azure-language-service

name	azure-language-service
description	Expert knowledge for Azure AI Language development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building CLU, custom NER, sentiment, PII redaction, or conversational question answering solutions, and other Azure AI Language related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Speech (use azure-speech), Azure Translator (use azure-translator), Azure AI Immersive Reader (use azure-immersive-reader).
compatibility	Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata	{"generated_at":"2026-07-26","generator":"docs2skills/1.0.0"}

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 issues in Azure Language custom NER and conversational question answering (CQA), including model errors, configuration problems, and troubleshooting workflows.
Best Practices	L43-L54	Best practices for designing and authoring CLU, custom NER, PII, and CQA projects, including data prep, schemas, lifecycles, chitchat personas, and document formatting.
Decision Making	L55-L64	Guides for choosing regions and app types, planning CQA solutions, and deciding or executing migrations from LUIS, QnA Maker, Text Analytics, and Language Studio to Azure Language/Fountry.
Architecture & Design Patterns	L65-L72	Designing and implementing regional failover and high-availability patterns for CLU, custom NER, custom text classification, and orchestration workflow models in Azure AI Language.
Limits & Quotas	L73-L96	Limits, quotas, languages, and supported entities for Azure Language features (CLU, NER, classification, CQA, health), including data size, rate/throughput, training and model lifecycles.
Security	L97-L108	Securing Azure AI Language and CQA: encryption at rest (including CMK), RBAC, managed identities, SAS tokens, network isolation/Private Link, and secure deployment/data access configuration.
Configuration	L109-L129	Configuring Azure AI Language projects and containers: resources, versioning, NER entities/skills, orchestration intents, CQA behavior/telemetry, health analytics, and storage/security settings.
Integrations & Coding Patterns	L130-L152	Using Azure AI Language APIs/SDKs for NER, entity linking, key phrases, sentiment, language detection, health/FHIR, custom Q&A/CLU, PII redaction, async patterns, and Power Automate integration
Deployment	L153-L165	Guides for deploying Azure Language services and custom projects (NER, key phrases, sentiment, health, CQA) across regions, Docker/on-prem, and AKS, plus moving CQA between environments.

Troubleshooting

Topic	URL
Resolve common issues with custom NER in Azure Language	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/faq
Troubleshoot common CQA issues and errors	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/troubleshooting

Best Practices

Topic	URL
Apply CLU project authoring best practices	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/best-practices
Prepare data and design schema for custom NER models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/design-schema
Adapt PII detection to custom domain terminology	https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/how-to/adapt-to-domain-pii
Implement CQA project best practices	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/best-practices
Follow CQA project development lifecycle	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/project-development-lifecycle
Apply authoring best practices to CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/best-practices
Add chitchat personas to CQA projects	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/chit-chat
Apply document formatting best practices for custom Q&A	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/reference/document-format-guidelines

Decision Making

Topic	URL
Choose Azure regions for Language service features	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/regional-support
Choose CLU app vs orchestration workflow	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/concepts/app-architecture
Migrate Azure Language Studio projects to Microsoft Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/migration-studio-to-foundry
Plan a CQA app and select Azure resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/plan
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
Design regional failover for CLU models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/fail-over
Design regional failover for custom NER models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/fail-over
Design regional failover for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/fail-over
Implement regional failover for orchestration workflow models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/orchestration-workflow/concepts/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
Understand lifecycle timelines for Azure Language models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/model-lifecycle
Use CLU containers with on-premises limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/use-containers
Check CLU supported languages and locales	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/language-support
Reference CLU prebuilt entity components	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/prebuilt-component-reference
Review CLU data and throughput limits	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/service-limits
Understand training job expiration for custom NER	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/train-model
Check language support matrix for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/language-support
Review data and rate limits for custom text classification	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-text-classification/service-limits

Security

Topic	URL
Understand data-at-rest encryption in Language service	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/encryption-data-at-rest
Configure RBAC for Azure Language resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/role-based-access-control
Configure managed identities for Azure storage access	https://learn.microsoft.com/en-us/azure/ai-services/language-service/native-document-support/managed-identities
Create SAS tokens for Azure storage blobs securely	https://learn.microsoft.com/en-us/azure/ai-services/language-service/native-document-support/shared-access-signatures
Configure Azure resources for CQA fine-tuning	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/configure-azure-resources
Configure CMK encryption for CQA data at rest	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/encrypt-data-at-rest
Enable network isolation and Private Link for CQA	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/network-isolation
Secure Azure Language deployments and data access	https://learn.microsoft.com/en-us/azure/ai-services/language-service/secure-deployment

Configuration

Topic	URL
Configure Azure resources for CLU fine-tune models	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/configure-azure-resources
Configure Azure Language service containers settings	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/configure-containers
Manage project versioning in conversational language	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/custom-features/project-versioning
Use supported data formats for custom NER	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/concepts/data-formats
Create and manage Azure custom NER projects and resources	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/create-project
Use NER entity metadata and resolutions	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/concepts/entity-metadata
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 options	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/how-to/skill-parameters
Configure the None intent behavior in orchestration workflow	https://learn.microsoft.com/en-us/azure/ai-services/language-service/orchestration-workflow/concepts/none-intent

Integrations & Coding Patterns

Topic	URL
Integrate Azure Language via SDK and REST APIs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/developer-guide
Use Azure Language features asynchronously via API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/concepts/use-asynchronously
Call the custom NER prediction API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/call-api
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
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
Invoke the Key Phrase Extraction API correctly	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/how-to/call-api
Call Azure Language Detection API and interpret scores	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
Perform NER using Azure Language APIs	https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/how-to-call
Create a .NET app using the NER client library

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 NER with Docker containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/custom-named-entity-recognition/how-to/use-containers
Deploy Key Phrase Extraction containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/key-phrase-extraction/how-to/use-containers
Deploy Azure Language Detection via Docker containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/language-detection/how-to/use-containers
Run NER 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 CQA agent in Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/deploy-agent
Move CQA projects between environments	https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/how-to/migrate-knowledge-base
Deploy Sentiment Analysis containers on-premises	https://learn.microsoft.com/en-us/azure/ai-services/language-service/sentiment-opinion-mining/how-to/use-containers
Run Text Analytics for health in Docker containers	https://learn.microsoft.com/en-us/azure/ai-services/language-service/text-analytics-for-health/how-to/use-containers