NVIDIA agent skills are portable instruction sets that teach AI agents how to use NVIDIA CUDA-X libraries, AI Blueprints, and platform tools correctly. NVIDIA-verified skills published in the NVIDIA/skills GitHub repo are: Cataloged and synced daily from the NVIDIA product team that owns it
Scanned for software and agent-native risks before publication
Signed with a detached skill.oms.sig that can be verified post-download
Documented with a skill card describing ownership, dependencies, limitations, and verification status Evaluation is the next layer. It will add standardized quality metri
An NVIDIA-verified skill starts in a source repository owned by a product team. From there, it moves through a publishing flow that can include both human review and automated policy checks, followed by scanning, evaluation, generation of the skill card, signing, cataloging, and synchronization into the public catalog. Each verified skill is paired with a skill card, a machine-readable trust record that explains the following: What the skill does
Who built the skill
How is the skill licensed
What are the skill dependencies
What are the known technical limitations, risks, and mitigatio
How does cryptographic signing add verifiable provenance for agent skills?
NVIDIA is publicly experimenting with cryptographic signing for agent skills as part of a broader validation roadmap for enterprise-scale deployment. The goal is to make it easier for developers to trust the skills NVIDIA publishes and replicate the same validation and deployment pipeline across environments. The signature covers every file and subdirectory in the skill directory, giving developers a concrete way to verify that the downloaded skill is authentic and unchanged. This is what distinguishes verified skills from assets that are merely associated with a known publisher or listed in a
The AI-Q skill enables Claude Code, Codex, or other general-purpose agents to submit a research task to a running AI-Q server and receive a well-formatted, detailed report with citations. The skill includes a SKILL.md file that tells the harness how to use AI-Q, plus a helper script that manages request routing, job submission, polling, and result retrieval. A skill can mean different things in agent workflows. Agent skills guide the harness, the NVIDIA NeMo Agent Toolkit helps define reusable tool functions, and the AI-Q Agent Skill exposes the full research pipeline—including intent classifi