Search the NVIDIA CUDA-Q documentation and return ranked excerpts.

Use this before answering any CUDA-Q question from memory: the platform moves quickly and memorized APIs are often stale. Each result carries a breadcrumb, an excerpt, and the canonical doc URL to cite.

Args: query: Natural language or keywords, for example "run kernel on GPU state vector" or "quantinuum credentials". version: Docs version such as "0.15.0" or "latest". Defaults to the installed cudaq version. limit: Maximum number of results (default 5).

Fetch one documentation page as clean markdown.

Args: path: Page path as returned by search_docs, for example "using/quick_start" or "using/backends/sims/svsims". version: Docs version. Defaults to the installed cudaq version.

Resolve a CUDA-Q API symbol to its canonical definition and doc URL.

Args: name: Symbol name, full or partial: "sample", "cudaq.observe", "qvector", "set_target". language: "python" or "cpp" to filter; omit for both. version: Docs version. Defaults to the installed cudaq version.

Find complete, runnable CUDA-Q example programs.

Sources are the example, snippet, and application files shipped in the CUDA-Q repository at the matching release. Prefer adapting these over writing kernels from memory.

Args: query: What the example should show, for example "GHZ state", "VQE", or "noise model". language: "python" or "cpp" to filter; omit for both. version: Docs version. Defaults to the installed cudaq version. limit: Maximum number of examples (default 3).

List CUDA-Q execution targets (backends) with guidance on choosing.

Covers simulators (CPU, GPU state vector, tensor network, noisy, dynamics), quantum hardware providers, and cloud aggregators, each with selection snippets and doc URLs. Call this when deciding where to run a kernel or when the user names a provider.

Args: category: Optional filter: "simulator", "hardware", or "cloud".