Agent skill · DevOps & Cloud

azure-ai

Build AI solutions with Azure AI services including OpenAI, Cognitive Services, Document Intelligence, and AI Search. Use for enterprise AI, document processing, and intelligent applications on Azure.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill azure-ai --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 32 KB
Bundled scripts: none
Path: skills/ai-llm/azure-ai/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

The skill provides complete guidance for building, configuring, troubleshooting, and managing Azure AI services, covering multiple service categories such as AI Platform, Generative AI, Search & RAG, AI Agents, Document AI, Cognitive Services, ML Platform, and Governance.

How it works

It enumerates deployment options and workflows across four major areas:

  • Microsoft Foundry (Azure AI Foundry): outlines hub/project setup, model catalog, and prompt flow, with CLI and Python SDK usage examples for creating resources and connecting components.
  • Azure OpenAI Service: details deployment types, available models, resource creation, model deployments, Python SDK usage, content filtering configuration, and example code snippets for chat, embeddings, and image generation.
  • Azure AI Search: shows search service creation, admin/query keys, vector index creation with a vector field, and configurations for hybrid and semantic search, plus example code for hybrid queries and knowledge stores for agents.
  • Azure AI Agents: describes agent types and includes Python examples for creating agents with tools (code interpreter, file search), threads, messages, and runs; also provides patterns for function-calling agents and multi-agent orchestration.
  • Document Intelligence (partial): lists prebuilt models and shows resource creation commands (CLI) and Python usage.

When to use it

Use when implementing enterprise Azure AI solutions that require Foundry integration, OpenAI deployments, AI search with vector embeddings, or multi-agent orchestration in Azure.

What it can touch

Tools and scripts mentioned include:

  • CLI: az group create, az ml workspace create, az cognitiveservices account create, az cognitiveservices account deployment create, az search service create, az search admin-key show, az search query-key list
  • Python SDKs and packages: azure-ai.projects, azure-identity, openai (AzureOpenAI), azure-ai-agents, azure-search-documents, azure-core
  • File contents like connection.yml, YAML examples, and code snippets for client initialization and operations

Caveats

The skill presents configuration examples and deployments but does not guarantee successful execution or availability of resources in a given Azure environment. It includes license and tool references appropriate to the described services but does not state license terms beyond mentioning MIT for the skill package.

From the SKILL.md

# Azure AI Skill Complete guidance for building, configuring, troubleshooting, and managing Azure AI services. ## Quick Reference ### Service Categories | Category | Services | |----------|----------| | **AI Platform** | Microsoft Foundry (Azure AI Foundry), Azure AI Hub, AI Projects | | **Generative AI** | Azure OpenAI Service (GPT-4, GPT-4o, o1, DALL-E, Whisper) | | **Search & RAG** | Azure AI Search (vector, semantic, hybrid, agentic retrieval) | | **AI Agents** | Azure AI Agent Service, Foundry Agent Service, Multi-agent Orchestration | | **Document AI** | Document Intelligence (OCR, form extraction, prebuilt models) | | **Cognitive Services** | Vision, Speech, Language, Translator, Content Safety | | **ML Platform** | Azure Machine Learning (MLOps, training, deployment) | | **Governance** | Responsible AI, Content Filtering, Safety Evaluations | ### Common CLI Prefixes ```bash az cognitiveservices # Cognitive Services & Azure OpenAI az search # Azure AI Search az ml # Azure Machine Learning az ai # Azure AI resources (newer) ``` --- ## 1. Microsoft Foundry (Azure AI Foundry) ### Overview Microsoft Foundry is the unified platform for enterprise AI operations, combining: - **AI

What's inside
Steps it walks through
  1. Quick Reference
  2. Service Categories
  3. Common CLI Prefixes
  4. 1. Microsoft Foundry (Azure AI Foundry)
  5. Overview
  6. Portal Access
  7. Create AI Hub & Project
  8. Python SDK Setup
  9. Connections Management
  10. 2. Azure OpenAI Service
  11. Deployment Types
  12. Available Models (as of 2024)
  13. Create Azure OpenAI Resource
  14. List Deployments & Models
Ships with 1 file
  • metadata.json
Commands it runs
az cognitiveservices    # Cognitive Services & Azure OpenAI
az search               # Azure AI Search
az ml                   # Azure Machine Learning
az ai                   # Azure AI resources (newer)
Create resource group
az group create --name rg-ai-foundry --location eastus
Create AI Hub (shared infrastructure)
az ml workspace create \
Create AI Project (linked to hub)
List connections in hub
More from claude-skill-registry
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About this skill
What does the azure-ai skill do?

Build AI solutions with Azure AI services including OpenAI, Cognitive Services, Document Intelligence, and AI Search. Use for enterprise AI, document processing, and intelligent applications on Azure.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill azure-ai --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going