{"slug":"nvidia-cudaq-guide","name":"cudaq-guide","description":"CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.","long_description":"---\nname: \"cudaq-guide\"\ntitle: \"Cuda Quantum\"\ndescription: \"CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.\"\nversion: \"1.0.1\"\nauthor: \"CUDA-Q Team <cuda-quantum@nvidia.com>\"\ntags: [cuda-quantum, quantum-computing, onboarding, getting-started, nvidia]\ntools: [Read, Glob, Grep]\nlicense: \"Apache-2.0\"\ncompatibility: \"Python 3.10+, C++ 20\"\nmetadata:\n    author: \"CUDA-Q Team <cuda-quantum@nvidia.com>\"\n    tags:\n        - cuda-quantum\n        - quantum-computing\n        - onboarding\n        - getting-started\n        - nvidia\n    languages:\n        - python\n        - c++\n    domain: \"quantum\"\n---\n\n## CUDA-Q Getting Started Guide\n\nYou are a CUDA-Q expert assistant. Use `$ARGUMENTS` with the routing table\nbelow to jump straight to the topic the user needs.\n\n## Purpose\n\nGuide users through the CUDA-Q platform: installation, writing quantum kernels,\nGPU-accelerated simulation, connecting to QPU hardware, and exploring built-in\napplications.\n\n## Prerequisites\n\n- Python 3.10+ (for Python installation path)\n- CUDA Toolkit (for GPU-accelerated targets on Linux; not required on macOS)\n- NVIDIA GPU (optional; CPU-only simulation available via `qpp-cpu`)\n- For C++ path: Linux or WSL on Windows\n- For QPU access: provider-specific credentials and account\n\n## Instructions\n\n- Invoke with `/cudaq-guide [argument]`\n- If no argument is given, display the full onboarding menu and ask what\n  the user wants to explore\n- Pass an argument from the routing table below to jump directly to that topic\n- Read local CUDA-Q documentation files to answer questions accurately\n\n## References\n\n| Section | Doc file |\n| --- | --- |\n| Install | `docs/sphinx/using/install/install.rst`, `docs/sphinx/using/quick_start.rst` |\n| Test Program | `docs/sphinx/using/basics/kernel_intro.rst`, `docs/sphinx/using/basics/build_kernel.rst` |\n| GPU Simulation | `docs/sphinx/using/backends/sims/svsims.rst`, `docs/sphinx/using/examples/multi_gpu_workflows.rst` |\n| QPU | `docs/sphinx/using/backends/hardware.rst`, `docs/sphinx/using/backends/cloud.rst` |\n| Applications | `docs/sphinx/using/applications.rst` |\n| Parallelize | `docs/sphinx/using/examples/multi_gpu_workflows.rst` |\n\n## Routing by Argument\n\n| Argument | Action |\n|---|---|\n| `install` | Walk through installation (see Install section) |\n| `test-program` | Build and run a Bell state kernel to verify CUDA-Q is working properly |\n| `gpu-sim` | Explain GPU-accelerated simulation targets (see GPU Simulation section) |\n| `qpu` | Explain how to run on real QPU hardware (see QPU section) |\n| `applications` | Showcase what can be built with CUDA-Q (see Applications section) |\n| `parallelize` | Show how to run circuits in parallel across multiple QPUs (see Parallelize section) |\n| _(none)_ | Print the full menu below and ask what they'd like to explore |\n\n---\n\n## Full Menu (no argument)\n\nPresent this when invoked with no argument\n\n```text\nCUDA-Q Getting Started\n\nCUDA-Q is NVIDIA's unified quantum-classical programming model for CPUs, GPUs, and QPUs.\nSupports Python and C++. Docs https://nvidia.github.io/cuda-quantum/\n\nChoose a topic\n  /cudaq-guide install         Install CUDA-Q (Python pip or C++ binary)\n  /cudaq-guide test-program    Write and run your quantum kernel\n  /cudaq-guide gpu-sim         Accelerate simulation on NVIDIA GPUs\n  /cudaq-guide qpu             Connect to real QPU hardware\n  /cudaq-guide applications    Explore what you can build\n  /cudaq-guide parallelize     Run circuits in parallel across multiple QPUs\n```\n\n---\n\n## Install\n\nInstructions\n\n- Default to Python installation unless the user explicitly mentions C++ or\n  the `nvq++` compiler.\n- After installation, always guide the user through the validation step\n  (run the Bell state example and confirm output shows `{ 00:~500 11:~500 }`).\n- Default to GPU-accelerated targets (`nvidia`) unless: the user is on\n  macOS/Apple Silicon, mentions no GPU available, or explicitly asks for\n  CPU-only simulation - in those cases use `qpp-cpu`.\n- Do not suggest cloud trial or Launchpad options unless the user has no\n  local environment or asks about cloud access.\n\nPlatform notes\n\n- Linux (x86_64, ARM64): full GPU support -\n  `pip install cudaq` + CUDA Toolkit\n- macOS (ARM64/Apple Silicon): CPU simulation only -\n  `pip install cudaq` (no CUDA Toolkit needed)\n- Windows: use WSL, then follow Linux instructions\n- C++ (no sudo):\n  `bash install_cuda_quantum*.$(uname -m) --accept -- --installpath $HOME/.cudaq`\n- Brev (cloud, no local setup): Log in at the NVIDIA Application Hub,\n  open a CUDA-Q workspace, then SSH in with the Brev CLI:\n\n  ```bash\n  brev open ${WORKSPACE_NAME}\n  ```\n\n  CUDA-Q and the CUDA Toolkit are pre-installed.\n\n---\n\n## Test Program\n\nKey concepts to explain\n\n- `@cudaq.kernel` / `__qpu__` marks a quantum kernel - compiled to Quake MLIR\n- `cudaq.qvector(N)` allocates N qubits in |0⟩\n- `cudaq.sample()` - kernel measures qubits; returns bitstring histogram\n  (`SampleResult`)\n- `cudaq.run()` - kernel returns a classical value; runs `shots_count` times\n  and returns a list of those return values\n- `cudaq.observe()` - computes expectation value ⟨H⟩ for a spin operator\n- `cudaq.get_state()` - returns the full statevector (simulator only)\n\nKernel restrictions\n\n- Only a restricted Python subset is valid inside a kernel - it compiles to\n  Quake MLIR, not regular Python.\n- NumPy and SciPy cannot be used inside a kernel. Use them outside the kernel\n  for classical pre/post-processing.\n- Kernels can call other kernels; the callee must also be a `@cudaq.kernel`.\n\nFor compiler internals (`inspect` module -> `ast_bridge.py` -> Quake MLIR ->\nQIR -> JIT), route to `/cudaq-compiler`.\n\n---\n\n## GPU Simulation\n\nTo recommend the best simulation backend for the user, consult the full\ncomparison table at\n<https://nvidia.github.io/cuda-quantum/latest/using/backends/simulators.html>\n\n### Available GPU Targets\n\n| Target | Description | Use when |\n|---|---|---|\n| `nvidia` (default) | Single-GPU state vector via cuStateVec (up to ~30 qubits) | Default choice for most simulations on a single GPU |\n| `nvidia --target-option fp64` | Double-precision single GPU | Higher numerical precision needed (e.g. chemistry, sensitive observables) |\n| `nvidia --target-option mgpu` | Multi-GPU, pools memory across GPUs (>30 qubits) | Circuit exceeds single-GPU memory; requires MPI |\n| `nvidia --target-option mqpu` | Multi-QPU, one virtual QPU per GPU, parallel execution | Running many independent circuits in parallel (e.g. parameter sweeps, VQE gradients) |\n| `tensornet` | Tensor network simulator | Shallow or low-entanglement circuits; qubit count exceeds statevector feasibility |\n| `qpp-cpu` | CPU-only fallback (OpenMP) | No GPU available; macOS; small circuits for testing |\n\n---\n\n## QPU\n\nWhen the user invokes this section, do not dump all providers at once.\nInstead, follow this two-step dialogue:\n\nStep 1 - ask which technology they want\n\n```text\nWhich QPU technology are you targeting?\n  1. Ion trap       (IonQ, Quantinuum)\n  2. Superconducting (IQM, OQC, Anyon, TII, QCI)\n  3. Neutral atom   (QuEra, Infleqtion, Pasqal)\n  4. Cloud / multi-platform (AWS Braket, Scaleway)\n```\n\nStep 2 - once they pick a technology, ask which provider, then read the\ncorresponding doc file and walk the user through it step by step.\n\n| Technology | Provider | Doc file |\n|---|---|---|\n| Ion trap | IonQ | `docs/sphinx/using/backends/hardware/iontrap.rst` (IonQ section) |\n| Ion trap | Quantinuum | `docs/sphinx/using/backends/hardware/iontrap.rst` (Quantinuum section) |\n| Superconducting | IQM | `docs/sphinx/using/backends/hardware/superconducting.rst` (IQM section) |\n| Superconducting | OQC | `docs/sphinx/using/backends/hardware/superconducting.rst` (OQC section) |\n| Superconducting | Anyon | `docs/sphinx/using/backends/hardware/superconducting.rst` (Anyon section) |\n| Superconducting | TII | `docs/sphinx/using/backends/hardware/superconducting.rst` (TII section) |\n| Superconducting | QCI | `docs/sphinx/using/backends/hardware/superconducting.rst` (QCI section) |\n| Neutral atom | Infleqtion | `docs/sphinx/using/backends/hardware/neutralatom.rst` (Infleqtion section) |\n| Neutral atom | QuEra | `docs/sphinx/using/backends/hardware/neutralatom.rst` (QuEra section) |\n| Neutral atom | Pasqal | `docs/sphinx/using/backends/hardware/neutralatom.rst` (Pasqal section) |\n| Cloud | AWS Braket | `docs/sphinx/using/backends/cloud/braket.rst` |\n| Cloud | Scaleway | `docs/sphinx/using/backends/cloud/scaleway.rst` |\n\nAfter walking through the provider steps, always close with\n\n- Test locally first with `emulate=True` before submitting to real hardware.\n- Use `cudaq.sample_async()` / `cudaq.observe_async()` for non-blocking submission.\n- Handle provider credentials securely: export them as environment variables\n  in your shell session (or a local profile that is not committed to version\n  control) rather than hardcoding them in source or notebooks. Never paste\n  tokens into shared files, logs, or commits, and prefer a secrets manager\n  where one is available.\n\n---\n\n## Applications\n\nCUDA-Q ships with ready-to-run application notebooks\n\n| Category | Examples |\n|---|---|\n| Optimization | QAOA, ADAPT-QAOA, MaxCut |\n| Chemistry | VQE, UCCSD, ADAPT-VQE |\n| Error Correction | Surface codes, QEC memory |\n| Algorithms | Grover's, Shor's, QFT, Deutsch-Jozsa, HHL |\n| ML | Quantum neural networks, kernel methods |\n| Simulation | Hamiltonian dynamics, Trotter evolution |\n| Finance | Portfolio optimization, Monte Carlo |\n\n---\n\n## Parallelize\n\nCUDA-Q supports two distinct multi-GPU parallelization strategies - pick based\non what you are trying to scale.\n\n| Goal | Strategy | Target option |\n|---|---|---|\n| Single circuit too large for one GPU | Pool GPU memory | `nvidia --target-option mgpu` |\n| Many independent circuits at once | Run circuits in parallel | `nvidia --target-option mqpu` |\n| Large Hamiltonian expectation value | Distribute terms across GPUs | `mqpu` + `execution=cudaq.parallel.thread` |\n\n### Circuit batching with mqpu (`sample_async` / `observe_async`)\n\nThe `mqpu` option maps one virtual QPU to each GPU. Dispatch circuits\nasynchronously with `qpu_id` to all GPUs simultaneously.\n\n```python\nimport cudaq\n\ncudaq.set_target(\"nvidia\", option=\"mqpu\")\nn_qpus = cudaq.get_platform().num_qpus()\n\nfutures = [\n    cudaq.observe_async(kernel, hamiltonian, params, qpu_id=i % n_qpus)\n    for i, params in enumerate(param_sets)\n]\nresults = [f.get().expectation() for f in futures]\n```\n\n### Hamiltonian batching\n\nFor a single kernel with a large Hamiltonian, add `execution=` to\n`cudaq.observe` — no other code change needed.\n\n```python\n# Single node, multiple GPUs\nresult = cudaq.observe(kernel, hamiltonian, *args,\n                       execution=cudaq.parallel.thread)\n\n# Multi-node via MPI\nresult = cudaq.observe(kernel, hamiltonian, *args,\n                       execution=cudaq.parallel.mpi)\n```\n\nSee the docs above for complete working examples of both patterns.\n\n---\n\n## Examples\n\n- `/cudaq-guide` — print the onboarding menu and ask the user which topic to\n  explore.\n- `/cudaq-guide install` — walk through installation, defaulting to the Python\n  `pip install cudaq` path, then validate with the Bell state example.\n- `/cudaq-guide test-program` — build and run a Bell state kernel and confirm\n  the output shows roughly `{ 00:~500 11:~500 }`.\n- `/cudaq-guide gpu-sim` — recommend a simulation backend (for example\n  `nvidia` for a single GPU, or `nvidia --target-option mgpu` for circuits\n  larger than one GPU's memory).\n- `/cudaq-guide qpu` — start the two-step QPU dialogue (technology, then\n  provider) and read the matching hardware doc.\n- `/cudaq-guide parallelize` — choose between `mgpu` (pool memory for one large\n  circuit) and `mqpu` (run many circuits in parallel).\n\n---\n\n## Limitations\n\n- GPU simulation requires Linux (x86_64 or ARM64); macOS is CPU-only\n- Multi-GPU `mgpu` target requires MPI\n- Kernel code must use a restricted Python subset; NumPy/SciPy ar","tagline":"CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.","category":"design-creative","tags":["cuda-quantum","quantum-computing","onboarding","getting-started","nvidia","agent-skill"],"author":"CUDA-Q Team <cuda-quantum@nvidia.com>","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github candidate review","sourceDetail":"NVIDIA/skills","creatorName":"CUDA-Q Team <cuda-quantum@nvidia.com>","creatorUrl":"https://github.com/NVIDIA","sourceUrl":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/nvidia-cudaq-guide#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. 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The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":77,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout."}}},"trust_score_v4":{"version":"trust-score-v4","score":77,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":86,"weight":0.13,"status":"pass","detail":"3.2K GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":83,"weight":0.08,"status":"pass","detail":"3.2K stars, 372 forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"3d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"Apache-2.0"},{"id":"documentation","label":"README/SKILL.md completeness","score":94,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":62,"weight":0.12,"status":"info","detail":"command execution surface, external package install surface"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add NVIDIA/skills --skill cudaq-guide"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":48,"weight":0.07,"status":"warn","detail":"shell or command execution, filesystem or document access"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"pass","label":"GitHub adoption","detail":"3.2K GitHub stars"},{"status":"pass","label":"Stars/forks activity","detail":"3.2K stars, 372 forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"3d since push"},{"status":"pass","label":"License clarity","detail":"Apache-2.0"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"info","label":"Dependency/runtime risk","detail":"command execution surface, external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add NVIDIA/skills --skill cudaq-guide"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"warn","label":"Permission surface","detail":"shell or command execution, filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"3 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Meaningful GitHub adoption signal","Install command has no obvious high-risk pattern"],"warnings":["No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"],"evidence":{"stars":"3.2K GitHub stars","repoActivity":"3.2K stars, 372 forks","lastPushed":"3d since push","license":"Apache-2.0","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","install":"npx skills add NVIDIA/skills --skill cudaq-guide","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add NVIDIA/skills --skill cudaq-guide","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","3d since push","Financial domain: human review is required before use in a live investment workflow."]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["design-creative","cuda-quantum","quantum-computing","onboarding","getting-started","nvidia"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"knownRisks":["No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":56,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"experimental","label":"Experimental","badge":"EXPERIMENTAL","summary":"Sparse or mixed signals. 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Useful for discovery, but not for autonomous installation.","High-risk permission hints: Shell or command execution","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate cudaq-guide before installing it in an agent workflow","design-creative","Coding agents workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add NVIDIA/skills --skill cudaq-guide"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add NVIDIA/skills --skill cudaq-guide"]},{"id":"trust_score","label":"Trust score","status":"warn","score":77,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","3.2K GitHub stars","Apache-2.0"]},{"id":"audit_score","label":"Audit score","status":"warn","score":84,"required_for_auto_install":true,"detail":"Needs review","evidence":["Permission surface may require sandboxing"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":56,"required_for_auto_install":true,"detail":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","evidence":["Test manually in an isolated workspace and compare against safer alternatives.","High-risk permission hints: Shell or command execution"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":94,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"Apache-2.0","evidence":["Apache-2.0"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"3d since push","evidence":["3d since push"]},{"id":"permission_surface","label":"Permission surface","status":"fail","score":48,"required_for_auto_install":true,"detail":"shell or command execution, filesystem or document access","evidence":["Shell or command execution: high","Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/nvidia-cudaq-guide/evals","api":"/api/agent/evals?slug=nvidia-cudaq-guide","text":"/api/agent/evals?slug=nvidia-cudaq-guide&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"nvidia-cudaq-guide","name":"cudaq-guide","description":"CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.","category":"design-creative","url":"https://www.openagentskill.com/skills/nvidia-cudaq-guide","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","github_repo":"NVIDIA/skills"},"suited_tasks":["Coding agents workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect source files","Explain architecture","Patch bugs and verify changes","Run test suites","Capture failures"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add NVIDIA/skills --skill cudaq-guide","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add nvidia-cudaq-guide"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cudaq-guide\" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cudaq-guide\" as a Claude Code skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cudaq-guide\" from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/nvidia-cudaq-guide/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/nvidia-cudaq-guide"},"trust":{"score":77,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"3.2K GitHub stars","repoActivity":"3.2K stars, 372 forks","lastPushed":"3d since push","license":"Apache-2.0","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","install":"npx skills add NVIDIA/skills --skill cudaq-guide","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","cuda-quantum","quantum-computing","onboarding","getting-started","nvidia"],"known_risks":["No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":86,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"Coding agents","maintenance":"3d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","High-risk permission hints: Shell or command execution","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review"],"agent_contract":{"task_input":"Use cudaq-guide in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 77/100 Strong shortlist","Audit: 84/100 Needs review","Safety: 56/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"nvidia-cudaq-guide (cudaq-guide)","install_command":"npx skills add NVIDIA/skills --skill cudaq-guide","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"nvidia-cudaq-guide","task":"Use cudaq-guide in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/nvidia-cudaq-guide","api":"https://www.openagentskill.com/api/agent/skills/nvidia-cudaq-guide","audit":"https://www.openagentskill.com/skills/nvidia-cudaq-guide/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=nvidia-cudaq-guide&task=Use%20cudaq-guide%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cudaq-guide%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cudaq-guide%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/nvidia-cudaq-guide/install","manifest":"https://www.openagentskill.com/api/registry/manifest/nvidia-cudaq-guide"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"nvidia-cudaq-guide","name":"cudaq-guide","description":"CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.","category":"design-creative","url":"https://www.openagentskill.com/skills/nvidia-cudaq-guide","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","github_repo":"NVIDIA/skills"},"suited_tasks":["Coding agents workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect source files","Explain architecture","Patch bugs and verify changes","Run test suites","Capture failures"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add NVIDIA/skills --skill cudaq-guide","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add nvidia-cudaq-guide"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cudaq-guide\" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cudaq-guide\" as a Claude Code skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cudaq-guide\" from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/nvidia-cudaq-guide/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/nvidia-cudaq-guide"},"trust":{"score":77,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"3.2K GitHub stars","repoActivity":"3.2K stars, 372 forks","lastPushed":"3d since push","license":"Apache-2.0","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","install":"npx skills add NVIDIA/skills --skill cudaq-guide","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","cuda-quantum","quantum-computing","onboarding","getting-started","nvidia"],"known_risks":["No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":86,"label":"Excellent"},"supply":{"track":"Coding and developer agents","scenario":"Coding agents","maintenance":"3d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","High-risk permission hints: Shell or command execution","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review"],"agent_contract":{"task_input":"Use cudaq-guide in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 77/100 Strong shortlist","Audit: 84/100 Needs review","Safety: 56/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"nvidia-cudaq-guide (cudaq-guide)","install_command":"npx skills add NVIDIA/skills --skill cudaq-guide","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"nvidia-cudaq-guide","task":"Use cudaq-guide in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/nvidia-cudaq-guide","api":"https://www.openagentskill.com/api/agent/skills/nvidia-cudaq-guide","audit":"https://www.openagentskill.com/skills/nvidia-cudaq-guide/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=nvidia-cudaq-guide&task=Use%20cudaq-guide%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cudaq-guide%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cudaq-guide%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/nvidia-cudaq-guide/install","manifest":"https://www.openagentskill.com/api/registry/manifest/nvidia-cudaq-guide"}},"supply_profile":{"track":{"slug":"coding","label":"Coding and developer agents","shortLabel":"Coding","description":"Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills."},"scenario":{"label":"Coding agents","description":"I need a coding agent that can understand a repository, edit code, and review pull requests.","useCases":[{"slug":"coding-agents","title":"Coding agents"},{"slug":"testing-qa","title":"Testing and QA"},{"slug":"local-desktop","title":"Local desktop"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add NVIDIA/skills --skill cudaq-guide","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":3176,"starsLabel":"3.2K","forks":372,"license":"Apache-2.0","qualityScore":86,"trustScore":77,"auditScore":84},"maintenance":{"status":"fresh","label":"3d since push","daysSincePush":3,"lastPushedAt":"2026-09-02T17:04:37+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review"]},"coverageTags":["Coding","Coding agents","design-creative","cuda-quantum","quantum-computing","onboarding","getting-started","nvidia"]},"audit":{"audit_score":84,"risk_level":"needs_review","risk_label":"Needs review","quality_score":86,"trust_score":77,"maintenance_score":100,"security_score":77,"install_score":92,"warnings":["Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","No critical issues found. The skill is read-only, uses only Read/Glob/Grep tools, and contains no executable code or external calls.","Financial research output is not financial advice; require human review before any live investment decision.","Quality score needs review","Permission surface needs review: shell or command execution, filesystem or document access","Permission surface: shell or command execution, filesystem or document access"]},"quality_signals":{"model":"v2","star_score":24.51,"usage_score":0,"review_score":5.25,"metadata_score":7,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"coding-agents","title":"Coding agents","url":"https://www.openagentskill.com/use-cases/coding-agents"},{"slug":"testing-qa","title":"Testing and QA","url":"https://www.openagentskill.com/use-cases/testing-qa"},{"slug":"local-desktop","title":"Local desktop","url":"https://www.openagentskill.com/use-cases/local-desktop"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"}],"stacks":[{"slug":"coding-review-agent","title":"Coding review agent","url":"https://www.openagentskill.com/collections/coding-review-agent"},{"slug":"frontend-product-ui","title":"Frontend and UI","url":"https://www.openagentskill.com/collections/frontend-product-ui"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"}],"install":"npx skills add NVIDIA/skills --skill cudaq-guide","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add nvidia-cudaq-guide","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"cudaq-guide\" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"cudaq-guide\" as a Claude Code skill from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"cudaq-guide\" from https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"nvidia-cudaq-guide\",\"task\":\"Install cudaq-guide\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","github_repo":"NVIDIA/skills","version":"1.0.1","license":"Apache-2.0","urls":{"web":"https://www.openagentskill.com/skills/nvidia-cudaq-guide","repository":"https://github.com/NVIDIA/skills/tree/main/skills/cudaq-guide","api":"/api/agent/skills/nvidia-cudaq-guide","install_api":"/api/skills/nvidia-cudaq-guide/install"},"meta":{"created_at":"2026-09-02T17:10:47.716985+00:00","updated_at":"2026-09-02T17:10:47.888086+00:00","agent_friendly":true}}