Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (us
SkillScore91Maintained
Automatic
◆AI Engineer pack
Last verified 8/9/2026
What it changes
Passed 20 of 22 test cases with the skill, and 14 of 22 without it.
Without skill64%
With skill91%
Checks it passed that the model alone missed
The response specifies a minimum floor of 50 TPM.
The environment variable named is PROJECT_RESOURCE_ID.
The response specifies using 50% of available capacity.
and 6 more in the full report
6 fixed14 passed either way2 still failing0 broke
Pass-rate lift
+27 pp
Tokens
+17%
Agent turns
0%
Response time
-43%
Model gemini-3.6-flashMeasured 8/9/2026v220 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 6
Prompt
What action is taken automatically if `az cognitiveservices account deployment create` fails with an error indicating the deployment name already exists?
What was checked, without and with the skill
Checked
Without skill
With skill
The response states that a suffix is appended to generate a unique deployment name.
Missed
Passed
case-15 · gemini-3.6-flash · 8/9/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md94 lines3 files
Deploy Model to Optimal Region
Automates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.
What This Skill Does
Verifies Azure authentication and project scope
Checks capacity in current project's region
If no capacity: analyzes all regions and shows available alternatives
Filters projects by selected region
Supports creating new projects if needed
Deploys model with GlobalStandard SKU
Monitors deployment progress
Prerequisites
Azure CLI installed and configured
Active Azure subscription with Cognitive Services read/create permissions
Microsoft Foundry project resource ID (PROJECT_RESOURCE_ID env var or provided interactively)
Found in: Microsoft Foundry portal → Project → Overview → Resource ID
Quick Workflow
Fast Path (Current Region Has Capacity)
1. Check authentication → 2. Get project → 3. Check current region capacity
→ 4. Deploy immediately
Alternative Region Path (No Capacity)
1. Check authentication → 2. Get project → 3. Check current region (no capacity)
→ 4. Query all regions → 5. Show alternatives → 6. Select region + project
→ 7. Deploy