Inspect and guide NVIDIA DGX Station GB300 development using the local dgx-assist CLI and pinned NVIDIA playbooks. Use for general Station platform questions, Software 1.0 or 2.0 compatibility, GB300 or RTX GPU selection, UUID ordering, mixed ATS/HMM coherency, CDMM, general containers, CDI, CUDA visibility, or vsloshd power-sloshing behavior. Do not use for vLLM or SGLang container selection or tuning, serving a named model, changing MIG, or troubleshooting a reported failure when the dedicated Station skill applies.
npx skills add https://github.com/NVIDIA/dgx-spark-playbooks --skill dgx-station
Ground every Station-specific answer in current host evidence and a retrieved NVIDIA passage.
scripts/dgx-assist system inspect --json.compatibility.profile_id, support_level, and capabilities; do not branch on a version prefix.scripts/dgx-assist playbook search "<query>" --json.true. If it is false, explain the profile restriction separately from relevant read-only guidance.version_specific_guidance is false or retrieval abstains, say no applicable version-specific passage was found and avoid inventing a platform command.nvidia-smi index is a CUDA ordinal.mixed_coherency_service is true, inspect mixed-coherency-gpu-select.service, its generated environment, and container exposure separately.dynamic_power_sloshing is true, inspect vsloshd. Always inspect observed caps and never propose an ad hoc power-cap change.Read references/platform.md when interpreting coherency, container ordering, power, memory placement, or qualification evidence. Read references/software-compatibility.md before applying version-specific guidance. Read references/sources.md when guidance may come from the Development Guide or bring-up guide. Read references/cli.md for command and JSON details.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take nvidia/dgx-station from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.