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cassm199-mita
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microsoft-foundry

Manage Foundry agent and model lifecycle with deployment and evaluation.

Updated Apr 21, 2026
Search Tags:#rbac#model deployment#agent management#foundry#capacity management
One-click install
npx skills add https://github.com/cassm199-mita/azure-agentic-infraops-accelerator --skill microsoft-foundry-cassm199-mita
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: microsoft-foundry
Source: https://github.com/cassm199-mita/azure-agentic-infraops-accelerator/tree/main/.github/skills/microsoft-foundry
Command: npx skills add https://github.com/cassm199-mita/azure-agentic-infraops-accelerator --skill microsoft-foundry-cassm199-mita

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires az, jq, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive solution for managing Foundry agents and models, covering deployment, evaluation, and lifecycle management.

Core Features & Use Cases

  • Agent Management: Deploy, evaluate, and manage Foundry agents.
  • Model Deployment: Deploy models to Foundry with intelligent routing.
  • Capacity Management: Monitor and manage quotas and capacity for Foundry resources.
  • RBAC Management: Manage RBAC permissions and role assignments.
  • Use Case: Imagine you need to deploy a new AI agent to Foundry. Use this Skill to create the agent, deploy the model, and set up RBAC permissions.

Quick Start

Use the 'microsoft-foundry' skill to deploy a new Foundry agent with the 'create' sub-skill.

Frequently Asked Questions about microsoft-foundry

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

FAQPage Schema
How do I manage the lifecycle of Foundry agents and models?▼

To manage the lifecycle of Foundry agents and models, you can deploy, evaluate, and manage both containerized and prompt-based agents while integrating directly with Azure AI Services.

What's the best way to deploy a new AI agent to Foundry?▼

Deploying a new AI agent to Foundry involves using the create sub-skill to provision the agent, deploy the associated model, and configure necessary RBAC role assignments for secure access.

Do I need Azure CLI and a subscription to manage Foundry capacity and RBAC?▼

Yes, managing Foundry capacity quotas and RBAC permissions requires Azure CLI access and an active Azure subscription to authenticate and apply role assignments.

How does capacity management work for Foundry resources?▼

Capacity management for Foundry resources involves monitoring and managing quotas to ensure your deployed agents and models have the necessary compute resources available within your Azure environment.

Can I use this to deploy both containerized and prompt-based agents?▼

Yes, you can deploy both containerized and prompt-based agents to Foundry, allowing you to evaluate and manage diverse AI agent architectures within a single workflow.

How do I set up RBAC permissions for a newly deployed Foundry model?▼

Setting up RBAC permissions for a newly deployed Foundry model requires using Azure CLI to assign appropriate roles, ensuring secure access control over your agent and model resources.

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