Agent Skill
Spark Memory Thermal Ops skill
spark-memory-thermal-opswshobson/agentsplugins/dgx-spark-ops/skills/spark-memory-thermal-ops/SKILL.md
Manage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.
always on
59 tokname + description
once used
1,975 tokSKILL.md body
bundled files
21 scripts
repo stars
42kGitHub
Install the Spark Memory Thermal Ops skill
Skills CLI (Claude Code, Codex, Cursor and others)
npx skills add https://github.com/wshobson/agents --skill spark-memory-thermal-ops
Claude Code, by hand (all projects)
git clone --depth 1 https://github.com/wshobson/agents.git /tmp/agents mkdir -p ~/.claude/skills cp -R /tmp/agents/plugins/dgx-spark-ops/skills/spark-memory-thermal-ops ~/.claude/skills/spark-memory-thermal-ops
For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.
What it costs your context
Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.
| When | What loads | Cost |
|---|---|---|
| Every session | Name and description | 59 tok |
| When the agent uses it | The SKILL.md instructions | 1,975 tok |
| Only if opened | 2 bundled files (5 KB) | varies |
Until it is used, spark-memory-thermal-ops costs about 23× less than the median MCP server we measured (1,362 tokens on every turn). Installing all 150 skills from wshobson/agents would load 7,688 tokens of descriptions. Skills vs MCP study
Checks
- Ships scripts the agent can run. Read them before installing.
Checked 2026-10-22 · method
What's inside
The headings of its SKILL.md. Read the full file on GitHub.
- Spark Memory & Thermal Ops
- Common Issues Quick Reference
- When to Use This Skill
- UMA Memory Model
- Planning Sequence
- Example: Sizing a 70B QLoRA Run
- The OOM Ladder
- Thermal Monitoring
- Concurrent Workloads
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