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帮助你跨区域与项目查询 Azure OpenAI 容量配额并推荐最佳部署位置
复制安装指令，让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "capacity" 技能： 1. 下载 https://raw.githubusercontent.com/microsoft/GitHub-Copilot-for-Azure/main/plugin/skills/microsoft-foundry/models/deploy-model/capacity/SKILL.md 2. 保存为 ~/.claude/skills/capacity/SKILL.md 3. 装好后重载技能，告诉我可以用了
帮我检查 GPT-4o 在哪些 Azure 区域有可用容量，列出每个区域的配额情况，并推荐最适合部署的 3 个区域。
返回各区域的容量与配额对比，并给出最优部署区域建议。
请在我的多个 Azure 项目中搜索 o3-mini 的可用容量，比较各项目和区域的 TPM 配额，并指出哪里最适合新部署。
输出跨项目与区域的容量分析，以及最合适的部署位置。
我需要至少 200K TPM 的模型容量，请分析哪些 Azure 区域能够满足需求，并说明每个候选区域的优缺点。
给出满足容量门槛的区域列表、对比分析和推荐结论。
Finds available Azure OpenAI model capacity across all accessible regions and projects. Recommends the best deployment location based on capacity requirements.
| Property | Description |
|---|---|
| Purpose | Find where you can deploy a model with sufficient capacity |
| Scope | All regions and projects the user has access to |
| Output | Ranked table of regions/projects with available capacity |
| Action | Read-only analysis — does NOT deploy. Hands off to preset or customize |
| Authentication | Azure CLI (az login) |
After discovery → hand off to preset or customize for actual deployment.
Pre-built scripts handle the complex REST API calls and data processing. Use these instead of constructing commands manually.
| Script | Purpose | Usage |
|---|---|---|
scripts/discover_and_rank.ps1 | Full discovery: capacity + projects + ranking | Primary script for capacity discovery |
scripts/discover_and_rank.sh | Same as above (bash) | Primary script for capacity discovery |
scripts/query_capacity.ps1 | Raw capacity query (no project matching) | Quick capacity check or version listing |
scripts/query_capacity.sh | Same as above (bash) | Quick capacity check or version listing |
az account show --query "{Subscription:name, SubscriptionId:id}" --output table
Extract model name from user prompt. If version is unknown, query available versions:
.\scripts\query_capacity.ps1 -ModelName <model-name>
./scripts/query_capacity.sh <model-name>
This lists available versions. Use the latest version unless user specifies otherwise.
Run the full discovery script with model name, version, and minimum capacity target:
.\scripts\discover_and_rank.ps1 -ModelName <model-name> -ModelVersion <version> -MinCapacity <target>
./scripts/discover_and_rank.sh <model-name> <version> <min-capacity>
💡 The script automatically queries capacity across ALL regions, cross-references with the user's existing projects, and outputs a ranked table sorted by: meets target → project count → available capacity.
After discovery identifies candidate regions, validate that the user's subscription actually has available quota in each region. Model capacity (from Phase 3) shows what the platform can support, but subscription quota limits what this specific user can deploy.
# For each candidate region from discovery results:
$usageData = az cognitiveservices usage list --location <region> --subscription $SUBSCRIPTION_ID -o json 2>$null | ConvertFrom-Json
# Check quota for each SKU the model supports
# Quota names follow pattern: OpenAI.<SKU>.<model-name>
$usageEntry = $usageData | Where-Object { $_.name.value -eq "OpenAI.<SKU>.<model-name>" }
if ($usageEntry) {
$quotaAvailable = $usageEntry.limit - $usageEntry.currentValue
} else {
$quotaAvailable = 0 # No quota allocated
}
# For each candidate region from discovery results:
usage_json=$(az cognitiveservices usage list --location <region> --subscription "$SUBSCRIPTION_ID" -o json 2>/dev/null)
# Extract quota for specific SKU+model
quota_available=$(echo "$usage_json" | jq -r --arg name "OpenAI.<SKU>.<model-name>" \
'.[] | select(.name.value == $name) | .limit - .currentValue')
Annotate discovery results:
…
分析并精简 Markdown 内容，降低 token 消耗并提升 AI 处理效率。
引导你逐步自定义 Azure OpenAI 模型部署参数与高级选项。