skill
Customize
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 dep...
About
# Customize Model Deployment
Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options.
## Quick Reference
| Property | Description | |----------|-------------| | **Flow** | Interactive step-by-step guided deployment | | **Customization** | Version, SKU, Capacity, RAI Policy, Advanced Options | | **SKU Support** | GlobalStandard, Standard, ProvisionedManaged, DataZoneStandard | | **Best For** | Precise control over deployment configuration | | **Authentication** | Azure CLI (`az login`) | | **Tools** | Azure CLI, MCP tools (optional) |
## 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 - ✅ **Configure content filtering** (RAI policy selection) - ✅ **Enable advanced features** (dynamic quota, priority processing, spillover) - ✅ **PTU deployments** (Provisioned Throughput Units)
**Alternative:** Use `preset` for quick deployment to the best available region with automatic configuration.
### Comparison: customize vs preset
| Feature | customize | preset | |---------|---------------------|----------------------------| | **Focus** | Full customization control | Optimal region selection | | **Version Selection** | User chooses from available | Uses latest automatically | | **SKU Selection** | User chooses (GlobalStandard/Standard/PTU) | GlobalStandard only | | **Capacity** | User specifies exact value | Auto-calculated (50% of available) | | **RAI Policy** | User selects from options | Default policy only | | **Region** | Current region first, falls back to all regions if no capacity | Checks capacity across all regions upfront | | **Use Case** | Precise deployment requirements | Quick deployment to best region |
## 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}`) - Azure CLI installed and authenticated (`az login`) - Optional: Set `PROJECT_RESOURCE_ID` environment variable
## Workflow Overview
### Complete Flow (14 Phases)
``` 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 ```
### 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.
---
## Phase Summaries
> ⚠️ **MUST READ:** Before executing any phase, load [references/customize-workflow.md](references/customize-workflow.md) for the full scripts and implementation details. The summaries below describe *what* each phase does — the reference file contains the *how* (CLI commands, quota patterns, capacity formulas, cross-region fallback logic).
| Phase | Action | Key Details | |-------|--------|-------------| | **1. Verify Auth** | Check `az account show`; prompt `az login` if needed | Verify correct subscription is active | | **2. Get Project ID** | Read `PROJECT_RESOURCE_ID` env var or prompt user | ARM resource ID format required | | **3. Verify Project** | Parse resource ID, call `az cognitiveservices account show` | Extracts subscription, RG, account, project, region | | **4. Get Model** | List models via `az cognitiveservices account list-models` | User selects from available or enters custom name | | **5. Select Version** | Query versions for chosen model | Recommend latest; user picks from list | | **6. Select SKU** | Query model catalog + subscription quota, show only deployable SKUs | ⚠️ Never hardcode SKU lists — always query live data | | **7. Configure Capacity** | Query capacity API, validate min/max/step, user enters value | Cross-region fallback if no capacity in current region | | **8. Select RAI Policy** | Present content filter options | Default: `Microsoft.DefaultV2` | | **9. Advanced Options** | Dynamic quota (GlobalStandard), priority processing (PTU), spillover | SKU-dependent availability | | **10. Upgrade Policy** | Choose: OnceNewDefaultVersionAvailable / OnceCurrentVersionExpired / NoAutoUpgrade | Default: auto-upgrade on new default | | **11. Deployment Name** | Auto-generate unique name, allow custom override | Validates format: `^[\w.-]{2,64}$` | | **12. Review** | Display
Install
Run this command
git clone https://github.com/microsoft/azure-skills && cp -r azure-skills/skills/microsoft-foundry/models/deploy-model/customize ~/.claude/skills/Works with
Manual steps
Clone the repository and copy the `skills/microsoft-foundry/models/deploy-model/customize` folder into your Claude skills directory. Compatible with Claude Code, Cursor, Codex, and any Agent Skills-compatible agent.
Frequently asked questions
What is the Customize skill?
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…
How do I install Customize?
Run this in your terminal:
git clone https://github.com/microsoft/azure-skills && cp -r azure-skills/skills/microsoft-foundry/models/deploy-model/customize ~/.claude/skills/Which AI tools does Customize work with?
It works with claude_app, claude_code, claude_api, cursor, codex, windsurf, cline, zed.
Who made Customize?
Microsoft, released under the MIT license.
Is Customize free?
Yes, it is free to use under the MIT license.
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