application-flow
High-level overview of a typical ovrtx application lifecycle. Use when user asks how to structure an ovrtx program, what the main…
Upgrade skill to migrate an existing ovrtx codebase from 0.2.0 to 0.3.0. Use when the user asks to "upgrade from 0.2 to 0.3", migrate ovrtx API usage, update 0.2 projects to 0.3, or fix code after moving from ovrtx 0.2.x to 0.3.x.
$ npx -y skills add nvidia-omniverse/ovrtx --skill update-0_2-0_3 --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/update-0_2-0_3Context preview
The summary Claude sees to decide when to auto-load this skill.
Upgrade skill to migrate an existing ovrtx codebase from 0.2.0 to 0.3.0. Use when the user asks to "upgrade from 0.2 to 0.3", migrate ovrtx API usage, update 0.2 projects to 0.3, or fix code after moving from ovrtx 0.2.x to 0.3.x.
# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: LicenseRef-NvidiaProprietary # # NVIDIA CORPORATION, its affiliates and licensors retain all intellectual # property and proprietary rights in and to this material, related # documentation and any modifications thereto. Any use, reproduction, # disclosure or distribution of this material and related documentation # without an express license agreement from NVIDIA CORPORATION or # its affiliates is strictly prohibited. name: update-0_2-0_3 description: > Upgrade skill to migrate an existing ovrtx codebase from 0.2.0 to 0.3.0. Use when the user asks to "upgrade from 0.2 to 0.3", migrate ovrtx API usage, update 0.2 projects to 0.3, or fix code after moving from ovrtx 0.2.x to 0.3.x. license: LicenseRef-NvidiaProprietary author: NVIDIA ovrtx tags: - ovrtx - upgrade - migration tools: - Read - Grep - Edit
Use this skill when the user asks to upgrade an existing ovrtx project from 0.2.0 or 0.2.x to 0.3.0 or 0.3.x, especially with the prompt "upgrade from 0.2 to 0.3".
Do not use this for brand-new examples unless the user explicitly wants migration guidance. For new code, prefer the topic skills that describe current 0.3 usage directly.
Resolve inputs in this order: the user's repository, its dependency files, then source code and docs.
1. Find version pins first. Search package and lock files for `ovrtx==0.2`, `ovrtx~=0.2`, or equivalent C package references. Update to the user's requested 0.3 build; in this repo's examples the packaged Python pin is `ovrtx==0.3.0`. 2. Scan for 0.2-only Python symbols: `RendererResult`, `add_usd`, `add_usd_layer`, `add_usd_async`, `add_usd_layer_async`, `output_partial_frames`, `step_async`, and `MappedRenderVar.tensor`. 3. Scan for 0.2-only C symbols: `ovrtx_add_usd`, `ovrtx_usd_input_t`, `ovrtx_rendered_output_t`, `ovrtx_map_rendered_output`, `ovrtx_unmap_rendered_output`, `ovrtx_rendered_output_handle_t`, `ovrtx_rendered_output_map_handle_t`, `OVRTX_CONFIG_OUTPUT_PARTIAL_FRAMES`, `ovrtx_release_errors`, `ovrtx_flush_op_log`, and old renderer-scoped `ovrtx_set_log_callback` calls. 4. Rewrite USD loading by intent:
5. Rewrite Python async rendering. `Renderer.step()` still returns fetched outputs. `Renderer.step_async()` now returns `Operation[PendingFetch[RenderProductSetOutputs]]`; call `wait()` for the pending fetch and then `fetch()` for outputs. 6. Rewrite render output mapping. In Python, use DLPack directly on a single-tensor mapping or named tensor/param access for composite outputs. In C, map to `ovrtx_render_var_output_t`, read `tensors[]` and `params[]`, then unmap with `ovrtx_unmap_render_var_output`. 7. Remove global partial-frame config. If 0.2 code explicitly disabled partial frames, author `bool omni:sensor:Core:accumulateOutputs = true` on the affected camera prim instead. If 0.2 code omitted the setting or used the default partial-frame behavior, remove the config without replacement. 8. Rewrite C wait/error handling. Read `ovrtx_op_wait_result_t.error_op_ids`, fetch strings with `ovrtx_get_last_op_error()`, copy or print them before the next wait on the same thread, and remove `ovrtx_release_errors`. 9. Rewrite C logging. The callback is process-global, no longer receives an op id, uses carb-style severity values, and flushing is `ovrtx_flush_log(timeout)`. 10. Validate with the narrowest runnable project tests or examples. For Python projects, run the user's normal test command or at least import and exercise the migrated code path. For C/C++ projects, rebuild so removed symbols are caught at compile time.
This skill has no scripts. Use repository search and targeted edits directly.
Update the ovrtx dependency pin, remove `RendererResult` imports, and remove
ovrtx is a C and Python library for embedding Omniverse RTX sensor simulation and visualization directly into applications.
High-level overview of a typical ovrtx application lifecycle. Use when user asks how to structure an ovrtx program, what the main…
Asynchronous operation patterns including polling, timeouts, and non-blocking workflows. Use when user asks about async…
Replacing persistent ovrtx attribute bindings with reusable ovstage queries for repeated writes or maps. Use when user asks about…
Binding materials to prims at runtime. Use when user asks to assign a material, change a material, set material binding, or swap…
Available camera render outputs for Real-Time Path-Tracing (RT2) mode. Use when user asks what AOVs/render vars are available,…
Cloning USD subtrees to create copies at new paths. Use when user asks to clone, duplicate, copy a prim, or create instances of…