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Localized reading guide

customizePurpose, usage and source

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

Source retrieved:

Source repository
microsoft/skills
SKILL.md
.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize/SKILL.md
Repository stars
3,157
Repository updated
2026-10-31
Categories
Cloud
Last collected

License: License file needs review

Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.

The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.

What this Skill does

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

How the upstream workflow works

When to Use This Skill

Use this skill when you need precise control over deployment configuration: ✅ Choose specific model version (not just latest) ✅ Select deployment SKU (GlobalStandard vs Standard vs PTU) ✅ Set exact capacity within available range

Upstream passage · L25 ↗

Customize Model Deployment

Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options.

Upstream passage · L10 ↗

Fast Path (Defaults)

If user accepts all defaults (latest version, GlobalStandard SKU, recommended capacity, default RAI policy, standard upgrade policy), deployment completes in ~5 interactions.

Upstream passage · L78 ↗
Upstream passage · ↗
1. Verify Authentication
2. Get Project Resource ID
3. Verify Project Exists
4. Get Model Name (if not provided)
5. List Model Versions → User Selects
6. List SKUs for Version → User Selects
7. Get Capacity Range → User Configures
   7b. If no capacity: Cross-Region Fallback → Query all regions → User selects region/project
8. List RAI Policies → User Selects
9. Configure Advanced Options (if applicable)
10. Configure Version Upgrade Policy
11. Generate Deployment Name
12. Review Configuration
13. Execute Deployment & Monitor

Requirements and setup

Prerequisites

Azure subscription with Cognitive Services Contributor or Owner role Microsoft Foundry project resource ID (format: /subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project})

Upstream passage · L50 ↗

Limits and quality checks

No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.

Start with a safe trial

  1. Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
  2. Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
  3. Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
  4. Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.

Skill format and directory specification ↗

Read further in the source

Translation and scope

This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.

This introduction refers to the pinned version below; current repository activity and collection time are shown separately.

Source retrieved
Source commit
00d66a64919edca5bca2c673373444e36a4b5461
Source SHA-256
d0a25090ffc3e139ff2eaeca5f814a83aa61d596571d267f6a7ad534c153ba68
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