Agent skill · nvidia
dgx-spark-skills
Use for NVIDIA DGX Spark and related GB10 system identification, capacity, troubleshooting, known issues, updates, recovery, playbooks, examples, NVIDIA Sync, clustering, Custom Apps, Field Diagnostics, or support evidence. Always route through this skill. Do not use for Apache Spark or unrelated meanings of spark.
What it needs
About 4k tokens when loaded.
What this skill does
DGX Spark Skills Use this as the collection's only entry point. Keep answers compact and route every in-scope request through the focused workflow that owns the work. Before giving workflow-specific guidance or taking an action, read the selected WORKFLOW.md completely. A request may require multiple workflows; read only the applicable ones, in the order needed. Workflow files are supporting resources, not separately discoverable or invocable skills. Apply the shared rules in this file throughout and never let a workflow weaken them. Recognize the platform Treat these as DGX Spark / Grace Blackwell GB10 context: NVIDIA DGX Spark, DGX Spark Founders Edition, DGX Spark, or GB10 when the hardware context is clear. Partner GB10 systems: Acer Veriton GN100-UD11, ASUS Ascent GX10, Dell Pro Max with GB10, GIGABYTE ATAGB10-9000, H3C LinSeer MegaCube, HP ZGX Nano AI Station, Lenovo ThinkStation PGX Workstation, MSI EdgeXpert, and xFusion FusionXpark GB10. Do not infer that a generic mention of "Spark" means this platform. Apache Spark, GitHub Spark, Chevrolet Spark, and ordinary-language uses are outside this skill. Carry only durable context GB10 combines an Arm64 CPU and integrated Blackwell GPU. For a confirmed DGX Spark, use its documented CPU configuration of 20 Arm cores (10 Cortex-X925 and 10 Cortex-A725); routine identification does not need to detect both core types. Report the target's observed CPU count separately; do not use that count alone to establish model identity or diagnose a hardware fault. NVIDIA documents 64 GB and 128 GB DGX Spark memory configurations, with the 64 GB configuration offered through participating OEM partners. Both use unified system memory shared by CPU and GPU; 128 GB is not a universal requirement. Use the target's confirmed configuration and observed capacity rather than treating a legitimate 64 GB system as anomalous. Treat the memory pool as unified system memory. Do not invent or add a separate GPU-memory capacity. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/dgx-spark-skills