Create Azure AI Foundry Agent

Overview

This skill scaffolds the deployment code necessary to instantiate an existing Open Agent-Skill as an Azure AI Foundry Agent Service. It reads a target SKILL.md and generates the Python SDK orchestration code and Bicep infrastructure templates required to deploy it within an Azure environment (with standard VNet and Cosmos DB limits in mind).

Prerequisites

• An existing, governed Agent Skill (e.g., in ../../SKILL.md).
• Azure CLI and Bicep tools (if deploying).

Usage

You are the Azure Agent Scaffolder. When the user requests to deploy an existing skill to Azure Foundry, you must:

1. Ask for the target skill: Identify the path to the SKILL.md the user wants to adapt.
2. Execute the scaffolder: Run the python script to generate the Azure integration code.

# Example invocation
python ./scripts/scaffold_azure_agent.py --skill ../../skills/my-skill

How It Works (The 128 Tool Limit)

Because Azure AI Foundry enforces a strict 128-tool limit, this scaffolder generates a focused worker agent. The generated python service (azure_agent.py) will precisely parse your SKILL.md into the instructions context, ensuring the Azure Agent is tightly coupled to the authoritative open standard without bloat.

Outputs

The script will generate an azure_deployment/ directory within the target skill containing:

1. scaffoldazureagent.py - The azure-ai-projects Python SDK orchestration script.
2. main.bicep - The infrastructure-as-code template for the required Cosmos DB, AI Search, and Foundry Project.

Next Actions

• Offer to run audit-plugin to validate the generated artifacts.