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, text classification, CQA, sentiment, summarization, or health workloads, 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 Bot Service (use azure-bot-service). Use when this capability is needed.
metadata	{"author":"atc-net"}

Azure Language Service Skill

This skill provides expert guidance for Azure Language Service. 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: This file may be large. Use the Category Index below to locate relevant sections, then use read_file with specific line ranges (e.g., L136-L144) to read the sections needed for the user's question This skill requires network access to fetch documentation content. Use mcp_microsoftdocs:microsoft_docs_fetch to retrieve full articles.

• Fallback: Use the built-in WebFetch tool if the Microsoft Learn MCP server is not available.

Category Index

Category	Lines	Description
Troubleshooting	L31-L35	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	L37-L53	Best practices for designing, labeling, and evaluating CLU, custom NER, text classification, and CQA projects, including multilingual handling, emojis, schemas, and autolabeling.
Decision Making	L55-L61	Guidance on Azure Language lifecycle policies, choosing resources for conversational QA, and when/how to migrate from LUIS, QnA Maker, or Text Analytics to Azure Language API
Architecture & Design Patterns	L63-L68	Architectural guidance for CLU and custom text classification: choosing CLU vs orchestration workflows, and designing regional backup, redundancy, and failover strategies.
Limits & Quotas	L70-L87	Limits, quotas, and regional/language support for Azure AI Language features (CLU, NER, PII, CQA, containers), including data, rate, throughput, and job constraints.
Security	L89-L97	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	L99-L124	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	L126-L156	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	L158-L168	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

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 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 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
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

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

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

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
Migrate Azure Language Studio projects to Foundry	https://learn.microsoft.com/en-us/azure/ai-services/language-service/migration-studio-to-foundry
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

---

Source: atc-net/atc-agentic-toolkit — distributed by TomeVault.