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://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/speech/interpretation.md

Interpret observations, not assumptions

Read source boundaries for the reviewed release. Every finding needs an analyzer line anchor; avoid broad root-cause statements.

Configuration and feature evidence

property observations distinguish a property write from a read on a property-bag object. Neither proves the user explicitly configured it, nor that it belongs to the nearest session. Values can change; retain conflicting observations, not a process-global "last value".

request_context observations summarize selected speech.context JSON fields: language identification, pronunciation assessment presence, phrase-list count, segmentation, output options, and speaker diarization. They mean the SDK generated that context, not that transport succeeded or the server adopted it. Do not print phrase/reference text, JSON bodies or unknown properties.

Observation	Safe interpretation
Locale, voice or format property	A value was observed on that object
LID context with mode/candidate languages	Those fields occurred in generated context
Pronunciation assessment object	Assessment configuration was present; scoring success is unknown
Speaker diarization context	Diarization configuration was present; not proof of speaker accuracy
Detailed output/word timings	Requested output; may be set by another feature
No feature entry	Not observed, not disabled

IDs and lifecycle

The ID inventory is typed, not a count of unique business requests. Session ID is not ResultId. STT intermediate/final IDs can reflect phrase IDs; do not count every occurrence as a new request. TTS result/request equivalence is supported only by the reviewed implementation. One connection can serve multiple synthesis requests. Preserve protocol request IDs separately.

Final recognition records retain numeric reasonCode, not a guessed cause. For the reviewed version, ResultReason defines NoMatch as 0 and RecognizedSpeech as 3. Other values/versions require their matching enum; cancellation details must come from app events when the native trace does not expose them.

Only IDs explicit in the same record are attached to observations. Result IDs on unrelated records remain unassociated. Same thread, time overlap, or similar GUID spelling is insufficient.

Client evidence	Next check; not a conclusion
WebSocket upgrade status other than 101	Preserve exact status; compare endpoint/auth mode and error details
DNS error code	Resolve the confirmed host from the affected environment
401/403	Verify resource/endpoint, auth method and relevant configuration; no single-cause mapping
NoMatch	Read NoMatch details and inspect input/configuration; do not label an outage
TLS certificate verification error (not extracted by the analyzer)	Keep the exact line; compare the trust store and any TLS-inspecting proxy of the affected host; never disable validation
Log ends without a terminal event	Incomplete capture is possible; do not invent a disconnect

The analyzer does not implement all these diagnoses or echo unknown errors.

Relative milliseconds are not wall-clock UTC or audio offsets. Embedded timestamps are separate observations, not automatic cross-clock anchors. SDK latency properties are reported as SDK metrics, not microphone-to-display or playback latency. Use matching API definitions before deriving a breakdown: TTS latency.

Never disable certificate validation, remove network controls, rotate keys, increase quota, or delete/recreate resources as a generic troubleshooting fix.

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

Instructions that use the network
Scripts that your agent may run

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A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

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

2026-11-09

Also distributed in

microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

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