mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
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a680d0472b
Adds a Claude Code plugin structure that exposes each NVIDIA DGX Spark
playbook as a triggerable skill, with an index skill ('dgx-spark') that
routes users to the right leaf based on intent and encodes the
relationship graph between playbooks (prerequisites, alternatives,
composes-with, upgrade paths).
Structure:
- overrides/*.md hand-curated frontmatter + Related sections
- scripts/generate.mjs zero-dep Node generator: nvidia + overrides → skills
- scripts/install.sh symlinks skills into ~/.claude/skills (--plugin mode available)
- skills/ committed, browsable, installable without Node
- .github/workflows/ auto-regenerates skills/ when playbooks/overrides change
Initial curated leaves: ollama, open-webui, vllm, connect-to-your-spark.
Remaining 37 leaves use generator fallback (title + tagline + summary
extracted from README) and can be curated incrementally via overrides/.
19 lines
1.6 KiB
Markdown
19 lines
1.6 KiB
Markdown
---
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name: dgx-spark-isaac
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description: Build Isaac Sim and Isaac Lab from source for Spark — on NVIDIA DGX Spark. Use when setting up isaac on Spark hardware.
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---
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<!-- GENERATED:BEGIN from nvidia/isaac/README.md -->
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# Install and Use Isaac Sim and Isaac Lab
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> Build Isaac Sim and Isaac Lab from source for Spark
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Isaac Sim is a robotics simulation platform built on NVIDIA Omniverse that enables photorealistic, physically accurate simulations of robots and environments. It provides a comprehensive toolkit for robotics development, including physics simulation, sensor simulation, and visualization capabilities. Isaac Lab is a reinforcement learning framework built on top of Isaac Sim, designed for training and deploying RL policies for robotics applications.
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Isaac Sim uses GPU-accelerated physics simulation to enable fast, realistic robot simulations that can run faster than real-time. Isaac Lab extends this with pre-built RL environments, training scripts, and evaluation tools for common robotics tasks like locomotion, manipulation, and navigation. Together, they provide an end-to-end solution for developing, training, and testing robotics applications entirely in simulation before deploying to real hardware.
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**Outcome**: You'll build Isaac Sim from source on your NVIDIA DGX Spark device and set up Isaac Lab for reinforcement learning experiments. This includes compiling the Isaac Sim engine, configuring the development environment, and running a sample RL training task to verify the installation.
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**Full playbook**: `/Users/jkneen/Documents/GitHub/dgx-spark-playbooks/nvidia/isaac/README.md`
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<!-- GENERATED:END -->
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