gpu-resource-management

gpu-resource-management is a skill for Claude Code from aws-samples/sample-oh-my-aidlcops. It costs 76 tokens per session (1,420 once invoked), scanned A, original, MIT-0.

Instructions for managing GPU resources on Amazon EKS, a managed Kubernetes service. They cover automatic node provisioning, scaling workloads to zero, and dividing GPUs into smaller partitions.

In plain words
What is it for?
Designing EKS node pools, configuring spot and on-demand GPU capacity, scaling GPU workloads, partitioning GPUs with MIG, and scheduling workloads with topology awareness.
Why use it?
They help match GPU capacity to workload demand while supporting different GPU types and scheduling constraints.

Skill for Claude Code ✓ vendor

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the ai-infra plugin — 6 skills, 2 commands, 4 agents shipped together

Good fit Designing EKS node pools, configuring spot and on-demand GPU capacity, scaling GPU workloads, partitioning GPUs with MIG, and scheduling workloads with topology awareness.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management
About the project

sample-oh-my-aidlcops is a plugin marketplace for Claude Code and Kiro that packages practices for managing the AWS AI-Driven Development Lifecycle, including design correctness and agent safety. It is for teams using agents to develop and operate AWS systems with approval checkpoints. Its catalogue contains the marketplace's plugins, skills, agents, and commands.

aws-samples/sample-oh-my-aidlcops · 22 stars · on GitHub · aws-samples.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add aws-samples/sample-oh-my-aidlcops --skill gpu-resource-management
Clone the repo
git clone --depth 1 https://github.com/aws-samples/sample-oh-my-aidlcops

Made for: Claude Code.

Or install ai-infra, the plugin that ships this one along with the rest of its 6 skills, 2 commands, 4 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gpu-resource-management

README.md
[![agentmods](https://agentmods.dev/badge/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management/github.svg)](https://agentmods.dev/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management)
Your own site
<a href="https://agentmods.dev/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gpu-resource-management

Your own site · 80×15
<a href="https://agentmods.dev/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-oh-my-aidlcops/gpu-resource-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,420 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.01420
Opus 5.5 $0.00030 $0.00568
Sonnet 5.5 $0.00015 $0.00284
Haiku 4.5 $0.00008 $0.00142

Measured 1mo ago against content hash 010dec003240, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

gpu-resource-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/ai-infra/skills/gpu-resource-management/SKILL.md · 141 lines

The source is not reproduced here

Licensed MIT-0

The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 141 lines · 76 tokens per session scan A 010dec003240

Subscribe to this mod's changes

gpu-resource-management is a skill published in the GitHub repository aws-samples/sample-oh-my-aidlcops (22 stars, last pushed yesterday), licensed MIT-0. It adds 76 tokens to every session and 1,420 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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