Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →nvidia/holoscan-install-wheel
Install Holoscan SDK Python wheel via pip into a venv.
Passed 17 of 22 test cases with the skill, and 7 of 22 without it.
and 11 more in the full report
10 fixed7 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
If I don't have the racerx dataset for video_replayer, what script provided by the Debian installation downloads the example data automatically?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies the system helper script provided by the Debian package for sample data acquisition. | Missed | Passed |
| Specifies path `/opt/nvidia/holoscan/examples/download_example_data`. | Missed | Passed |
The instructions your model reads when the skill loads.
Install the Holoscan SDK Python bindings via the holoscan-cu12 / holoscan-cu13 pip wheel into a virtual environment, and verify with hello_world and video_replayer.
nvidia-smi).PATH matching the host CUDA major (12 or 13).venv available.docs.nvidia.com./holoscan-install-debian.holoscan-cu12 and holoscan-cu13 are mutually exclusive — wheel must match host CUDA driver.video_replayer data ships only with the Debian package; without it, set HOLOSCAN_INPUT_PATH to a directory containing racerx/.ulimit -s 32768 is recommended in every shell that runs Holoscan — without it some apps emit a stack-size warning or, in rarer cases, segfault.Always fetch the pip-wheel section of https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html before installing. Extract: exact wheel package names (holoscan-cu12, holoscan-cu13), the supported Python range for the current release, prerequisites that must be on PATH (CUDA Toolkit), and any optional extras (LibTorch / ONNX Runtime version pins). If the doc disagrees with anything below, the doc wins.
You need the CUDA variant already determined. If not known, run nvidia-smi 2>&1 | head -5 first.
CUDA variant rule — pick the pip package:
| nvidia-smi CUDA Version | pip package |
|---|---|
| 13.x+ | holoscan-cu13 |
| 12.x (any GPU) | holoscan-cu12 |
Prerequisites: CUDA Toolkit on PATH, Python 3.10–3.13. Optional extras: LibTorch 2.11.0+, ONNX Runtime 1.22.0+.
Always install into a Python virtual environment — this avoids system-package conflicts and is required on Ubuntu 24.04 (which blocks system-wide pip entirely).
Check if one exists first:
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.