Azure AI

MicrosoftOfficialCreated by Microsoft

Skill
Tool integration
Cloud and DevOps
MIT
Low risk
Has scripts

From the author

Build and troubleshoot Azure AI Search, Speech, OpenAI, and Document Intelligence apps. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, Speech SDK logs, session ID, result ID, OCR, convert text to speech.

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a centralized reference for integrating and debugging Microsoft Azure AI services. It covers AI Search, Speech, OpenAI, and Document Intelligence, offering guidance on MCP tool usage, CLI commands, and SDK patterns. It includes specific troubleshooting resources for Speech SDK diagnostics and best practices for secure authentication across development and production environments.

What it does

Provides MCP tool mappings for Azure AI Search and Speech services.
Offers quick-reference guides for various Azure AI SDKs across multiple languages.
Outlines best practices for secure authentication using managed identities.
Includes troubleshooting patterns for Speech SDK logs and diagnostics.
Summarizes capabilities for vector, hybrid, and semantic search.
Details patterns for document intelligence and content safety implementations.

When to use it

When integrating Azure AI Search, Speech, or OpenAI into an application.
When troubleshooting Speech SDK connectivity or transcription issues.
When setting up authentication for Azure services in production versus local environments.
When looking for language-specific SDK patterns for Azure AI services.
When needing to perform OCR or form extraction via Document Intelligence.

Advantages

Centralizes documentation for multiple Azure AI services.
Provides clear guidance on moving from local development to production security.
Includes actionable MCP tool commands for rapid integration.
Offers language-specific SDK snippets for quick implementation.
Simplifies complex troubleshooting tasks like Speech SDK log analysis.

Usage examples

“List the available search indexes in my Azure AI Search service.”: The agent uses the azure__search MCP tool with the search_index_list command to retrieve and display the indexes.
“How should I authenticate my Azure AI client in a production environment?”: The agent provides the recommended pattern using ManagedIdentityCredential instead of DefaultAzureCredential to ensure secure, deterministic authentication.
“Transcribe this audio file using Azure Speech.”: The agent utilizes the azure__speech tool with the speech_transcribe command to process the audio file.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-ai/download
Unzip it into the cross-client skills folder of your project:
```
mkdir -p .agents/skills && unzip azure-ai.zip -d .agents/skills
```

Documentation by Microsoft

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, SDK logs	`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: In Copilot CLI or Claude Code, ask the user to run /mcp and enable Azure MCP; in other hosts, ask the user to enable Azure MCP through the host's MCP configuration.

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
Client SDK diagnostics	Speech SDK client diagnostics for log collection, offline analysis, features, and session/result IDs (no MCP or login required)

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
Speech SDK client logs and troubleshooting -> Speech SDK client diagnostics

Files

ATTRIBUTION.mdAdded by AutoGineer956 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md3.6 KiB
references/auth-best-practices.md6.1 KiB
references/sdk/azure-ai-contentsafety-java.md1.4 KiB
references/sdk/azure-ai-contentsafety-py.md1.3 KiB
references/sdk/azure-ai-contentsafety-ts.md1.4 KiB
references/sdk/azure-ai-document-intelligence-dotnet.md1.4 KiB
references/sdk/azure-ai-document-intelligence-ts.md1.5 KiB
references/sdk/azure-ai-openai-dotnet.md1.4 KiB
references/sdk/azure-ai-transcription-py.md1.2 KiB
references/sdk/azure-ai-translation-text-py.md1.3 KiB
references/sdk/azure-ai-translation-ts.md1.3 KiB
references/sdk/azure-ai-vision-imageanalysis-java.md1.3 KiB
references/sdk/azure-ai-vision-imageanalysis-py.md1.3 KiB
references/sdk/azure-search-documents-dotnet.md1.3 KiB
references/sdk/azure-search-documents-py.md1.5 KiB
references/sdk/azure-search-documents-ts.md1.2 KiB
references/speech/azure-checks.md3.5 KiB
references/speech/collection.md3.5 KiB
references/speech/diagnostics.md3.9 KiB
references/speech/interpretation.md3.8 KiB
references/speech/logging-apis.md3.8 KiB
references/speech/output.md3.5 KiB
references/speech/source-contract.md3.8 KiB
references/speech/without-node.md1.9 KiB
scripts/analyze-speech-sdk-log.mjsScript17.7 KiB
scripts/analyze-speech-sdk-log.ps1Script1.4 KiB
scripts/analyze-speech-sdk-log.shScript1.3 KiB

references/auth-best-practices.md

Azure Authentication Best Practices

Source: Microsoft — Passwordless connections for Azure services and Azure Identity client libraries.

Golden Rule

Use managed identities and Azure RBAC in production. Reserve DefaultAzureCredential for local development only.

Authentication by Environment

Environment	Recommended Credential	Why
Production (Azure-hosted)	`ManagedIdentityCredential` (system- or user-assigned)	No secrets to manage; auto-rotated by Azure
Production (on-premises)	`ClientCertificateCredential` or `WorkloadIdentityCredential`	Deterministic; no fallback chain overhead
CI/CD pipelines	`AzurePipelinesCredential` / `WorkloadIdentityCredential`	Scoped to pipeline identity
Local development	`DefaultAzureCredential`	Chains CLI, PowerShell, and VS Code credentials for convenience

Why Not `DefaultAzureCredential` in Production?

Unpredictable fallback chain — walks through multiple credential types, adding latency and making failures harder to diagnose.
Broad surface area — checks environment variables, CLI tokens, and other sources that should not exist in production.
Non-deterministic — which credential actually authenticates depends on the environment, making behavior inconsistent across deployments.
Performance — each failed credential attempt adds network round-trips before falling back to the next.

Production Patterns

.NET

using Azure.Identity;

var credential = Environment.GetEnvironmentVariable("AZURE_FUNCTIONS_ENVIRONMENT") == "Development"
    ? new DefaultAzureCredential()                          // local dev — uses CLI/VS credentials
    : new ManagedIdentityCredential();                      // production — deterministic, no fallback chain
// For user-assigned identity: new ManagedIdentityCredential("<client-id>")

TypeScript / JavaScript

import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

const credential = process.env.NODE_ENV === "development"
  ? new DefaultAzureCredential()                          // local dev — uses CLI/VS credentials
  : new ManagedIdentityCredential();                      // production — deterministic, no fallback chain
// For user-assigned identity: new ManagedIdentityCredential("<client-id>")

Python

import os
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential

credential = (
    DefaultAzureCredential()                              # local dev — uses CLI/VS credentials
    if os.getenv("AZURE_FUNCTIONS_ENVIRONMENT") == "Development"
    else ManagedIdentityCredential()                      # production — deterministic, no fallback chain
)
# For user-assigned identity: ManagedIdentityCredential(client_id="<client-id>")

Java

import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

var credential = "Development".equals(System.getenv("AZURE_FUNCTIONS_ENVIRONMENT"))
    ? new DefaultAzureCredentialBuilder().build()          // local dev — uses CLI/VS credentials
    : new ManagedIdentityCredentialBuilder().build();      // production — deterministic, no fallback chain
// For user-assigned identity: new ManagedIdentityCredentialBuilder().clientId("<client-id>").build()

Local Development Setup

DefaultAzureCredential is ideal for local dev because it automatically picks up credentials from developer tools:

Azure CLI — az login
Azure Developer CLI — azd auth login
Azure PowerShell — Connect-AzAccount
Visual Studio / VS Code — sign in via Azure extension

import { DefaultAzureCredential } from "@azure/identity";

// Local development only — uses CLI/PowerShell/VS Code credentials
const credential = new DefaultAzureCredential();

Environment-Aware Pattern

Detect the runtime environment and select the appropriate credential. The key principle: use DefaultAzureCredential only when running locally, and a specific credential in production.

Tip: Azure Functions sets AZURE_FUNCTIONS_ENVIRONMENT to "Development" when running locally. For App Service or containers, use any environment variable you control (e.g. NODE_ENV, ASPNETCORE_ENVIRONMENT).

import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

function getCredential() {
  if (process.env.NODE_ENV === "development") {
    return new DefaultAzureCredential();          // picks up az login / VS Code creds
  }
  return process.env.AZURE_CLIENT_ID
    ? new ManagedIdentityCredential(process.env.AZURE_CLIENT_ID)  // user-assigned
    : new ManagedIdentityCredential();                            // system-assigned
}

Security Checklist

[ ] Use managed identity for all Azure-hosted apps
[ ] Never hardcode credentials, connection strings, or keys
[ ] Apply least-privilege RBAC roles at the narrowest scope
[ ] Use ManagedIdentityCredential (not DefaultAzureCredential) in production
[ ] Store any required secrets in Azure Key Vault
[ ] Rotate secrets and certificates on a schedule
[ ] Enable Microsoft Defender for Cloud on production resources

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs Node.js

Security

What our scanner noticed· Low risk

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Attribution and licence

Created by

Microsoft

Publisher

Microsoft (Official)

Source

microsoft/skills · .github/plugins/azure-skills/skills/azure-ai · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

Also distributed in

microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-ai.zip