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aleph23
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customize

Configure Azure OpenAI deployments with model version, SKU, capacity, and RAI policy.

Updated Feb 15, 2026
Search Tags:#deployment#azure#throughput#openai#sku#rai#ptu
One-click install
npx skills add https://github.com/aleph23/Natasha --skill customize-aleph23
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: customize
Source: https://github.com/aleph23/Natasha/tree/main/skills/microsoft-foundry/models/deploy-model/customize
Command: npx skills add https://github.com/aleph23/Natasha --skill customize-aleph23

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Deploying Azure OpenAI models with precise configuration is complex and error-prone. This skill provides an interactive guided workflow to configure model version, SKU, capacity, RAI policy, and advanced options, reducing setup time and misconfigurations.

Core Features & Use Cases

  • Interactive, step-by-step deployment flow for Azure OpenAI models.
  • Full customization: version, SKU, capacity, RAI policy, dynamic quota, priority processing, spillover.
  • PTU deployments and MaaS compatibility with cross-region quota checks and Anthropic path through REST as needed.
  • Alternative: preset deployment for quick region selection.

Quick Start

Guide me through a customized deployment of an Azure OpenAI model by selecting version, SKU, capacity, RAI policy, and advanced options.

Frequently Asked Questions about customize

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

FAQPage Schema
How do I customize an Azure OpenAI deployment with specific SKU and capacity settings?▼

You can customize an Azure OpenAI deployment through an interactive, step-by-step workflow that configures model version, SKU, capacity, RAI policy, and advanced options to reduce setup time and prevent misconfigurations.

What prerequisites do I need to deploy Azure OpenAI models using a guided workflow?▼

To deploy Azure OpenAI models through this workflow, you need Azure CLI authentication, a valid project resource ID, and proper handling of MaaS versus OpenAI formats to ensure successful provisioning and configuration.

Can I configure RAI policy and dynamic quota for PTU deployments on Azure OpenAI?▼

Yes, the deployment workflow enables full customization of RAI policy, dynamic quota, priority processing, and spillover for PTU deployments, while maintaining MaaS compatibility and verifying cross-region quota limits.

Does the Azure OpenAI deployment workflow support Anthropic models through REST?▼

Yes, the deployment workflow includes an optional Anthropic path that provisions models through REST API calls, extending configuration capabilities beyond standard Azure OpenAI model formats.

What is the best way to quickly select a region for an Azure OpenAI preset deployment?▼

For faster setup, you can use the preset deployment alternative which streamlines the process by focusing on quick region selection rather than walking through the full interactive customization workflow.

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