customize

Automate end-to-end Azure OpenAI deployment configuration with version, SKU, capacity, and RAI policy options.

Updated Apr 12, 2026

Search Tags:#automation #deployment #customization #azure-openai #sku #rai-policy #ptu

Ready to run

npx skills add https://github.com/davidrrowley/CortexYouV3 --skill customize-davidrrowley

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: customize
Source: https://github.com/davidrrowley/CortexYouV3/tree/main/.agents/skills/microsoft-foundry/models/deploy-model/customize
Command: npx skills add https://github.com/davidrrowley/CortexYouV3 --skill customize-davidrrowley

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provides an interactive guided workflow to configure Azure OpenAI deployments with full customization control, enabling precise version, SKU selection, capacity, RAI policy, and advanced options.

Core Features & Use Cases

Interactive phase-driven deployment setup (version, SKU, capacity, RAI, and advanced options)
Supports OpenAI MaaS and Anthropic deployments with appropriate payloads
Handles validation, region/capacity fallbacks, and deployment naming

Quick Start

Follow the guided prompts to configure a customized Azure OpenAI deployment end-to-end.

Frequently Asked Questions about customize

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

FAQPage Schema

How do I configure an Azure OpenAI deployment with specific SKU and RAI policy settings?▼

You can configure an Azure OpenAI deployment by using an interactive guided workflow that collects your model name, SKU, capacity, and RAI policy preferences to apply precise customization settings end-to-end.

Can I deploy Anthropic models via the Azure OpenAI CLI or REST API?▼

Yes, you can deploy Anthropic models through the Azure OpenAI deployment workflow, which generates the appropriate payloads and deploys them via CLI or REST API alongside standard OpenAI MaaS deployments.

What is the best way to automate Azure OpenAI deployments with dynamic quota and spillover?▼

Automating Azure OpenAI deployments with dynamic quota and spillover is handled through a guided setup process that configures advanced options, validates inputs, and manages region and capacity fallbacks automatically.

How do I handle region and capacity fallbacks when setting up PTU deployments on Azure OpenAI?▼

Handling region and capacity fallbacks for PTU deployments is managed automatically by the configuration workflow, which validates your selected capacity and applies fallback logic to ensure successful Azure OpenAI deployment.

Does the Azure OpenAI deployment configuration support custom RAI policies?▼

Yes, the Azure OpenAI deployment configuration supports custom RAI policies, allowing you to define and apply specific Responsible AI policies interactively during the phase-driven deployment setup process.

What are the limitations of customizing Azure OpenAI deployments for PTU SKUs?▼

Customizing Azure OpenAI deployments for PTU SKUs requires specific capacity validation and region fallback handling, meaning deployments may fail if the requested PTU capacity is unavailable in the selected region.