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Localized reading guide

capacityPurpose, usage and source

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

Source retrieved:

Source repository
microsoft/skills
SKILL.md
.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/capacity/SKILL.md
Repository stars
3,157
Repository updated
2026-10-31
Categories
Cloud
Last collected

License: License file needs review

Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.

The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.

What this Skill does

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

How the upstream workflow works

When to Use This Skill

✅ User asks "where can I deploy gpt-4o?" ✅ User specifies a capacity target: "find a region with 10K TPM for gpt-4o" ✅ User wants to compare availability: "which regions have gpt-4o available?" ✅ User got a quota error and needs to find an alternative location

Upstream passage · L24 ↗

Capacity Discovery

Finds available Azure OpenAI model capacity across all accessible regions and projects. Recommends the best deployment location based on capacity requirements.

Upstream passage · L10 ↗

Scripts

Pre-built scripts handle the complex REST API calls and data processing. Use these instead of constructing commands manually.

Upstream passage · L34 ↗

Requirements and setup

Upstream passage · bash ↗
az account show --query "{Subscription:name, SubscriptionId:id}" --output table

Limits and quality checks

No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.

Start with a safe trial

  1. Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
  2. Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
  3. Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
  4. Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.

Skill format and directory specification ↗

Read further in the source

Translation and scope

This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.

This introduction refers to the pinned version below; current repository activity and collection time are shown separately.

Source retrieved
Source commit
00d66a64919edca5bca2c673373444e36a4b5461
Source SHA-256
91b3ce958de44f728453572747504e8c9146f119892aa690546fd19f8d96a344
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