Azure Local Multi Rack

Organization

microsoft

azure-local-multi-rack

Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.

Overview

Publisher	microsoft
Repository	`GitHub-Copilot-for-Azure`
Skill name	`azure-local-multi-rack`
Stars	259
Forks	215
Bundled files	9
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
9 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Azure Local Multi Rack AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-local-skills/skills/azure-local-multi-rack
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-local-skills/skills/azure-local-multi-rack

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git /tmp/GitHub-Copilot-for-Azure
mkdir -p .claude/skills
cp -r /tmp/GitHub-Copilot-for-Azure/plugins/azure-local-skills/skills/azure-local-multi-rack .claude/skills/azure-local-multi-rack

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Local Multi Rack in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure Local Multi Rack on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure Local Multi Rack is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Azure Local Multi-Rack

Multi-rack is in preview — say so, and confirm availability from the docs before committing to a design.

Quick Reference

Property	Value
Best for	Rack-scale Azure Local: 100+ machines, preintegrated racks, SAN, managed fabric
Scale	Minimum four racks — one aggregation rack plus three or more compute racks
Providers	`Microsoft.NetworkCloud`, `Microsoft.ManagedNetworkFabric`, `Microsoft.AzureStackHCI`
CLI	`az networkcloud`, `az networkfabric`, `az stack-hci-vm`
Related skill	`azure-local` for standard 1-16 node and rack-aware deployments

When to Use This Skill

Use when the deployment is multi-rack / rack scale: preintegrated racks, an aggregation rack, a Network Fabric Controller, a Cluster Manager, SAN storage, or the networkcloud / managednetworkfabric CLI extensions.

Do not use for standard Azure Local (1-16 node hyperconverged, up to 64 disaggregated) or rack-aware clusters — hand off to the azure-local skill. If the scale is unclear, ask first: the two have separate, non-interchangeable procedures for the same-sounding tasks (logical networks, VM creation, NSGs).

MCP Tools

No dedicated MCP namespace. Use generic Azure MCP tools: mcp_azure_mcp_extension_cli_generate (confirm networkcloud/networkfabric extensions first), mcp_azure_mcp_monitor (needs Log Analytics), mcp_azure_mcp_resourcehealth (partial; not fabric or SAN health), mcp_azure_mcp_documentation (multi-rack articles only — standard Azure Local pages do not apply).

Details: cli-and-prereqs.

Workflow

Confirm this is multi-rack, not standard Azure Local — see When to Use.
Plan/deploy -> plan-and-deploy
VMs, AKS, images, disks -> workload-management
Fabric, isolation domains, load balancers, NSGs -> networking
Monitoring, metrics, serial console, failures -> operate-and-monitor

Read the matched workflow first and use docs-map. Start read-only. Ask before fabric changes, isolation domain edits, VM power/delete operations, or anything touching the aggregation rack or SAN.

Error Handling

Scenario	Remediation
Scale unknown	Ask whether the deployment is multi-rack or standard before recommending procedures.
Standard Azure Local detected	Hand off to the `azure-local` skill; multi-rack procedures do not apply.
Missing CLI extension	Install per cli-and-prereqs before running commands.
Risky fabric or SAN change	Stop and follow safety-rules.
Doc URL 404/redirect	Search Learn for the title, scoped to multi-rack deployments of Azure Local.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Azure Local Multi Rack AI skill do?

Why use Azure Local Multi Rack on TypingMind?

Because you install it once and use it with any model. Azure Local Multi Rack is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure Local Multi Rack in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-local-skills/skills/azure-local-multi-rack. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Azure Local Multi Rack?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure Local Multi Rack?

As many as you like. As long as a model supports skills, you can use Azure Local Multi Rack with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure Local Multi Rack AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Azure Local Multi-Rack

Quick Reference

When to Use This Skill

MCP Tools

Workflow

Error Handling

Bundled files

Frequently asked questions

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