gpu-resource-optimizer
Optimize gpu resource optimizer operations. Auto-activating skill for ML Deployment. Triggers on: gpu resource optimizer, gpu resource optimizer Part of the ML Deployment skill category. Use when working with gpu resource optimizer functionality. Trigger with phrases like "gpu resource optimizer", "gpu optimizer", "gpu". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill gpu-resource-optimizer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Gpu Resource Optimizer ## Overview This skill provides automated assistance for gpu resource optimizer tasks within the ML Deployment domain. ## When to Use This skill activates automatically when you: - Mention "gpu resource optimizer" in your request - Ask about gpu resource optimizer patterns or best practices - Need help with machine learning deployment skills covering model serving, mlops p
What does the gpu-resource-optimizer skill do?
Optimize gpu resource optimizer operations. Auto-activating skill for ML Deployment. Triggers on: gpu resource optimizer, gpu resource optimizer Part of the ML Deployment skill category. Use when working with gpu resource optimizer functionality. Trigger with phrases like "gpu resource optimizer", "gpu optimizer", "gpu". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill gpu-resource-optimizer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.