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 apps, custom NER/classification, CQA, sentiment/summarization, or PII/key phrase pipelines, and other Azure AI Language related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Speech (use azure-speech), Azure Translator (use azure-translator). Use when this capability is needed.
metadata	{"author":"gabrielmoreira"}

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 custom text classification and custom question answering, including model performance, configuration, and runtime/response problems.
Best Practices	L43-L59	Best practices for designing, labeling, and evaluating CLU, custom NER, text classification, and CQA projects, including multilingual handling, emojis, schemas, and autolabeling.
Decision Making	L60-L69	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	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 language/region support for Azure AI Language features (CLU, NER, PII, key phrases, QnA), including data sizes, throughput, containers, and training job constraints.
Security	L96-L106	Security, encryption, and access control for Azure AI Language: RBAC, managed identities, SAS, CMK/data-at-rest, network isolation, Private Link, and CQA-specific security setup.
Configuration	L107-L131	Configuring Azure AI Language/CLU/NER/CQA projects and containers, including data formats, resources, Docker/on-prem setups, metrics, confidence scores, PII redaction, and sentiment/summarization.
Integrations & Coding Patterns	L132-L163	Implementing Azure AI Language features via REST/SDKs: CLU, custom NER/classification, CQA, sentiment, summarization, health, entity linking, and integrating with bots/Power Automate.
Deployment	L164-L173	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
Diagnose and resolve custom question answering issues	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 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

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 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 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-tune models	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
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
Create CLU fine-tuning tasks via Foundry and REST API	https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/create-project
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

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

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Source: gabrielmoreira/agent-skills-mirror — distributed by TomeVault.