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slurm-info-summaryslurm 信息摘要

Agent Skill

slurm-info-summary 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

186

周安装

8

GitHub Stars

1

下载量

65
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:slurm-info-summary(slurm 信息摘要)
来源仓库:https://github.com/kdkyum/slurm-skills
仓库路径:skills/slurm-info-summary
安装命令:
npx skills add https://github.com/kdkyum/slurm-skills --skill slurm-info-summary
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/kdkyum/slurm-skills --skill slurm-info-summary

简介

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息,整理代码变更状态。

  • 适合在需要围绕仓库状态、代码变更或协作事项进行整理的场景中使用。
  • 可结合来源仓库和原始 README 继续核验具体用法和功能细节。
  • 安装前建议确认权限范围和是否涉及网络请求或文件系统操作。
  • 维护状态不明时,建议先评估稳定性再投入生产使用。

SKILL.md

SLURM Info Summary

Collect SLURM cluster specs and save a polished, human-readable reference document.

Steps

  1. Check for existing doc: Look for ~/.claude/skills/slurm-info-summary/references/slurm-cluster-summary.md.
  2. If the doc already exists:

- Tell the user: "SLURM cluster summary already exists at ~/.claude/skills/slurm-info-summary/references/slurm-cluster-summary.md." - Read the file and display its content. - Do NOT re-run the script. Stop here.

  1. If the doc does NOT exist:

- Run ~/.claude/skills/slurm-info-summary/scripts/gather-slurm-info.sh and capture stdout. - Parse the raw output (structured with === SECTION === markers) and produce a polished markdown summary following the template below. - Write the summary to ~/.claude/skills/slurm-info-summary/references/slurm-cluster-summary.md. - Display the summary to the user. - Tell the user the file path where it was saved.

Output Template

Use the raw data to produce a summary that matches this structure and style exactly. Convert raw memory values from MB to human-readable GB/TB. Derive node types by grouping nodes with the same prefix (e.g. ravc, ravg, ravh, ravl).

# <ClusterName> Cluster Overview

> Auto-generated on <UTC timestamp> by `/slurm-info-summary`

All compute nodes use **<CPU model>** processors with **<sockets> sockets, <cores>/socket, <threads> threads/core = <total logical CPUs> CPUs** per node.

---

## Partitions

| Partition | Nodes | Node Type | Memory/Node | GPUs/Node | Max Walltime | Max Nodes/Job | Oversubscribe |
|-----------|-------|-----------|-------------|-----------|--------------|---------------|---------------|
| ... | ... | ... | ... | ... | ... | ... | ... |

---

## Node Types

| Prefix | Count | Memory | GPUs | Notes |
|--------|-------|--------|------|-------|
| ... | ... | ... | ... | ... |

---

## Key Partition Differences

- **`<partition_a>` vs `<partition_b>`**: <explain the difference concisely>
- ...

---

## QOS Limits (notable only)

| QOS | Max Nodes/Job | Max Running Jobs | Max Submit Jobs | Max Walltime |
|-----|---------------|------------------|-----------------|---------------|
| ... | ... | ... | ... | ... |

Only include QOS entries that have at least one non-empty limit.

---

## Usage Examples

Provide 5-7 ready-to-use `sbatch`/`srun` examples covering:
- Interactive session
- Single-node CPU job (small partition)
- Multi-node CPU job (general partition)
- Single-GPU shared job (gpu1 partition)
- Multi-node GPU exclusive job (gpu partition)
- Quick GPU dev/test (gpudev partition)
- High-memory node request (if available)

## Key Tips

- Bullet list of practical tips: billing weights, constraint flags, useful commands (`squeue`, `scancel`), etc.

Important

  • Do NOT output the raw script data to the user. Only output the polished summary.
  • Keep the summary concise but complete.
  • The "Node Availability" section from the script is point-in-time data — do NOT include it in the saved summary (it would be stale).
  • Physical cores vs logical CPUs: Nodes with hyperthreading have more logical CPUs than physical cores (e.g., 72 physical cores = 144 logical CPUs with 2 threads/core). SLURM's --cpus-per-task counts physical cores. When describing per-GPU resource limits for shared partitions, always state the value in physical cores and note the logical CPU count parenthetically. For example: "18 physical cores (36 logical CPUs) and 125 GB memory per GPU".

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.98%
按下载量换算22

Claude

29.71%
按下载量换算19

Cursor

19.97%
按下载量换算13

Gemini CLI

9.98%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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