mcpbeat Sign in

Dgx Station Agent Skill

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.

3k tokens
context cost
the whole folder, loaded on every use
7
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1211
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/NVIDIA/dgx-spark-playbooks --skill dgx-station

What comes with it

9 268 bytes besides the instruction
agents/openai.yaml
references/cli.md
references/platform.md
references/software-compatibility.md
references/sources.md
scripts/dgx-assist

The instruction itself

3 sections, as written by the author

DGX Station

Ground every Station-specific answer in current host evidence and a retrieved NVIDIA passage.

Workflow

  • Run scripts/dgx-assist system inspect --json.
  • Read references/software-compatibility.md. Use compatibility.profile_id, support_level, and capabilities; do not branch on a version prefix.
  • Form a narrow playbook query from the user's question and run scripts/dgx-assist playbook search "<query>" --json.
  • Apply the source-precedence rules in references/sources.md. Use only passages applicable to the detected profile. Cite their URL, heading, line span, source commit, and source-file digest.
  • On the Software 1.0 capability-scoped profile, provide the supported inspection, diagnostics, compatibility guidance, and exact recipes qualified for that profile. Do not treat an absent Software 2.0-only service as a fault.
  • Before any platform action, require its named capability to be true. If it is false, explain the profile restriction separately from relevant read-only guidance.
  • If version_specific_guidance is false or retrieval abstains, say no applicable version-specific passage was found and avoid inventing a platform command.
  • Answer from the combined profile and applicable passage. Label unknown evidence as unknown.

Safety requirements

  • Before any mutating action, display the exact command to be run and obtain explicit user approval immediately before executing it. Never batch approvals or carry one forward to a later action.
  • Never assume an nvidia-smi index is a CUDA ordinal.
  • Use GPU UUIDs for every proposed launch. When multiple GPUs are deliberately visible, place the GB300 UUID first.
  • Do not apply either legacy or Software 2.0 mixed-device behavior without checking the detected profile and observed ATS/HMM state.
  • Do not tell the user to install or operate Fabric Manager as a normal Station requirement.
  • When mixed_coherency_service is true, inspect mixed-coherency-gpu-select.service, its generated environment, and container exposure separately.
  • When dynamic_power_sloshing is true, inspect vsloshd. Always inspect observed caps and never propose an ad hoc power-cap change.
  • Never install or change the driver, kernel, OS, firmware, or packages.
  • Never display credential values.

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.

Other skills for the same job

different authors, same section of the catalogue
MCP Builder
by anthropics
vendor ×13

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).

30k tokens scripts
Changelog Generator
by frostant
×9

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.

774 tokens
Finishing A Development Branch
by ZhanlinCui
×7

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

1k tokens
MCP Builder
by JayZeeDesign
×7

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).

37k tokens scripts
Vercel React Native Skills
by vercel-labs
vendor ×6

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.

39k tokens
Vercel React Best Practices
by ratacat
×5

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.

34k tokens
Next Best Practices
by vercel-labs
vendor ×4

Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling

20k tokens
Using Git Worktrees
by ZhanlinCui
×4

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

1k tokens

How to use it

Copy the folder

Take nvidia/dgx-station from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.