Agent skill
azure-language-service
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 intents, custom NER, text classification, CQA/FAQ, sentiment, or summarization solutions, 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 Immersive Reader (use azure-immersive-reader), Azure Translator (use azure-translator).
Install this agent skill to your Project
npx add-skill https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-language-service
Metadata
Additional technical details for this skill
- generator
- docs2skills/1.0.0
- generated at
- 2026-04-05
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), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools 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_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=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 regions, resources, lifecycles, and migration decisions for Azure Language apps, including moving from LUIS/QnA Maker/Text Analytics and Language Studio to newer Language/Foundry setups |
| 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
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 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
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
Integrations & Coding Patterns
Deployment
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