用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/NVIDIA-Omniverse/omniverse-labs --skill usd-tokens命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Use when setting up a fresh clone of this repo to run OVRTX Dev Variant Presenter (also called the "variant studio" in the walkthrough video and earlier releases) — no .venv yet, ovrtx/ovstage/ovstream not installed, ModuleNotFoundError on ovrtx/ovstage/ovstream, or "how do I install / get this running". RTX + uv; validated on Windows.
Use when asked to start, run, launch, restart, or bring up the OVRTX Dev Variant Presenter server, stream, or viewport in this repo — also called the "variant studio" in the walkthrough video and earlier releases — or after the stream / GPU / server was lost and needs recovering. RTX required; validated on Windows.
Build a browser-based, RTX-streamed app for exploring and rendering USD VARIANT PERMUTATIONS — a live ovstream/WebRTC viewport plus instant variant switching, cameras, a turntable rig, grid/batch stills, a multi-track timeline, projects, post, and remote-stage mirroring. Use when asked to build a "variant presenter / configurator" — or a "variant studio", the name used in the walkthrough video and earlier releases — a permutation render tool, or to add variant/timeline/batch features on top of an Omniverse realtime viewer.
基于 SOC 职业分类
正在显示 SKILL.md
| name | usd-tokens |
| description | Use this skill when implementing or verifying USD token values. |
| metadata | {"author":"NVIDIA"} |
Use this skill when implementing or verifying USD token values.
specification/foundational_data_types/README.md section Scalar Typesspecification/foundational_data_types/README.md section List Operationsspecification/glossary/README.md entry Tokenspecification/document_data_model/README.md section Value Rangesspecification/file_formats/README.md sections Values and Crate tokenPinned tag / commit: v1.0.1
The token fundamental type has the same value domain as string: a UTF-8
encoded string. The token type exists because runtimes are expected to optimize
commonly used strings for hashing and equality. Tokens often serve the role of
enumerated values, but the type itself does not restrict values to identifiers,
keywords, non-empty strings, or strings without whitespace.
This skill owns the Token handle contract in
contracts/handles/token.handle.json. A TokenHandle is an opaque reference
owned by a target-specific context; it is not a required class, struct layout,
pointer type, intern-table index, string representation, or product API.
Targets may implement tokens as interned strings, atom table indices, arena
entries, reference-counted string handles, or plain strings where that target
still satisfies the conformance and performance expectations for its scope.
Those are storage strategies, not the public semantic shape of the generated
library. A target must keep token distinguishable from string in the USD
value model and must expose a named Token abstraction or equivalent first-class
value type for implementation code. Raw primitive IDs may be used internally,
but they must not be the primary token abstraction generated for the library.
Token equality and hashing are defined within a compatible token identity domain. Implementations may realize that domain with a process-wide registry, runtime-owned registry, sharded registry, pointer-stable string pool, target-language atom facility, or another strategy. A token identity must not be merely an ID from an unrelated local table unless tokens from that table cannot escape or be compared with tokens from another table.
This skill also owns the performance contract in
contracts/performance/token.performance.json. Equality, hashing, and
assignment/copy of existing token handles must be flat with respect to token
text length. Interning from arbitrary text is deliberately measured separately
because construction must inspect the input text.
The generated implementation should make Token visible as a domain concept.
For targets with nominal types, Token should be a distinct class, struct,
newtype, alias with type-checking value, or equivalent native abstraction. For
dynamic targets, Token should be represented by a dedicated value object or
tagged value rather than an unadorned integer or string.
Token values should be cheap to copy or assign. Equality and hashing should use registered identity where available, not re-scan token text. String conversion may consult the registry/table/context that owns the token text.
Token values are immutable after creation and may be copied, assigned, compared, and hashed concurrently without caller synchronization. Interning into a shared token identity domain must either be safe under concurrent calls or the target must explicitly declare a weaker single-threaded threading model for this skill.
Do not impose identifier, keyword, schema, or field-specific restrictions in the token type. Those restrictions belong to the caller, metadata field, schema, or USDA syntax layer.
Do not implement token listOp composition here. This skill only supplies token identity, string conversion, equality, and hashing behavior needed by listOps.
Do not make USDA spelling decisions here. Parsing whether a token came from an
identifier or quoted string belongs to usda-value-parser.
benchmarks/token/targets.json