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/.
1.8 KiB
| name | description |
|---|---|
| dgx-spark-openshell | Run OpenClaw with local models in an NVIDIA OpenShell sandbox on DGX Spark — on NVIDIA DGX Spark. Use when setting up openshell on Spark hardware. |
Secure Long Running AI Agents with OpenShell on DGX Spark
Run OpenClaw with local models in an NVIDIA OpenShell sandbox on DGX Spark
OpenClaw is a local-first AI agent that runs on your machine, combining memory, file access, tool use, and community skills into a persistent assistant. Running it directly on your system means the agent can access your files, credentials, and network—creating real security risks.
NVIDIA OpenShell solves this problem. It is an open-source sandbox runtime that wraps the agent in kernel-level isolation with declarative YAML policies. OpenShell controls what the agent can read on disk, which network endpoints it can reach, and what privileges it has—without disabling the capabilities that make the agent useful.
By combining OpenClaw with OpenShell on DGX Spark, you get the full power of a local AI agent backed by 128GB of unified memory for large models, while enforcing explicit controls over filesystem access, network egress, and credential handling.
Notice & Disclaimers
Quick Start Safety Check
Outcome: You will install the OpenShell CLI (openshell), deploy a gateway on your DGX Spark, and launch OpenClaw inside a sandboxed environment using the pre-built OpenClaw community sandbox. The sandbox enforces filesystem, network, and process isolation by default. You will also configure local inference routing so OpenClaw uses a model running on your Spark without needing external API keys.
Full playbook: /Users/jkneen/Documents/GitHub/dgx-spark-playbooks/nvidia/openshell/README.md