Azure AI Language Skill
SkillCloud & infraExpert 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, CQA, health text, sentiment/PII, or orchestration workflows, and other Azure AI Language related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure Speech in Foundry Tools (use azure-speech), Azure Translator (use azure-translator), Azure AI Document Intelligence (use azure-document-intelligence).
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Azure AI Language Skill skill
What this skill tells your AI
The instructions your AI receives, as published by microsoftdocs/agent-skills in skills/azure-language-service/SKILL.md and read by ahel’s review.
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 issues in Azure Language custom NER and conversational question answering (CQA), including model errors, configuration problems, and troubleshooting workflows. |
| Best Practices | L43-L53 | 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 | L54-L63 | 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 | L64-L71 | 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 | L72-L95 | Limits, quotas, languages, and model lifecycles for Azure Language features (CLU, NER, text classification, CQA, health), including data size, rate, throughput, and container constraints. |
| Security | L96-L107 | Securing Azure Language and CQA: encryption at rest (including CMK), RBAC, managed identities, SAS tokens, network isolation/Private Link, and secure deployment/data access configuration. |
| Configuration | L108-L125 | Configuring Azure AI Language features and runtime: CLU fine-tuning, NER formats/metadata, CQA behavior/telemetry, health/FHIR output, and container settings. |
| Integrations & Coding Patterns | L126-L145 | How to call Azure Language/TA/health/CLU/CQA APIs and SDKs for NER, entity linking, key phrases, language detection, sentiment, PII redaction, relations, and orchestration workflows. |
| Deployment | L146-L156 | Guides for deploying and running custom language/NER/CQA/sentiment/health models across regions, on-prem via Docker containers, and moving projects 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
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
Security
Configuration
Integrations & Coding Patterns
Deployment
Signals
- GitHub stars
- 740
- Forks
- 119
- Last commit
- Sep 2026
ahel review
S4info
community integration — published by microsoftdocs, not azure
Automated review, not a security audit. Ruleset v1.
Advanced
- Catalog kind
- skill
- Gateway key
azure-language-service- Source
- github.com/microsoftdocs/agent-skills