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microsoft-foundry

Automate deployment, management, and evaluation of Azure AI Foundry agents and models.

6|2|Updated Jan 29, 2026
Search Tags:#deployment#ai#azure#agent#model#foundry
One-click install
npx skills add https://github.com/jonathan-vella/azure-smb-rf --skill microsoft-foundry-jonathan-vella
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: microsoft-foundry
Source: https://github.com/jonathan-vella/azure-smb-rf/tree/main/.github/skills/microsoft-foundry
Command: npx skills add https://github.com/jonathan-vella/azure-smb-rf --skill microsoft-foundry-jonathan-vella

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires az, azure-ai-projects, azure-identity, python, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps you manage and automate the deployment, evaluation, and troubleshooting of Foundry agents and models, streamlining the process of creating and managing AI solutions in Azure.

Core Features & Use Cases

  • Agent Management: Deploy, invoke, and troubleshoot Foundry agents.
  • Model Deployment: Deploy and evaluate Azure OpenAI models, including capacity discovery and model availability checks.
  • Quota Management: Monitor and manage quota usage, request increases, and optimize allocations.
  • RBAC Management: Configure access control, role assignments, and service principal setup for CI/CD pipelines.
  • Onboarding: Create new Azure AI Foundry projects and provisions the necessary infrastructure.
  • Use Case: Let's say you have a project that requires deploying a new agent and model. This Skill will guide you through creating the project, deploying the agent, setting up the model, and handling any issues that arise during the process.

Quick Start

Use the 'microsoft-foundry' skill to create a new Foundry project and deploy an agent.

Frequently Asked Questions about microsoft-foundry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy and evaluate Azure AI Foundry agents and models?▼

You can deploy and evaluate Azure AI Foundry agents and models by using automated workflows that guide you through project creation, agent deployment, model setup, and issue troubleshooting end-to-end.

What is the best way to manage Azure OpenAI model capacity and quota usage?▼

Managing Azure OpenAI model capacity and quota usage is handled through dedicated quota management features that monitor allocation, request increases, check model availability, and optimize resource distribution.

How do I set up RBAC and service principals for Azure AI Foundry CI/CD pipelines?▼

Setting up RBAC and service principals for Azure AI Foundry CI/CD pipelines involves configuring access control and role assignments to authenticate and automate deployment workflows securely.

Do I need Azure CLI and Python SDKs to automate Foundry agent management?▼

Yes, automating Foundry agent management requires the Azure CLI, Python, and specific SDKs like azure-ai-projects and azure-identity to interact with Azure AI infrastructure and execute deployment operations.

Can I provision new Azure AI Foundry projects and infrastructure automatically?▼

Provisioning new Azure AI Foundry projects and their necessary infrastructure can be automated through onboarding workflows that initialize the project environment and prepare it for agent and model deployment.

Why are my Foundry agent deployments failing and how do I troubleshoot them?▼

Troubleshooting failed Foundry agent deployments involves using built-in diagnostic workflows to identify configuration issues, quota limits, or model availability problems and apply the necessary remediation steps.

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