Microsoft Azure AI Foundry Skills — Setup Guide¶
Source: microsoft/azure-skills (478K+ combined installs) Category: Agent Infrastructure / Cloud Quality Tier: 🟢 Production
Microsoft's official skills for building, deploying, and managing AI agents on Azure AI Foundry. Covers the full agent lifecycle: project creation, model deployment, agent scaffolding, CI/CD pipelines, observability, evaluation, fine-tuning, and troubleshooting. Enterprise-grade infrastructure for production agent deployments.
Installation¶
npx skills add microsoft/azure-skills --skill microsoft-foundry
npx skills add microsoft/azure-skills --skill azure-ai
npx skills add microsoft/azure-skills --skill azure-deploy
Included Skills¶
| Skill | Installs | Purpose |
|---|---|---|
| microsoft-foundry | 478.2K | Full Azure AI Foundry agent platform — create, deploy, invoke, observe, CI/CD, routines, fine-tuning |
| azure-ai | 474.4K | Azure AI Services resource and project management |
| azure-deploy | 474.1K | Agent deployment, versioning, and multi-environment management |
Prerequisites¶
| Requirement | Details |
|---|---|
| Azure subscription | Active Azure account with AI Foundry access |
Azure CLI (az) |
Install via curl -sL https://aka.ms/InstallAzureCLIDeb |
Azure Developer CLI (azd) |
Install via curl -fsSL https://aka.ms/install-azd.sh |
| Python 3.10+ | For hosted agent development |
Key Capabilities¶
Agent Lifecycle Management¶
- Create: Scaffold new agents end-to-end (quick-start) or customize with existing code, A2A, and advanced setups
- Deploy: Deploy hosted agents to Foundry, manage versions, multi-environment deploys
- Invoke: Send messages to agents, single or multi-turn conversations, WebSocket duplex for voice/real-time
- Routines: Schedule or event-trigger agents with CRUD, enable/disable, manual dispatch
Observability & Quality¶
- Observe: Evaluate agent quality, run batch evals, analyze failures, optimize prompts
- Trace: Query traces, analyze latency/failures, correlate eval results
- Agent Optimizer: Run optimization jobs, apply candidates locally, deploy through azd
- Eval Datasets: Harvest production traces into datasets, version management, regression detection
Infrastructure¶
- Project/Resource Creation: Create Foundry projects with public or VNet-isolated access
- Model Deployment: Unified deployment with intelligent routing (preset, custom, capacity discovery)
- Fine-tuning: SFT distillation, DPO preference optimization, RFT with graders
- CI/CD: Set up deployment pipelines with azd, continuous evaluation monitoring
Quick Start¶
# 1. Authenticate
az login
# 2. Create a new Foundry project (public access)
azd init --template microsoft/azure-ai-foundry-agent
azd up
# 3. Deploy and test an agent
azd deploy
azd invoke --agent my-agent --message "Hello"
# 4. Set up CI/CD
azd pipeline config
Verification¶
npx skills list | grep microsoft/azure-skills
az account show # Verify Azure auth
azd version # Verify azd CLI
Notes¶
- Official Microsoft-maintained skills with 478K+ combined installs — the standard for Azure AI agent infrastructure
- Requires active Azure subscription and cloud resources (not local-only)
- Best for production-grade agent deployments with enterprise requirements (VNet, CI/CD, observability)
- Complements local agent development (Hermes, Claude Code) with cloud deployment capabilities
- Fine-tuning supports SFT, DPO, and RFT with custom graders