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azure-data-science-vm（Azure 数据 science VM）

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组，区分本地测试与生产操作；涉及删除资源、重启服务、修改网络或权限配置时，应先确认影响范围。

总安装

840

周安装

GitHub Stars

521

下载量

264

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

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：azure-data-science-vm（Azure 数据 science VM）
来源仓库：https://github.com/microsoftdocs/agent-skills
仓库路径：skills/azure-data-science-vm
安装命令：
npx skills add https://github.com/microsoftdocs/agent-skills --skill azure-data-science-vm
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/microsoftdocs/agent-skills --skill azure-data-science-vm

简介

为 Azure 数据科学虚拟机提供预装工具链配置指南。

适用于机器学习实验、模型训练与可视化分析环境搭建。
内置 Jupyter、TensorFlow 与 RStudio 等主流框架支持。
Agent 应按分类索引定位 troubleshooting 或 deployment 章节。
建议定期更新系统补丁并保持 CUDA 驱动版本兼容。

SKILL.md

Azure Data Science Virtual Machines Skill

This skill provides expert guidance for Azure Data Science Virtual Machines. Covers troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file

IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide

This skill requires network access to fetch documentation content:

Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

Category	Lines	Description
Troubleshooting	L35-L39	Diagnosing and resolving common Azure Data Science VM issues, including VM creation, package/environment errors, Jupyter access, GPU/driver problems, and performance or connectivity failures.
Decision Making	L40-L44	Guidance for upgrading Azure Data Science VMs from Ubuntu 18.04 to 20.04, including migration steps, compatibility considerations, and preserving tools/configurations.
Architecture & Design Patterns	L45-L50	Designing scalable DSVM-based analytics environments, including architecture patterns, shared VM pools, team workflows, and resource management for data science teams.
Security	L51-L56	Managing identities and credentials for Azure DSVMs, including shared identity setup, managed identities, and securing secrets with Azure Key Vault.
Configuration	L57-L69	Details of all preinstalled tools, frameworks, languages, and images on Azure DSVMs, including ML/deep learning, data ingestion, dev/productivity tools, and release/version info.
Integrations & Coding Patterns	L70-L74	Using MLflow on Azure DSVMs to track experiments, log metrics/artifacts, and integrate runs with Azure Machine Learning for centralized experiment management
Deployment	L75-L79	How to deploy Azure Data Science VMs using infrastructure-as-code, including Bicep and ARM templates, parameters, and configuration best practices.

Troubleshooting

Topic	URL
Troubleshoot known issues on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/reference-known-issues?view=azureml-api-2

Decision Making

Topic	URL
Migrate DSVM from Ubuntu 18.04 to 20.04	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/ubuntu-upgrade?view=azureml-api-2

Architecture & Design Patterns

Topic	URL
Design team analytics environments with DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-enterprise-overview?view=azureml-api-2
Architect shared DSVM pools for analytics teams	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-pools?view=azureml-api-2

Security

Topic	URL
Configure common identity for multiple DSVMs	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-common-identity?view=azureml-api-2
Secure DSVM credentials with managed identities and Key Vault	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-secure-access-keys?view=azureml-api-2

Configuration

Topic	URL
Use preinstalled ML tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-data-science?view=azureml-api-2
Check deep learning frameworks on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-deep-learning-frameworks?view=azureml-api-2
Identify development tools available on DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-development?view=azureml-api-2
Use data ingestion tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-ingestion?view=azureml-api-2
Review programming languages preinstalled on DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-languages?view=azureml-api-2
Leverage productivity tools on Azure DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tools-productivity?view=azureml-api-2
Reference tools installed on Ubuntu DSVM	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/reference-ubuntu-vm?view=azureml-api-2
Review Azure DSVM release changes and versions	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/release-notes?view=azureml-api-2
Review preinstalled tools on Azure DSVM images	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/tools-included?view=azureml-api-2

Integrations & Coding Patterns

Topic	URL
Track DSVM experiments with MLflow and Azure ML	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/how-to-track-experiments?view=azureml-api-2

Deployment

Topic	URL
Deploy Azure DSVM using Bicep templates	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tutorial-bicep?view=azureml-api-2
Deploy Azure DSVM with ARM templates	https://learn.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-tutorial-resource-manager?view=azureml-api-2

适合场景

Azure 资源规划

云服务升级

基础设施检查

企业云环境自动化

能力概览

能力 1

整理 Azure 服务操作流程

能力 2

提示 CLI/MCP 前置条件

能力 3

辅助云资源检查和规划

能力 4

保留官方服务来源线索

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

34.84%

按下载量换算92

Claude

31.5%

按下载量换算83

Cursor

16.06%

按下载量换算42

Gemini CLI

8.89%

按下载量换算23

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API，使用前需要确认账号、额度、数据发送范围和服务条款。

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

GitHub 仓库

github.com

/microsoftdocs/agent-skills

SKILL.md 来源

github.com

/microsoftdocs/agent-skills/tree/main/skills/azure-data-science-vm

skills-sh

skills.sh

/microsoftdocs/agent-skills/azure-data-science-vm

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