From azure
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).
npx claudepluginhub atc-net/atc-agentic-toolkit --plugin azureThis skill uses the workspace's default tool permissions.
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.
Provides guidance on Azure OpenAI Service 2025 models like GPT-5 series, GPT-4.1, o3/o4-mini reasoning, Sora video generation, image/audio models, and Azure CLI deployment.
Provides MCP tools and SDK guides for Azure AI services: AI Search for vector/hybrid/semantic queries, Speech for STT/TTS/transcription, OpenAI models, Document Intelligence for OCR.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Share bugs, ideas, or general feedback.
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.
IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use
read_filewith 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. Usemcp_microsoftdocs:microsoft_docs_fetchto retrieve full articles.
WebFetch tool if the Microsoft Learn MCP server is not available.| 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. |
| 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 |
| 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 |
| 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 |
| 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 |