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

简介

为 Azure AI Language 服务提供集成与配置指导，支持文本分析与自然语言处理。

适用于情感分析、实体识别、问答系统等智能应用的开发与部署。
提供多语言模型选择建议和 API 调用示例，便于快速对接业务逻辑。
调用付费接口前应确认资源配额，避免因超限导致服务不可用或产生额外费用。
azure-language-service 属于云服务类 Skill，可作为该场景下的辅助能力补充。

SKILL.md

Azure AI Language Skill

This skill provides expert guidance for Azure AI Language. Covers troubleshooting, best practices, decision making, architecture & design patterns, 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	L37-L42	Diagnosing and fixing common errors, low-accuracy results, and configuration issues in custom text classification and custom question answering projects in Azure AI Language.
Best Practices	L43-L60	Best practices for designing, labeling, and evaluating CLU, custom NER, text classification, and CQA projects, including multilingual handling, emojis, schemas, and autolabeling.
Decision Making	L61-L70	Guidance on choosing regions and resources, lifecycle policies, and migration paths from LUIS, QnA Maker, Text Analytics, and Language Studio to Azure Language and Microsoft Foundry
Architecture & Design Patterns	L71-L77	Architectural guidance for CLU and custom text classification: choosing CLU vs orchestration workflows, and designing regional backup, redundancy, and failover strategies.
Limits & Quotas	L78-L95	Limits, quotas, and language/region support for Azure AI Language features (CLU, NER, classification, PII, CQA), including data size, rate, throughput, and container request limits.
Security	L96-L105	Security for Azure AI Language: encryption at rest, customer-managed keys, RBAC, managed identities, SAS tokens, and network isolation/Private Link for CQA resources.
Configuration	L106-L133	Configuring Azure AI Language projects and containers: CLU, custom NER, text classification, CQA, sentiment, summarization, health, data formats, resources, and runtime settings.
Integrations & Coding Patterns	L134-L165	How to call Azure Language/CLU/Health/Summarization/CQA APIs and SDKs, wire them into bots, Power Automate, and Foundry, and correctly handle async, parameters, and outputs
Deployment	L166-L175	How to deploy and run Azure AI Language models (custom classification, NER, QnA, key phrases, language detection) across regions, containers, AKS, and migrate projects/resources.

Troubleshooting

Topic	URL
Resolve common issues in custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/faq
Troubleshoot common issues in custom question answering	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/troubleshooting

Best Practices

Topic	URL
Handle multilingual and emoji offsets in Language	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/multilingual-emoji-support
Apply CLU conversational design best practices	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/best-practices
Implement multilingual CLU projects effectively	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/multiple-languages
Design effective CLU project schemas	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/build-schema
Tag and label utterances for CLU training	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/tag-utterances
Interpret and stabilize CLU model evaluations	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/view-model-evaluation
Prepare data and design schemas for custom NER	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/design-schema
Label data effectively for custom NER training	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/tag-data
Use autolabeling to accelerate custom NER annotation	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/use-autolabeling
Prepare data and design schemas for text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/design-schema
Label data effectively for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/tag-data
Implement best practices for CQA project quality	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/best-practices
Apply project authoring best practices in CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/best-practices
Apply document format guidelines for CQA imports	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/reference/document-format-guidelines

Decision Making

Topic	URL
Understand Azure Language model lifecycle policies	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/model-lifecycle
Choose Azure regions for Language service features	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/regional-support
Migrate Azure Language Studio projects to Microsoft Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/migration-studio-to-foundry
Choose and manage Azure resources for CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/azure-resources
Decide migration from LUIS and QnA Maker to Azure Language	https://learn.microsoft.com/en-us/azure/ai-services/language-service/reference/migrate
Migrate Text Analytics apps to Azure Language API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/reference/migrate-language-service-latest

Architecture & Design Patterns

Topic	URL
Choose CLU vs orchestration workflow architecture	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/app-architecture
Design CLU regional backup and failover	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/fail-over
Design regional fail-over for custom text classification solutions	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/fail-over

Limits & Quotas

Topic	URL
Data size and rate limits for Azure Language features	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/data-limits
Train and manage CLU model jobs and limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/train-model
Apply CLU Docker container request limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/use-containers
Apply CLU data, region, and throughput limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/service-limits
Check language and region support for custom NER	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/language-support
Language support matrix for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/language-support
Review custom text classification data and rate limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/service-limits
Check language support for entity linking API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/language-support
Check language support for key phrase extraction	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/language-support
Review language detection supported languages and codes	https://learn.microsoft.com/en-us/azure/ai-services/language-service/language-detection/language-support
Review language support for Named Entity Recognition	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/language-support
Review orchestration workflow data and throughput limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/orchestration-workflow/service-limits
Apply PII container per-call character and document limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/how-to/use-containers
Service limits and boundaries for CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/limits

Security

Topic	URL
Understand Language service data-at-rest encryption	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/encryption-data-at-rest
Apply Azure RBAC to Azure Language resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/role-based-access-control
Use managed identities for Language Blob access	https://learn.microsoft.com/en-us/azure/ai-services/language-service/native-document-support/managed-identities
Create SAS tokens for Language Blob access	https://learn.microsoft.com/en-us/azure/ai-services/language-service/native-document-support/shared-access-signatures
Configure data-at-rest encryption and CMK for CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/encrypt-data-at-rest
Configure network isolation and Private Link for CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/network-isolation

Configuration

Topic	URL
Configure Azure resources for CLU fine-tuning	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/configure-azure-resources
Configure Azure Language service containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/configure-containers
Format data correctly for CLU projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/data-formats
Configure and use CLU None intent	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/none-intent
Use CLU prebuilt entity components	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/prebuilt-component-reference
Create custom NER projects and configure Azure resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/create-project
Configure and run Custom NER Docker containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/use-containers
Use required data formats for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/concepts/data-formats
Set up resources and create custom text classification projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/create-project
Configure and run training jobs for text classification models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/train-model
View and interpret evaluation metrics for text classification models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/view-model-evaluation
Map NER entity types and tags across API versions	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/concepts/ga-preview-mapping
Configure NER skill parameters and inference options	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/how-to/skill-parameters
Understand and configure confidence scores in CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/confidence-score
Enable diagnostics and run analytics for CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/analytics
Customize default answer behavior in CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/change-default-answer
Add and configure chitchat personas in CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/chit-chat
Configure Azure resources and permissions for CQA fine-tuning	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/configure-azure-resources
Configure smart URL refresh for CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/smart-url-refresh
Use supported markdown formats in CQA answers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/reference/markdown-format
Run Sentiment Analysis Docker containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/sentiment-opinion-mining/how-to/use-containers
Run Summarization Docker containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/summarization/how-to/use-containers
Configure Text Analytics for health containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/how-to/configure-containers
Run Text Analytics for health containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/how-to/use-containers

Integrations & Coding Patterns

Topic	URL
Integrate Azure Language SDK and REST APIs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/developer-guide
Use Azure Language features asynchronously	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/use-asynchronously
Call CLU prediction APIs and SDKs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/call-api
Integrate CLU with Bot Framework SDK	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/tutorials/bot-framework
Start building custom NER models via Foundry or REST	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/quickstart
Send prediction requests to custom text classification deployments	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/call-api
Call the entity linking API with correct parameters	https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/how-to/call-api
Call entity linking via SDKs and REST API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/entity-linking/quickstart
Call the key phrase extraction API correctly	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/how-to/call-api
Use key phrase extraction via.NET client library	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/quickstart
Call language detection API and interpret results	https://learn.microsoft.com/en-us/azure/ai-services/language-service/language-detection/how-to/call-api
Implement language detection using SDKs and REST	https://learn.microsoft.com/en-us/azure/ai-services/language-service/language-detection/quickstart
Call the NER API to extract named entities	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/how-to-call
Use the NER client library to extract entities	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/quickstart
Use native document support with Language APIs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/native-document-support/overview
Use the CQA Authoring API for automated management	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/authoring
Call the prebuilt CQA API for ad-hoc answering	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/prebuilt
Call Sentiment and Opinion Mining APIs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/sentiment-opinion-mining/how-to/call-api
Call Sentiment Analysis via SDK and REST	https://learn.microsoft.com/en-us/azure/ai-services/language-service/sentiment-opinion-mining/quickstart
Call conversation summarization API for chats	https://learn.microsoft.com/en-us/azure/ai-services/language-service/summarization/how-to/conversation-summarization
Summarize native documents via API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/summarization/how-to/document-summarization
Use extractive text summarization API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/summarization/how-to/text-summarization
Use Azure Summarization via SDK and REST	https://learn.microsoft.com/en-us/azure/ai-services/language-service/summarization/quickstart
Enable FHIR structuring in health API output	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/concepts/fhir
Interpret relation extraction JSON output	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/concepts/relation-extraction
Call Text Analytics for health API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/how-to/call-api
Quickstart Text Analytics for health via SDK/REST	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/quickstart
Use Azure Language in Power Automate flows	https://learn.microsoft.com/en-us/azure/ai-services/language-service/tutorials/power-automate

Deployment

Topic	URL
Deploy custom language projects to multiple regions	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/custom-features/multi-region-deployment
Deploy custom text classification models for prediction	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/how-to/deploy-model
Run key phrase extraction in Docker containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/how-to/use-containers
Deploy language detection with Docker containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/language-detection/how-to/use-containers
Deploy NER with Docker containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/how-to/use-containers
Move custom question answering projects between resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/migrate-knowledge-base
Deploy Language containers to Azure Kubernetes Service	https://learn.microsoft.com/en-us/azure/ai-services/language-service/tutorials/use-kubernetes-service

适合场景

01

Azure 资源规划

02

云服务升级

03

基础设施检查

04

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

38.32%

按下载量换算101

Claude

31.66%

按下载量换算84

Cursor

18.37%

按下载量换算48

Gemini CLI

9.59%

按下载量换算25

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-language-service

skills-sh

skills.sh

/microsoftdocs/agent-skills/azure-language-service

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