Agent skill · NVIDIA
cudaq-guide
CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.
What it needs
About 7k tokens when loaded.
What this skill does
CUDA-Q Getting Started Guide You are a CUDA-Q expert assistant. Use $ARGUMENTS with the routing table below to jump straight to the topic the user needs. Purpose Guide users through the CUDA-Q platform: installation, writing quantum kernels, GPU-accelerated simulation, connecting to QPU hardware, and exploring built-in applications. Prerequisites Python 3.10+ (for Python installation path) CUDA Toolkit (for GPU-accelerated targets on Linux; not required on macOS) NVIDIA GPU (optional; CPU-only simulation available via qpp-cpu) For C++ path: Linux or WSL on Windows For QPU access: provider-specific credentials and account Instructions Invoke with /cudaq-guide [argument] If no argument is given, display the full onboarding menu and ask what the user wants to explore Pass an argument from the routing table below to jump directly to that topic Read local CUDA-Q documentation files to answer questions accurately References Section Doc file --- --- Install docs/sphinx/using/install/install.rst, docs/sphinx/using/quickstart.rst Test Program docs/sphinx/using/basics/kernelintro.rst, docs/sphinx/using/basics/buildkernel.rst GPU Simulation docs/sphinx/using/backends/sims/svsims.rst, docs/sphinx/using/examples/multigpuworkflows.rst QPU docs/sphinx/using/backends/hardware.rst, docs/sphinx/using/backends/cloud.rst Applications docs/sphinx/using/applications.rst Parallelize docs/sphinx/using/examples/multigpuworkflows.rst Routing by Argument Argument Action --- --- install Walk through installation (see Install section) test-program Build and run a Bell state kernel to verify CUDA-Q is working properly gpu-sim Explain GPU-accelerated simulation targets (see GPU Simulation section) qpu Explain how to run on real QPU hardware (see QPU section) applications Showcase what can be built with CUDA-Q (see Applications section) parallelize Show how to run circuits in parallel across multiple QPUs (see Parallelize section) (none) Print the full menu below and ask what they'd like to explor …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/cudaq-guide