azure-ai-services（Azure AI services 部署） Skills下载安装命令和教程

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-ai-services（Azure AI services 部署）
来源仓库：https://github.com/microsoftdocs/agent-skills
仓库路径：skills/azure-ai-services
安装命令：
npx skills add https://github.com/microsoftdocs/agent-skills --skill azure-ai-services
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-ai-services

简介

azure-ai-services 提供 Azure AI 服务的综合指南，涵盖配置、安全和集成。

适用于 Codex、Claude、Cursor、Gemini CLI 中决策服务选型与部署方案。
支持本地快速参考和远程文档查询，按类别读取详细内容。
建议结合业务需求选择服务区域，确保合规和低延迟。
操作前应验证 API 密钥权限和服务可用性，避免调用失败。

SKILL.md

Azure AI services Skill

This skill provides expert guidance for Azure AI services. Covers troubleshooting, best practices, decision making, limits & quotas, 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	L36-L40	Diagnosing and fixing common Content Understanding issues, including model errors, data ingestion problems, configuration mistakes, and troubleshooting steps for failed analyses.
Best Practices	L41-L46	Best practices for Azure AI Content Understanding: designing extraction workflows, tuning models, improving document parsing accuracy, and handling complex or low‑quality documents.
Decision Making	L47-L56	Guidance on choosing pricing tiers and tools (Foundry vs Content Understanding vs Document Intelligence/LLMs), standard vs pro modes, migration steps, and estimating Content Understanding costs.
Limits & Quotas	L57-L64	Rate limits, quotas, and scaling for Foundry and Content Moderator/Understanding: autoscale strategies, image/term list limits, and how to stay within service quotas.
Security	L65-L80	Securing Azure AI/Foundry: auth (Entra, keys, Key Vault), encryption (CMK, data-at-rest), DLP for outbound calls, VNet rules, policy-based governance, and secure analyzer access.
Configuration	L81-L98	Configuring Foundry endpoints, credentials, containers, logging, and Content Understanding analyzers (classification, layout, audiovisual), routing, outputs, and resource recovery/purge.
Integrations & Coding Patterns	L99-L108	Using Azure Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, custom term lists, and building custom multimodal analyzers and workflows.
Deployment	L109-L117	How to deploy and run Foundry-based Azure AI containers (single/multiple, ACI, disconnected), map analyzers to deployments, and automate setup with ARM templates.

Troubleshooting

Topic	URL
Resolve common issues with Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/faq

Best Practices

Topic	URL
Apply best practices for Content Understanding workloads	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices
Improve Content Understanding document extraction quality	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement

Decision Making

Topic	URL
Choose and use Foundry commitment tier pricing	https://learn.microsoft.com/en-us/azure/ai-services/commitment-tier
Choose between Content Understanding, Document Intelligence, and LLMs	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool
Choose between standard and pro modes in Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes
Choose between Foundry and Content Understanding Studio	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio
Migrate Content Understanding analyzers from preview to GA	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga
Estimate and plan costs for Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer

Limits & Quotas

Topic	URL
Use autoscale to increase Foundry rate limits	https://learn.microsoft.com/en-us/azure/ai-services/autoscale
Use Content Moderator image lists within quota limits	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet
Understand Content Moderator image and term list limits	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet
Review Content Understanding service quotas and limits	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits

Security

Topic	URL
Configure authentication for Foundry Tools requests	https://learn.microsoft.com/en-us/azure/ai-services/authentication
Configure data loss prevention for Foundry outbound calls	https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-data-loss-prevention
Secure Foundry resources with virtual network rules	https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-virtual-networks
Understand Content Moderator data-at-rest encryption behavior	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/encrypt-data-at-rest
Configure secure access for Content Understanding analyzers	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications
Enforce Entra-only auth by disabling local keys	https://learn.microsoft.com/en-us/azure/ai-services/disable-local-auth
Configure customer-managed encryption keys for Foundry	https://learn.microsoft.com/en-us/azure/ai-services/encryption/cognitive-services-encryption-keys-portal
Use built-in Azure Policies for Foundry governance	https://learn.microsoft.com/en-us/azure/ai-services/policy-reference
Rotate Foundry API keys without downtime	https://learn.microsoft.com/en-us/azure/ai-services/rotate-keys
Apply Azure Policy compliance controls to Foundry	https://learn.microsoft.com/en-us/azure/ai-services/security-controls-policy
Apply security features for Foundry Tools resources	https://learn.microsoft.com/en-us/azure/ai-services/security-features
Secure Foundry applications using Azure Key Vault	https://learn.microsoft.com/en-us/azure/ai-services/use-key-vault

Configuration

Topic	URL
Configure custom subdomains for Foundry endpoints	https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-custom-subdomains
Use environment variables for Foundry credentials	https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-environment-variables
Create reusable Azure AI container images with presets	https://learn.microsoft.com/en-us/azure/ai-services/containers/container-reuse-recipe
Configure Content Understanding analyzers and parameters	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference
Configure classification and splitting in Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/classifier
Use and customize Content Understanding prebuilt analyzers	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers
Configure document layout and data extraction with Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements
Interpret Content Understanding document Markdown output	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown
Configure classification and routing in Content Understanding Studio	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/classification-content-understanding-studio
Copy Content Understanding custom analyzers across resources	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/copy-analyzers
Configure audiovisual analysis for audio and video inputs	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/elements
Interpret audiovisual Markdown output from Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/markdown
Configure diagnostic logging for Foundry resources	https://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging
Recover or purge deleted Foundry resources	https://learn.microsoft.com/en-us/azure/ai-services/recover-purge-resources

Integrations & Coding Patterns

Topic	URL
Reference for Azure Content Moderator REST APIs	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference
Call Content Moderator image moderation APIs	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api
Use custom term lists with Content Moderator.NET SDK	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/term-lists-quickstart-dotnet
Use Content Moderator text moderation APIs	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/text-moderation-api
Integrate Content Moderator video scanning in.NET	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api
Create custom Content Understanding analyzers via REST	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer

Deployment

Topic	URL
Run Foundry Tools using Azure AI containers	https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-container-support
Deploy Foundry containers to Azure Container Instances	https://learn.microsoft.com/en-us/azure/ai-services/containers/azure-container-instance-recipe
Run Foundry containers in disconnected environments	https://learn.microsoft.com/en-us/azure/ai-services/containers/disconnected-containers
Deploy multiple Azure AI containers with Docker Compose	https://learn.microsoft.com/en-us/azure/ai-services/containers/docker-compose-recipe
Map Content Understanding analyzers to Foundry deployments	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments
Deploy Foundry resources using ARM templates	https://learn.microsoft.com/en-us/azure/ai-services/create-account-resource-manager-template

适合场景

01

企业搜索

02

语音转写和合成

03

文档智能处理

04

Azure AI 服务接入

能力概览

能力 1

接入 Azure AI Search

能力 2

支持语音转写和合成

能力 3

覆盖 OpenAI 与文档智能服务

能力 4

提供 MCP 或 SDK 使用线索

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

39.67%

按下载量换算31

Claude

29.84%

按下载量换算23

Cursor

19.55%

按下载量换算15

Gemini CLI

8.48%

按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

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-ai-services

skills-sh

skills.sh

/microsoftdocs/agent-skills/azure-ai-services

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下一个 Skill

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