azure-ai

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "azure-ai" with this command: npx skills add microsoft/azure-skills/microsoft-azure-skills-azure-ai

Azure AI Services

Services

Service	Use When	MCP Tools	CLI
AI Search	Full-text, vector, hybrid search	`azure__search`	`az search`
Speech	Speech-to-text, text-to-speech	`azure__speech`	-
OpenAI	GPT models, embeddings, DALL-E	-	`az cognitiveservices`
Document Intelligence	Form extraction, OCR	-	-

MCP Server (Preferred)

When Azure MCP is enabled:

AI Search

azure__search with command search_index_list - List search indexes
azure__search with command search_index_get - Get index details
azure__search with command search_query - Query search index

Speech

azure__speech with command speech_transcribe - Speech to text
azure__speech with command speech_synthesize - Text to speech

If Azure MCP is not enabled: Run /azure:setup or enable via /mcp.

AI Search Capabilities

Feature	Description
Full-text search	Linguistic analysis, stemming
Vector search	Semantic similarity with embeddings
Hybrid search	Combined keyword + vector
AI enrichment	Entity extraction, OCR, sentiment

Speech Capabilities

Feature	Description
Speech-to-text	Real-time and batch transcription
Text-to-speech	Neural voices, SSML support
Speaker diarization	Identify who spoke when
Custom models	Domain-specific vocabulary

SDK Quick References

For programmatic access to these services, see the condensed SDK guides:

AI Search: Python | TypeScript | .NET
OpenAI: .NET
Vision: Python | Java
Transcription: Python
Translation: Python | TypeScript
Document Intelligence: .NET | TypeScript
Content Safety: Python | TypeScript | Java

Service Details

For deep documentation on specific services:

AI Search indexing and queries -> Azure AI Search documentation
Speech transcription patterns -> Azure AI Speech documentation

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Open in GitHub Open in ClawHub

Related Skills

Related by shared tags or category signals.

General

azure-deploy

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

Repository Source

139K594Microsoft

General

azure-prepare

Prepare Azure apps for deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Use for create/modernize or create+deploy; not cross-cloud migration (use azure-cloud-migrate). WHEN: "create app", "build web app", "create API", "create serverless HTTP API", "create frontend", "create back end", "build a service", "modernize application", "update application", "add authentication", "add caching", "host on Azure", "create and deploy", "deploy to Azure", "deploy to Azure using Terraform", "deploy to Azure App Service", "deploy to Azure App Service using Terraform", "deploy to Azure Container Apps", "deploy to Azure Container Apps using Terraform", "generate Terraform", "generate Bicep", "function app", "timer trigger", "service bus trigger", "event-driven function", "containerized Node.js app", "social media app", "static portfolio website", "todo list with frontend and API", "prepare my Azure application to use Key Vault", "managed identity".

Repository Source

138.9K594Microsoft

General

azure-diagnostics

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot container apps, troubleshoot functions, troubleshoot AKS, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors.

Repository Source

138.9K594Microsoft

General

azure-storage

Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics capabilities. Includes access tiers (hot, cool, archive) and lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, lifecycle management. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).

Repository Source

138.9K594Microsoft