Discover Azure OpenAI model capacity across regions and projects via REST.
npx skills add https://github.com/jaypatrick/skills --skill capacity-jaypatrick
Please help me install this Agent Skill. Skill: capacity Source: https://github.com/jaypatrick/skills/tree/main/microsoft-foundry/models/deploy-model/capacity Command: npx skills add https://github.com/jaypatrick/skills --skill capacity-jaypatrick
Discovers available Azure OpenAI model capacity across regions and projects, analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements.
Run the capacity discovery script to locate the best Azure OpenAI region with sufficient capacity for your model.
High-intent search queries and answers about installing and using this skill.
To find the best Azure OpenAI region for capacity, you can run a discovery script that queries model capacities via REST and cross-references AI projects in your subscription to identify available TPM.
You can check Azure OpenAI quota limits across multiple subscriptions by running a script that annotates per-region results with quota status, ensuring your deployment stays within subscription limits.
Yes, you can rank Azure OpenAI regions by available TPM capacity. The tool checks per-region quotas and applies region ranking to recommend optimal deployment locations based on your capacity requirements.
To discover Azure OpenAI model capacity across regions, you need the Azure CLI (az), jq, and python3 installed in your environment to execute the discovery and quota check scripts.
Azure OpenAI deployments often fail due to region capacity limits when available TPM is exhausted. Analyzing quota status and comparing availability across projects helps identify regions with sufficient capacity.
Yes, after discovering available Azure OpenAI model capacity and ranking regions, the tool provides guidance on when to hand off to preset or customize deployment workflows for your chosen location.
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