[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6PQTH7DA71HG6EM96RZENE2":3,"skill-same:01M6PQTH7DA71HG6EM96RZENE2":651},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":63,"commitSha":64,"skillDirectory":65,"forksCount":14,"repositoryHtmlUrl":66,"repositoryHomepageUrl":6,"ownerHtmlUrl":67,"ownerBlogUrl":68,"ownerDescription":6,"updatedAt":69,"install":70,"resources":83},"01M6PQTH7DA71HG6EM96RZENE2","omniverse-usd-performance-tuning",null,"Top-level workflow skill for USD performance diagnosis and optimization. Use for slow loading, high memory, low FPS, or 'optimize my scene' requests; delegates auth\u002Fruntime setup to Phase 0 owners.","headmktlucca-ui\u002Fneuroads-lp","headmktlucca-ui","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F247379838?v=4","01M6PDVAV6M1W96D1SR1PDF8CS","NeuroAds","01M6PDVAZ4P281GNDKD45CYTF5",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fomniverse-usd-performance-tuning\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"performance","performance tuning","usd","tuning","omniverse usd performance tuning","authentication","auth","read","orchestrator","optimize","workflow","optimizer","diagnosis","workflow skill","loading","memory","kit","top","validator","phase","2026-11-10 10:12:30",false,"---\nname: omniverse-usd-performance-tuning\ndescription: \"Top-level workflow skill for USD performance diagnosis and optimization. Use for slow loading, high memory, low FPS, or 'optimize my scene' requests; delegates auth\u002Fruntime setup to Phase 0 owners.\"\nversion: \"0.1.0\"\nlicense: Apache-2.0\ntools:\n  - Read\n  - Shell\n  - Write\ncompatibility: >\n  Orchestrator skill. Downstream phases may require Kit, Scene Optimizer, Asset Validator, USD Python, writable output paths, and omniverse:\u002F\u002F authentication selected by setup-usd-performance-tuning.\nmetadata:\n  author: NVIDIA Omniverse\n  tags:\n    - triage\n    - performance\n    - usd\n    - profiling\n  domain: ai-ml\n  languages:\n    - python\n---\n# Omniverse USD Performance Tuning\n\n\u003C!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->\n\u003C!-- SPDX-License-Identifier: Apache-2.0 -->\n\n## When to Use\n\nUse this workflow for broad performance asks such as slow loading, high memory, low FPS, GPU crashes, conversion-quality triage, or generic requests to optimize a USD scene.\n\n## Instructions\n\n1. Start from the mandatory runtime context gate before producing tuning output, unless the prompt is only asking for a static classification test.\n2. Classify broad optimization requests as `ready_to_plan`; reserve `approval_required` for prompts that explicitly name a destructive operation to execute before planning.\n3. Plan the full canonical chain through `optimization-report`, preserving the structured milestone order and the `profile-stage:baseline` \u002F `profile-stage:after` labels when listing milestones. For broad optimization, default to 3 scoped iterations unless the user opts out, asks for a quick pass, or stop criteria apply.\n4. Invoke downstream skill bodies only when their phase is reached, and keep raw runtime artifacts on disk while reading compact summaries.\n\nFrontmatter keeps `version` and `tools` at top level for agentskills.io runtime\ncompatibility. NVCARPS discoverability fields live under `metadata`.\n\n## Output Format\n\nReturn a plan or status summary that names the selected entry skill, uses `ready_to_plan` for generic optimization requests, includes the full milestone chain through `optimization-report`, and labels profile phases as `profile-stage:baseline` and `profile-stage:after`. For structured outputs, the broad-optimization milestone subsequence is `omniverse-usd-performance-tuning` -> `profile-stage:baseline` -> `usd-structure-assessment` -> `usd-validation-runner` -> `restructure-decision` -> `apply-restructure` -> `so-run-validators` -> `so-interpret-validators` -> `so-run-operations` -> `profile-stage:after` -> `compare-profiles` -> `optimization-report`. End-to-end execution should produce an optimized stage when mutation runs and a report conforming to the `optimization-report` reference's schema (`scripts\u002Foptimization-report.schema.json` within that reference). Broad optimization should plan 3 scoped iterations by default; each iteration writes an interim report\u002Fupdate and later passes reuse prior evidence instead of restarting the full workflow.\n\nUse this workflow for broad performance asks such as slow loading, low FPS,\nhigh memory, GPU crashes, conversion quality, or \"optimize my scene.\"\n\n## Entry skill rule\n\nThis skill is the named entry point for broad performance work whenever the\nagent has any verified way to do that work. Runtime probing details live in\n`setup-usd-performance-tuning`; this rule only decides which skill owns the\nuser-facing performance request.\n\n- If the setup probe shows **any** verified runtime path - Kit, standalone, or\n  even a partial stack such as Asset Validator only - enter here. If the\n  user's requested tool is missing, return the specific `blocked_code`\n  (`blocked_missing_scene_optimizer`, `blocked_missing_so_operation`, etc.)\n  instead of substituting another workflow.\n- Enter at `setup-usd-performance-tuning` only when **no** runtime path is\n  verified and runtime choice\u002Fsetup is the first unresolved problem.\n- For `omniverse:\u002F\u002F` assets, enter at `omniverse-authentication` first.\n  Authentication precedes setup and triage for remote assets.\n\nThe decision is about ownership, not order. Setup, authentication, and triage all run in their normal phase order; this rule only fixes which skill the agent **names as the entry skill** in its response.\n\n## Runtime context — session-start gate (mandatory)\n\n**Before any other tuning output**, follow the mandatory session-start gate in\n`skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fsetup-usd-performance-tuning\u002Freferences\u002Fruntime-context-header.md`.\nThat reference owns `output_path`, the canonical `setup-preflight.json`\nlocation, Format A\u002FFormat B, and the \"do not improvise a silent probe\"\nanti-pattern.\n\nRequired outcomes:\n\n- Missing or unreadable preflight: invoke `setup-usd-performance-tuning`.\n- Present preflight: print Format A and wait for the user to choose Continue,\n  Change Kit, Switch to standalone, or Re-run probe.\n- Confirmed runtime in the same session: use compact Format B for follow-up\n  status.\n\n```\n[Kit: {runtime_context.kit.application} {runtime_context.kit.version}  |  SO: {runtime_context.sceneOptimizer.version}  |  AV: {runtime_context.assetValidator.version}]\n```\n\n## Runtime artifact token budget\n\nBefore reading Kit logs, Asset Validator CSVs, Scene Optimizer logs, Tracy CSVs,\nor other runtime output, follow\n`references\u002Fruntime-artifact-token-budget.md`. Keep raw artifacts on disk, read\nsummary JSON first, and use bounded log snapshots instead of full dumps or live\nstreams.\n\n## Plan-time vs execution-time approval\n\n`approval_required` at planning time is reserved for requests that explicitly name a destructive operation. Use the following rule when deciding between `ready_to_plan` and `approval_required`:\n\n- **`approval_required` at planning time** — the user's request itself names a destructive operation: \"flatten this stage\", \"decimate the meshes\", \"merge prototypes\", \"delete unused prims\", or any specific named mutation that cannot be undone within the same workflow. In this case the agent's first response must be an approval prompt that names the operation, before the agent commits to a plan that executes it.\n- **`ready_to_plan` at planning time** — the user's request is general: \"optimize this scene\", \"make it load faster\", \"reduce GPU memory\", \"improve interactivity\". The agent lays out the full plan, including any destructive operations the plan would invoke (for example `so-run-operations` with `mergeMaterials`), without withholding the plan itself. **Approval for each destructive operation is requested alongside plan approval**.\n\nThe distinction is between **authorising a plan** and **authorising a destructive action**. A general optimisation request authorises planning; it does not authorise execution of specific destructive operations.\n\nFor structured runtime-test responses and similar planning summaries:\n\n- A future `restructure-decision` prompt is a planned user-decision gate, not a reason to set the top-level response `decision` to `approval_required` for a generic optimization request.\n- For a generic optimization request, set `decision: \"ready_to_plan\"` and include the full intended chain in both `committed_milestones` and `planned_phases`, through `optimization-report`.\n- It is valid for `gates_observed` to include `asks_user_for_restructure_decision` while the top-level `decision` remains `ready_to_plan`.\n- Whenever a chain names profile phases, use the exact labels `profile-stage:baseline` and `profile-stage:after`; do not emit the ambiguous bare `profile-stage` token.\n- Start structured milestone lists with `omniverse-usd-performance-tuning` as the owning entry skill. Include `setup-usd-performance-tuning` only as additional Phase 0 context, not as a replacement for the entry skill milestone.\n- For broad optimization requests, preserve the milestone subsequence from *Output Format* above exactly, with optional extra analysis steps inserted only where they do not reorder it.\n- Do not list `so-run-validators` or `so-interpret-validators` before `restructure-decision` in broad optimization milestone summaries. Phase-aware validator routing still happens through `usd-validation-runner`; the SO validator executor\u002Finterpreter milestones appear after the restructure decision path in the structured plan contract.\n\n## Output expectation\n\nEnd-to-end optimization work should produce both an optimized USD stage, when\nmutation is executed, and a structured optimization report conforming to\nthe `optimization-report` reference's `scripts\u002Foptimization-report.schema.json`. The HTML report must be rendered\nfrom `references\u002Freport-templates\u002Foptimization-report.html.template` via\n`render_preview.py` — never hand-write HTML. Diagnosis-only work should still\nend with a report or summary that states no optimized stage was written.\n\n## Purpose\n\nRoute digital twin USD performance requests into the right diagnostic and\noptimization workflow while preserving evidence before mutation.\n\n## Prerequisites\n\n- Stage path or enough context to identify the target asset.\n- User goal: diagnosis only, validation, profiling, or processor execution.\n- Runtime availability status from `setup-usd-performance-tuning` when not already known.\n- Permission status for in-place mutation vs writing a separate optimized output.\n\n## Examples\n\n- \"This USD loads slowly; triage what to check first.\"\n- \"Route a low-FPS CAD scene through the performance workflow.\"\n\n## Triage order\n\n0. **Runtime gate.** Follow the mandatory session-start gate above before\n   validation, profiling, or optimization. Do not scan, probe, install, or pick\n   Kit\u002Fstandalone runtimes directly in this skill; `setup-usd-performance-tuning`\n   owns probe\u002Fchooser\u002Finstall dispatch and writes the preflight consumed here.\n\n1. Identify the target problem:\n   - Load time.\n   - FPS or interactivity.\n   - GPU or system memory.\n   - Crash or device lost.\n   - CAD conversion quality.\n   - Validation failure.\n\n2. Gather minimum context:\n   - Stage path and size.\n   - Whether the stage is local, mounted, or `omniverse:\u002F\u002F` remote. For remote\n     assets, route through `omniverse-authentication` before first open.\n   - Kit or USD runtime.\n   - Whether the workload is CAD, VFI, AIF, Isaac, or generic OpenUSD.\n   - Whether in-place mutation is allowed.\n   - Whether the user wants diagnosis only or processor execution.\n\n3. Route:\n   - USD composition questions: `usd-structure-assessment` (composition is now part of the SA umbrella; deeper detail in `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fcomposition-audit.md`).\n   - Validation and content issues: `usd-validation-runner` (master router; routes to `validate-*` family or `so-run-validators` based on intent).\n   - Edit\u002Foutput decisions: `usd-edit-target-planner` (also owns variant\u002Fpayload gates).\n   - Repeated copied hierarchy or high mesh count with no instancing:\n     `usd-hierarchy-dedupe-candidates`.\n   - Restructure decision (monolithic stage, asset boundary materialization): `restructure-decision`.\n   - CAD converter settings: read `references\u002Fcad-conversion\u002FREADME.md` (niche pre-USD concern; see reference for details).\n   - Scene Optimizer: `so-run-validators`, `so-interpret-validators`, `so-run-operations`.\n\n## Optimization ordering\n\nFollow the canonical ordering in\n[workflow.md § Operation ordering invariants](references\u002Fworkflow.md#operation-ordering-invariants).\nThe high-level rule: **prototypes first → per-asset validation → stage-level\noperations last.** The workflow reference owns the full invariant list\n(meshCleanup before decimateMeshes, deduplication before decimation, never\nmerge if instanced, etc.) and the analysis-only ops catalogue.\n\n## Rules\n\n- Always run composition audit before mutation.\n- Always validate before and after processor execution.\n- Optimize prototypes before per-asset validation.\n- Do not run whole-stage mesh deduplication on very large CAD scenes before\n  checking for hierarchy-level reuse.\n- Do not recommend a fixed optimization stack without bottleneck evidence.\n- Do not invent numeric thresholds or expected percentage wins.\n- **Prefer canonical SO ops over specialty \u002F documentary ones.** The op\n  curation in `references\u002Foperations\u002F_curation.json` classifies every op\n  as `canonical`, `specialty`, `analysis`, `documentary`, or `deprecated`.\n  When more than one op could resolve the same finding, recommend the\n  canonical one first and only reach for a specialty op when the user\n  explicitly asks or the rationale warrants it. Specifically:\n  - For vertex welding, prefer canonical `meshCleanup` with explicit flags\n    over the standalone `mergeVertices` op. The standalone op is a\n    legacy\u002Fspecialty surface; use upstream `usd-optimize` for the operation\n    mechanics and local approval policy before mutating.\n  - For hierarchy dedupe, recommend `usd-hierarchy-dedupe-candidates` +\n    `apply-restructure` (the USD-authored rewrite path).\n  - For per-mesh dedupe, recommend `deduplicateGeometry` (canonical) over\n    `findCoincidingGeometry` (analysis — produces a report, not a change).\n  - Do not recommend `documentary`-status ops (e.g., `boxClip`,\n    `deletePrims`, `removeAttributes`, `removeUntypedPrims`,\n    `merge` outside its narrow non-instanced case) without an explicit\n    user request. Documentary ops survive in the per-op\n    `references\u002Foperations\u002F\u003Ckey>.md` routing stubs for completeness but are\n    excluded from agent-initiated recommendations.\n  - **Specialty ≠ documentary.** Ops classified as `specialty` in\n    `_curation.json` either (a) have validator-finding evidence that\n    wires them into the `so-interpret-validators` chain (e.g.\n    `sparseMeshes`, `optimizePrimvars`), or (b) are load-bearing escape\n    hatches needed for specific downstream contexts (e.g.\n    `primitivesToMeshes` when output must be `UsdGeomMesh`,\n    `utilityFunction` for instancing toggles and material rebinding,\n    `pythonScript` for `so-create-proxy` recipes). Recommend specialty\n    ops when their validator fires OR when their downstream context\n    applies — the suppression above only targets `documentary` ops.\n\n## Limitations\n\n- Does not replace downstream reference instructions; load each required\n  reference before executing it.\n- Does not install runtimes directly; follow setup or install references when\n  requirements are missing.\n- Does not authorize mutation when the user has not allowed writes.\n\n## Troubleshooting\n\n- If runtime status is unclear, run `setup-usd-performance-tuning` before profiling or validation.\n- If the reported problem is vague, gather stage path, workload type, and whether diagnosis or execution is requested.\n- If the workflow suggests mutation before evidence, return to baseline profiling and composition audit first.\n\n## References\n\nBefore routing, read:\n\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Foptimization-tradeoffs.md` — identify which pipeline phase the scene is in (extraction, structuring, or optimization). The right action depends on the phase.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Ffactory-level-structuring.md` — understand the three pillars (assets, aggregation, animation) and the seven-step structuring pattern.\n\nIf you have network access, prefer the live URLs (noted in each reference file) for the most current version.\n\n## Required execution flow\n\nRead `references\u002Fworkflow.md` for the canonical Phase 0-7 flow, including\nKit\u002Fstandalone branches, validator-stack routing, operation ordering,\ntermination conditions, duration hints, and the default three-pass scoped\niteration pattern.\nThe compact root map at `references\u002Fskill-map.md` only routes agents\ninto this workflow.\n\nDo not treat downstream phase names as plain checklist labels. Before executing\neach step, load that phase's nested `README.md` reference and follow its\ninstructions. Claude Code only exposes the public catalog skill; it does not\nrecursively inject `profile-stage`, `usd-structure-assessment`, or other nested\nreferences.\n\nThe final deliverable must come from `optimization-report`: save both the structured JSON report and the generated Markdown summary. Do not substitute an ad hoc `SUMMARY.md` or chat-only recap for the optimization report.\n\nFor deeper subtopic guidance, consult the references:\n\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fcomposition-audit.md`, `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Flayer-health.md` - subtopic detail for SA's Phase 1 checklist.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Finstancing-readiness\u002Freferences\u002Finstancing-tradeoffs.md` - merge safety, decision tree for instancing choices.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fusd-edit-target-planner\u002Freferences\u002Fvariants-payloads.md` - deeper variant\u002Fpayload trade-offs (gates are inline in usd-edit-target-planner).\n- `references\u002Fcad-conversion\u002FREADME.md` - CAD converter settings.\n- `references\u002Fupstreams\u002Fusd-optimize.md` - upstream SO mechanics and prebuilt package resolution.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-validation-runner\u002Freferences\u002Fso-run-validators\u002Freferences\u002Finfrastructure.md` - local handoff for SO validator infrastructure.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-validation-runner\u002FREADME.md` - tier 1\u002F2\u002F3 selected-probe plan, large-stage guardrails, full-sweep approval, and scene-aware adjustment.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Foptimization-report\u002Freferences\u002Foptimization-report-template.md` - the data contract every phase populates.\n\nFor full Kit runtime profiling (FPS, frame time, Hydra\u002FRTX metrics), refer to the external profiling skills at NVIDIA\u002Fomniperf.\n","# Omniverse USD Performance Tuning\n\n\u003C!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->\n\u003C!-- SPDX-License-Identifier: Apache-2.0 -->\n\n## When to Use\n\nUse this workflow for broad performance asks such as slow loading, high memory, low FPS, GPU crashes, conversion-quality triage, or generic requests to optimize a USD scene.\n\n## Instructions\n\n1. Start from the mandatory runtime context gate before producing tuning output, unless the prompt is only asking for a static classification test.\n2. Classify broad optimization requests as `ready_to_plan`; reserve `approval_required` for prompts that explicitly name a destructive operation to execute before planning.\n3. Plan the full canonical chain through `optimization-report`, preserving the structured milestone order and the `profile-stage:baseline` \u002F `profile-stage:after` labels when listing milestones. For broad optimization, default to 3 scoped iterations unless the user opts out, asks for a quick pass, or stop criteria apply.\n4. Invoke downstream skill bodies only when their phase is reached, and keep raw runtime artifacts on disk while reading compact summaries.\n\nFrontmatter keeps `version` and `tools` at top level for agentskills.io runtime\ncompatibility. NVCARPS discoverability fields live under `metadata`.\n\n## Output Format\n\nReturn a plan or status summary that names the selected entry skill, uses `ready_to_plan` for generic optimization requests, includes the full milestone chain through `optimization-report`, and labels profile phases as `profile-stage:baseline` and `profile-stage:after`. For structured outputs, the broad-optimization milestone subsequence is `omniverse-usd-performance-tuning` -> `profile-stage:baseline` -> `usd-structure-assessment` -> `usd-validation-runner` -> `restructure-decision` -> `apply-restructure` -> `so-run-validators` -> `so-interpret-validators` -> `so-run-operations` -> `profile-stage:after` -> `compare-profiles` -> `optimization-report`. End-to-end execution should produce an optimized stage when mutation runs and a report conforming to the `optimization-report` reference's schema (`scripts\u002Foptimization-report.schema.json` within that reference). Broad optimization should plan 3 scoped iterations by default; each iteration writes an interim report\u002Fupdate and later passes reuse prior evidence instead of restarting the full workflow.\n\nUse this workflow for broad performance asks such as slow loading, low FPS,\nhigh memory, GPU crashes, conversion quality, or \"optimize my scene.\"\n\n## Entry skill rule\n\nThis skill is the named entry point for broad performance work whenever the\nagent has any verified way to do that work. Runtime probing details live in\n`setup-usd-performance-tuning`; this rule only decides which skill owns the\nuser-facing performance request.\n\n- If the setup probe shows **any** verified runtime path - Kit, standalone, or\n  even a partial stack such as Asset Validator only - enter here. If the\n  user's requested tool is missing, return the specific `blocked_code`\n  (`blocked_missing_scene_optimizer`, `blocked_missing_so_operation`, etc.)\n  instead of substituting another workflow.\n- Enter at `setup-usd-performance-tuning` only when **no** runtime path is\n  verified and runtime choice\u002Fsetup is the first unresolved problem.\n- For `omniverse:\u002F\u002F` assets, enter at `omniverse-authentication` first.\n  Authentication precedes setup and triage for remote assets.\n\nThe decision is about ownership, not order. Setup, authentication, and triage all run in their normal phase order; this rule only fixes which skill the agent **names as the entry skill** in its response.\n\n## Runtime context — session-start gate (mandatory)\n\n**Before any other tuning output**, follow the mandatory session-start gate in\n`skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fsetup-usd-performance-tuning\u002Freferences\u002Fruntime-context-header.md`.\nThat reference owns `output_path`, the canonical `setup-preflight.json`\nlocation, Format A\u002FFormat B, and the \"do not improvise a silent probe\"\nanti-pattern.\n\nRequired outcomes:\n\n- Missing or unreadable preflight: invoke `setup-usd-performance-tuning`.\n- Present preflight: print Format A and wait for the user to choose Continue,\n  Change Kit, Switch to standalone, or Re-run probe.\n- Confirmed runtime in the same session: use compact Format B for follow-up\n  status.\n\n```\n[Kit: {runtime_context.kit.application} {runtime_context.kit.version}  |  SO: {runtime_context.sceneOptimizer.version}  |  AV: {runtime_context.assetValidator.version}]\n```\n\n## Runtime artifact token budget\n\nBefore reading Kit logs, Asset Validator CSVs, Scene Optimizer logs, Tracy CSVs,\nor other runtime output, follow\n`references\u002Fruntime-artifact-token-budget.md`. Keep raw artifacts on disk, read\nsummary JSON first, and use bounded log snapshots instead of full dumps or live\nstreams.\n\n## Plan-time vs execution-time approval\n\n`approval_required` at planning time is reserved for requests that explicitly name a destructive operation. Use the following rule when deciding between `ready_to_plan` and `approval_required`:\n\n- **`approval_required` at planning time** — the user's request itself names a destructive operation: \"flatten this stage\", \"decimate the meshes\", \"merge prototypes\", \"delete unused prims\", or any specific named mutation that cannot be undone within the same workflow. In this case the agent's first response must be an approval prompt that names the operation, before the agent commits to a plan that executes it.\n- **`ready_to_plan` at planning time** — the user's request is general: \"optimize this scene\", \"make it load faster\", \"reduce GPU memory\", \"improve interactivity\". The agent lays out the full plan, including any destructive operations the plan would invoke (for example `so-run-operations` with `mergeMaterials`), without withholding the plan itself. **Approval for each destructive operation is requested alongside plan approval**.\n\nThe distinction is between **authorising a plan** and **authorising a destructive action**. A general optimisation request authorises planning; it does not authorise execution of specific destructive operations.\n\nFor structured runtime-test responses and similar planning summaries:\n\n- A future `restructure-decision` prompt is a planned user-decision gate, not a reason to set the top-level response `decision` to `approval_required` for a generic optimization request.\n- For a generic optimization request, set `decision: \"ready_to_plan\"` and include the full intended chain in both `committed_milestones` and `planned_phases`, through `optimization-report`.\n- It is valid for `gates_observed` to include `asks_user_for_restructure_decision` while the top-level `decision` remains `ready_to_plan`.\n- Whenever a chain names profile phases, use the exact labels `profile-stage:baseline` and `profile-stage:after`; do not emit the ambiguous bare `profile-stage` token.\n- Start structured milestone lists with `omniverse-usd-performance-tuning` as the owning entry skill. Include `setup-usd-performance-tuning` only as additional Phase 0 context, not as a replacement for the entry skill milestone.\n- For broad optimization requests, preserve the milestone subsequence from *Output Format* above exactly, with optional extra analysis steps inserted only where they do not reorder it.\n- Do not list `so-run-validators` or `so-interpret-validators` before `restructure-decision` in broad optimization milestone summaries. Phase-aware validator routing still happens through `usd-validation-runner`; the SO validator executor\u002Finterpreter milestones appear after the restructure decision path in the structured plan contract.\n\n## Output expectation\n\nEnd-to-end optimization work should produce both an optimized USD stage, when\nmutation is executed, and a structured optimization report conforming to\nthe `optimization-report` reference's `scripts\u002Foptimization-report.schema.json`. The HTML report must be rendered\nfrom `references\u002Freport-templates\u002Foptimization-report.html.template` via\n`render_preview.py` — never hand-write HTML. Diagnosis-only work should still\nend with a report or summary that states no optimized stage was written.\n\n## Purpose\n\nRoute digital twin USD performance requests into the right diagnostic and\noptimization workflow while preserving evidence before mutation.\n\n## Prerequisites\n\n- Stage path or enough context to identify the target asset.\n- User goal: diagnosis only, validation, profiling, or processor execution.\n- Runtime availability status from `setup-usd-performance-tuning` when not already known.\n- Permission status for in-place mutation vs writing a separate optimized output.\n\n## Examples\n\n- \"This USD loads slowly; triage what to check first.\"\n- \"Route a low-FPS CAD scene through the performance workflow.\"\n\n## Triage order\n\n0. **Runtime gate.** Follow the mandatory session-start gate above before\n   validation, profiling, or optimization. Do not scan, probe, install, or pick\n   Kit\u002Fstandalone runtimes directly in this skill; `setup-usd-performance-tuning`\n   owns probe\u002Fchooser\u002Finstall dispatch and writes the preflight consumed here.\n\n1. Identify the target problem:\n   - Load time.\n   - FPS or interactivity.\n   - GPU or system memory.\n   - Crash or device lost.\n   - CAD conversion quality.\n   - Validation failure.\n\n2. Gather minimum context:\n   - Stage path and size.\n   - Whether the stage is local, mounted, or `omniverse:\u002F\u002F` remote. For remote\n     assets, route through `omniverse-authentication` before first open.\n   - Kit or USD runtime.\n   - Whether the workload is CAD, VFI, AIF, Isaac, or generic OpenUSD.\n   - Whether in-place mutation is allowed.\n   - Whether the user wants diagnosis only or processor execution.\n\n3. Route:\n   - USD composition questions: `usd-structure-assessment` (composition is now part of the SA umbrella; deeper detail in `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fcomposition-audit.md`).\n   - Validation and content issues: `usd-validation-runner` (master router; routes to `validate-*` family or `so-run-validators` based on intent).\n   - Edit\u002Foutput decisions: `usd-edit-target-planner` (also owns variant\u002Fpayload gates).\n   - Repeated copied hierarchy or high mesh count with no instancing:\n     `usd-hierarchy-dedupe-candidates`.\n   - Restructure decision (monolithic stage, asset boundary materialization): `restructure-decision`.\n   - CAD converter settings: read `references\u002Fcad-conversion\u002FREADME.md` (niche pre-USD concern; see reference for details).\n   - Scene Optimizer: `so-run-validators`, `so-interpret-validators`, `so-run-operations`.\n\n## Optimization ordering\n\nFollow the canonical ordering in\n[workflow.md § Operation ordering invariants](references\u002Fworkflow.md#operation-ordering-invariants).\nThe high-level rule: **prototypes first → per-asset validation → stage-level\noperations last.** The workflow reference owns the full invariant list\n(meshCleanup before decimateMeshes, deduplication before decimation, never\nmerge if instanced, etc.) and the analysis-only ops catalogue.\n\n## Rules\n\n- Always run composition audit before mutation.\n- Always validate before and after processor execution.\n- Optimize prototypes before per-asset validation.\n- Do not run whole-stage mesh deduplication on very large CAD scenes before\n  checking for hierarchy-level reuse.\n- Do not recommend a fixed optimization stack without bottleneck evidence.\n- Do not invent numeric thresholds or expected percentage wins.\n- **Prefer canonical SO ops over specialty \u002F documentary ones.** The op\n  curation in `references\u002Foperations\u002F_curation.json` classifies every op\n  as `canonical`, `specialty`, `analysis`, `documentary`, or `deprecated`.\n  When more than one op could resolve the same finding, recommend the\n  canonical one first and only reach for a specialty op when the user\n  explicitly asks or the rationale warrants it. Specifically:\n  - For vertex welding, prefer canonical `meshCleanup` with explicit flags\n    over the standalone `mergeVertices` op. The standalone op is a\n    legacy\u002Fspecialty surface; use upstream `usd-optimize` for the operation\n    mechanics and local approval policy before mutating.\n  - For hierarchy dedupe, recommend `usd-hierarchy-dedupe-candidates` +\n    `apply-restructure` (the USD-authored rewrite path).\n  - For per-mesh dedupe, recommend `deduplicateGeometry` (canonical) over\n    `findCoincidingGeometry` (analysis — produces a report, not a change).\n  - Do not recommend `documentary`-status ops (e.g., `boxClip`,\n    `deletePrims`, `removeAttributes`, `removeUntypedPrims`,\n    `merge` outside its narrow non-instanced case) without an explicit\n    user request. Documentary ops survive in the per-op\n    `references\u002Foperations\u002F\u003Ckey>.md` routing stubs for completeness but are\n    excluded from agent-initiated recommendations.\n  - **Specialty ≠ documentary.** Ops classified as `specialty` in\n    `_curation.json` either (a) have validator-finding evidence that\n    wires them into the `so-interpret-validators` chain (e.g.\n    `sparseMeshes`, `optimizePrimvars`), or (b) are load-bearing escape\n    hatches needed for specific downstream contexts (e.g.\n    `primitivesToMeshes` when output must be `UsdGeomMesh`,\n    `utilityFunction` for instancing toggles and material rebinding,\n    `pythonScript` for `so-create-proxy` recipes). Recommend specialty\n    ops when their validator fires OR when their downstream context\n    applies — the suppression above only targets `documentary` ops.\n\n## Limitations\n\n- Does not replace downstream reference instructions; load each required\n  reference before executing it.\n- Does not install runtimes directly; follow setup or install references when\n  requirements are missing.\n- Does not authorize mutation when the user has not allowed writes.\n\n## Troubleshooting\n\n- If runtime status is unclear, run `setup-usd-performance-tuning` before profiling or validation.\n- If the reported problem is vague, gather stage path, workload type, and whether diagnosis or execution is requested.\n- If the workflow suggests mutation before evidence, return to baseline profiling and composition audit first.\n\n## References\n\nBefore routing, read:\n\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Foptimization-tradeoffs.md` — identify which pipeline phase the scene is in (extraction, structuring, or optimization). The right action depends on the phase.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Ffactory-level-structuring.md` — understand the three pillars (assets, aggregation, animation) and the seven-step structuring pattern.\n\nIf you have network access, prefer the live URLs (noted in each reference file) for the most current version.\n\n## Required execution flow\n\nRead `references\u002Fworkflow.md` for the canonical Phase 0-7 flow, including\nKit\u002Fstandalone branches, validator-stack routing, operation ordering,\ntermination conditions, duration hints, and the default three-pass scoped\niteration pattern.\nThe compact root map at `references\u002Fskill-map.md` only routes agents\ninto this workflow.\n\nDo not treat downstream phase names as plain checklist labels. Before executing\neach step, load that phase's nested `README.md` reference and follow its\ninstructions. Claude Code only exposes the public catalog skill; it does not\nrecursively inject `profile-stage`, `usd-structure-assessment`, or other nested\nreferences.\n\nThe final deliverable must come from `optimization-report`: save both the structured JSON report and the generated Markdown summary. Do not substitute an ad hoc `SUMMARY.md` or chat-only recap for the optimization report.\n\nFor deeper subtopic guidance, consult the references:\n\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fcomposition-audit.md`, `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Flayer-health.md` - subtopic detail for SA's Phase 1 checklist.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Finstancing-readiness\u002Freferences\u002Finstancing-tradeoffs.md` - merge safety, decision tree for instancing choices.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-structure-assessment\u002Freferences\u002Fusd-edit-target-planner\u002Freferences\u002Fvariants-payloads.md` - deeper variant\u002Fpayload trade-offs (gates are inline in usd-edit-target-planner).\n- `references\u002Fcad-conversion\u002FREADME.md` - CAD converter settings.\n- `references\u002Fupstreams\u002Fusd-optimize.md` - upstream SO mechanics and prebuilt package resolution.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-validation-runner\u002Freferences\u002Fso-run-validators\u002Freferences\u002Finfrastructure.md` - local handoff for SO validator infrastructure.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Fusd-validation-runner\u002FREADME.md` - tier 1\u002F2\u002F3 selected-probe plan, large-stage guardrails, full-sweep approval, and scene-aware adjustment.\n- `skills\u002Fomniverse-usd-performance-tuning\u002Freferences\u002Foptimization-report\u002Freferences\u002Foptimization-report-template.md` - the data contract every phase populates.\n\nFor full Kit runtime profiling (FPS, frame time, Hydra\u002FRTX metrics), refer to the external profiling skills at NVIDIA\u002Fomniperf.\n",{"name":5,"tools":49,"license":15,"version":53,"metadata":54,"description":7,"compatibility":62},[50,51,52],"Read","Shell","Write","0.1.0",{"tags":55,"author":58,"domain":59,"languages":60},[56,24,26,57],"triage","profiling","NVIDIA Omniverse","ai-ml",[61],"python","Orchestrator skill. 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Use this skill when creating, updating, or designing game worlds via MCP tools.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fworld-builder\u002FSKILL.md",[706,709],{"categoryNo":707,"categoryName":708,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[711,712,713,714,715,716,717,718,669,719,720,721,722,723,724,698,725],"builder","world","world builder","MCP","create","mcp tools","Tools","game","pokemon","manage","style","via","theme","zone","generative",{"skillNo":727,"name":728,"nameZh":6,"description":729,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":656,"licenseFileUrl":6,"sourceHtmlUrl":730,"categories":731,"keywords":734,"publishedAt":44},"01M6PT9Z92JTSQEHE1QR0NNW5F","webdriverio-skill","Generates WebdriverIO (WDIO) automation tests in JavaScript or TypeScript. Supports local and TestMu AI cloud. Use when user mentions \"WebdriverIO\", \"WDIO\", \"wdio.conf\", \"browser.url\", \"$\", \"$$\". Triggers on: \"WebdriverIO\", \"WDIO\", \"wdio\", \"browser.$\".","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fwebdriverio-skill\u002FSKILL.md",[732,733],{"categoryNo":660,"categoryName":661,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[735,666,736,686,737,738,739,740,668,669,741,694,670,671,742,743],"webdriverio skill","typescript","javascript","browser","cloud","e2e","e2e-testing","URL","conf",{"skillNo":745,"name":746,"nameZh":6,"description":747,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":656,"licenseFileUrl":6,"sourceHtmlUrl":748,"categories":749,"keywords":759,"publishedAt":44},"01M6PT9NVK36ZWCQ69YXK3FR4K","web-design-guidelines","Web platform design and accessibility guidelines. Use when building web interfaces, auditing accessibility, implementing responsive layouts, or reviewing web UI code. Triggers on tasks involving HTML, CSS, web components, WCAG compliance, responsive design, or web performance.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fweb\u002FSKILL.md",[750,753,754],{"categoryNo":751,"categoryName":752,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":707,"categoryName":708,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":755,"categoryName":756,"taxonomyType":757,"taxonomyTypeDesc":758},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[760,761,762,763,764,765,24,766,767,768,769,770,771,772,773,774,775,776,671,777],"design","web","guidelines","web design guidelines","web design","css","components","web components","tasks","code","web performance","ui","platform design","html","responsive design","responsive","platform","implementing",{"skillNo":779,"name":780,"nameZh":6,"description":781,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":656,"licenseFileUrl":6,"sourceHtmlUrl":782,"categories":783,"keywords":786,"publishedAt":44},"01M6PT9A3JKRE3X34276F2FW5R","watchos-design-guidelines","Apple Human Interface Guidelines for Apple Watch. Use when building watchOS apps, complications, or workout features. Triggers on tasks involving Watch UI, Digital Crown, glanceable interfaces, or wrist-based interactions.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fwatchos\u002FSKILL.md",[784,785],{"categoryNo":707,"categoryName":708,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":755,"categoryName":756,"taxonomyType":757,"taxonomyTypeDesc":758},[760,762,787,768,771,669,788,789,695,776,790,671,696,791,698,792,793],"watchos design guidelines","workout","human","watch","interface","platform-design","features"]