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-L69	Guidance on when and how to migrate or transition Azure Language workloads (LUIS, QnA Maker, Text Analytics, Language Studio) and how to choose/manage resources for conversational QA.
Architecture & Design Patterns	L70-L76	Architectural guidance for CLU and custom text classification: choosing CLU vs orchestration workflows, and designing regional backup, redundancy, and failover strategies.
Limits & Quotas	L77-L95	Limits, quotas, and regional/language support for Azure AI Language features (CLU, NER, PII, CQA, containers), including data, rate, throughput, and job constraints.
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-L132	Configuring Azure AI Language projects and containers: CLU, NER, text classification, CQA, sentiment, summarization, and health—data formats, training, metrics, resources, and runtime options.
Integrations & Coding Patterns	L133-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-L176	How to deploy Azure AI Language models and projects (custom text/Q&A, NER, language detection, key phrases) across regions, containers, and AKS, including moving Q&A projects between 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
Plan migration from Language Studio to 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 when to migrate from LUIS or QnA Maker	https://learn.microsoft.com/en-us/azure/ai-services/language-service/reference/migrate
Migrate from Text Analytics 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
Use Azure Language data and rate limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/data-limits
Check regional availability for Azure Language features	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/regional-support
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
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 tools and agents in Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/foundry-tools-agents
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
Create and deploy a custom Q&A agent in Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/deploy-agent
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