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@b8a1c66
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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 (use customize), PTU deployments (use customize).

Use this Skill: https://skilld.dev/gh/microsoft/skills/preset

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referencesworkflow.md

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Preset Deployment Workflow — Step-by-Step

Condensed implementation reference for preset (optimal region) model deployment. See SKILL.md for overview.

Table of Contents: Phase 1: Verify Authentication · Phase 2: Get Current Project · Phase 3: Get Model Name · Phase 4: Check Current Region Capacity · Phase 5: Query Multi-Region Capacity · Phase 6: Select Region and Project · Phase 7: Deploy Model


Phase 1: Verify Authentication

az account show --query "{Subscription:name, User:user.name}" -o table

If not logged in: az login

Switch subscription:

az account list --query "[].[name,id,state]" -o table
az account set --subscription <subscription-id>

Phase 2: Get Current Project

Read PROJECT_RESOURCE_ID from env or prompt user. Format: /subscriptions/{sub-id}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project}

Parse ARM ID components:

SUBSCRIPTION_ID=$(echo "$PROJECT_RESOURCE_ID" | sed -n 's|.*/subscriptions/\([^/]*\).*|\1|p')
RESOURCE_GROUP=$(echo "$PROJECT_RESOURCE_ID" | sed -n 's|.*/resourceGroups/\([^/]*\).*|\1|p')
ACCOUNT_NAME=$(echo "$PROJECT_RESOURCE_ID" | sed -n 's|.*/accounts/\([^/]*\)/projects.*|\1|p')
PROJECT_NAME=$(echo "$PROJECT_RESOURCE_ID" | sed -n 's|.*/projects/\([^/?]*\).*|\1|p')

Verify project exists and get region:

az account set --subscription "$SUBSCRIPTION_ID"

PROJECT_REGION=$(az cognitiveservices account show \
  --name "$PROJECT_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --query location -o tsv)

Phase 3: Get Model Name

If model not provided as parameter, list available models:

az cognitiveservices account list-models \
  --name "$PROJECT_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --query "[].name" -o tsv | sort -u

Get versions for selected model:

az cognitiveservices account list-models \
  --name "$PROJECT_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --query "[?name=='$MODEL_NAME'].{Name:name, Version:version, Format:format}" \
  -o table

Phase 4: Check Current Region Capacity

CAPACITY_JSON=$(az rest --method GET \
  --url "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/providers/Microsoft.CognitiveServices/locations/$PROJECT_REGION/modelCapacities?api-version=2024-10-01&modelFormat=OpenAI&modelName=$MODEL_NAME&modelVersion=$MODEL_VERSION")

CURRENT_CAPACITY=$(echo "$CAPACITY_JSON" | jq -r '.value[] | select(.properties.skuName=="GlobalStandard") | .properties.availableCapacity')

If CURRENT_CAPACITY > 0 → skip to Phase 7. Otherwise continue to Phase 5.


Phase 5: Query Multi-Region Capacity

ALL_REGIONS_JSON=$(az rest --method GET \
  --url "https://management.azure.com/subscriptions/$SUBSCRIPTION_ID/providers/Microsoft.CognitiveServices/modelCapacities?api-version=2024-10-01&modelFormat=OpenAI&modelName=$MODEL_NAME&modelVersion=$MODEL_VERSION")

Extract available regions (capacity > 0):

AVAILABLE_REGIONS=$(echo "$ALL_REGIONS_JSON" | jq -r '.value[] | select(.properties.skuName=="GlobalStandard" and .properties.availableCapacity > 0) | "\(.location)|\(.properties.availableCapacity)"')

Extract unavailable regions:

UNAVAILABLE_REGIONS=$(echo "$ALL_REGIONS_JSON" | jq -r '.value[] | select(.properties.skuName=="GlobalStandard" and (.properties.availableCapacity == 0 or .properties.availableCapacity == null)) | "\(.location)|0"')

If no regions have capacity, defer to the quota skill for increase requests. Suggest checking existing deployments or trying alternative models like gpt-4o-mini.


Phase 6: Select Region and Project

Present available regions to user. Store selection as SELECTED_REGION.

Find projects in selected region:

PROJECTS_IN_REGION=$(az cognitiveservices account list \
  --query "[?kind=='AIProject' && location=='$SELECTED_REGION'].{Name:name, ResourceGroup:resourceGroup}" \
  --output json)

If no projects exist — create new:

az cognitiveservices account create \
  --name "$HUB_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --location "$SELECTED_REGION" \
  --kind "AIServices" \
  --sku "S0" --yes

az cognitiveservices account create \
  --name "$NEW_PROJECT_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --location "$SELECTED_REGION" \
  --kind "AIProject" \
  --sku "S0" --yes

Phase 7: Deploy Model

Generate unique deployment name using scripts/generate_deployment_name.sh:

DEPLOYMENT_NAME=$(bash scripts/generate_deployment_name.sh "$ACCOUNT_NAME" "$RESOURCE_GROUP" "$MODEL_NAME")

Calculate capacity — 50% of available, minimum 50 TPM:

SELECTED_CAPACITY=$(echo "$ALL_REGIONS_JSON" | jq -r ".value[] | select(.location==\"$SELECTED_REGION\" and .properties.skuName==\"GlobalStandard\") | .properties.availableCapacity")
DEPLOY_CAPACITY=$(( SELECTED_CAPACITY / 2 ))
[ "$DEPLOY_CAPACITY" -lt 50 ] && DEPLOY_CAPACITY=50

Create deployment:

az cognitiveservices account deployment create \
  --name "$ACCOUNT_NAME" \
  --resource-group "$RESOURCE_GROUP" \
  --deployment-name "$DEPLOYMENT_NAME" \
  --model-name "$MODEL_NAME" \
  --model-version "$MODEL_VERSION" \
  --model-format "OpenAI" \
  --sku-name "GlobalStandard" \
  --sku-capacity "$DEPLOY_CAPACITY"

Monitor with az cognitiveservices account deployment show ... --query "properties.provisioningState" until Succeeded or Failed.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub1mo

    This skill facilitates the deployment of Azure OpenAI models to optimal regions using the Azure CLI and official Azure management APIs. It follows standard practices for cloud resource provisioning within the Azure ecosystem and does not exhibit any suspicious behaviors.

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    Risk: LOW · No issues

Signed by skilld at b8a1c66. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

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metadata
{
  "author": "Microsoft",
  "version": "1.0.1"
}

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