,431.15402541682124,384.27109763398767,558400,16418,574818,,, condition-bf7d48bdde34ac9b89923e9ca2bff27f5e38460080eb7aa29147643bc5986f58,box_cardboard_open_a01,gpt-6.1-sol,pi,none,2,completed,100.0,0.0,,100.0,46,46,0,0,100.0,100.0,5,74.50980392156863,38,13,0,51,51,1.0,74.50980392156863,74.50980392156863,83.62945778748181,83.62945778748181,,34.047154017857146,1.0,1.0,0,0.5833333333333334,complete,measured,46,46,46,1.0,100.0,100.0,measured,0.0,2,2,1.0,0.0,0.0,not_applicable,0,0,0,0,,,0.0,measured,0.0,2048,2048,1.0,0.0,0.0,0,0,0,0,0,,not_applicable,0,0,0,0,,,,not_applicable,0,0,0,0,,,0.8362945778748181,1,1,measured,0.8362945778748181,1,1,measured,0,0,0,not_applicable,4881,14336,14336,measured,0.8828125,0.79443359375,2048,83.62945778748181,100.0,4,4,0,0,29,2,0,407.11550161987543,352.8515537455678,574540,16108,590648,,, 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