Aks Gpu Inference

Organization

microsoft

aks-gpu-inference

Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).

Overview

Publisher	microsoft
Repository	`GitHub-Copilot-for-Azure`
Skill name	`aks-gpu-inference`
Stars	259
Forks	215
Bundled files	5
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.
5 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 Aks Gpu Inference 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/aks-skills/skills/aks-gpu-inference
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/aks-skills/skills/aks-gpu-inference

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/aks-skills/skills/aks-gpu-inference .claude/skills/aks-gpu-inference

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

Use it in TypingMind

Enable Aks Gpu Inference 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 Aks Gpu Inference 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 Aks Gpu Inference 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.

AKS GPU Inference Day-2

Quick Reference

Property	Value
Best for	AKS GPU/KAITO failures
Evidence	Bound target, events/status, `gpuProfile`, DCGM

When to Use This Skill

Use for scheduling, VRAM/OOM, KAITO readiness, and workload scaling. Route exclusions as described above.

MCP Tools

Use a fitting host-advertised Azure read or the references' read-only queries.

Host Capability Gate

Before executing any referenced pipeline, verify that the host authorizes the required shell and kubectl/az commands against the bound target. File-backed collection also requires approved artifact storage and access to any bundled files it uses. A governed Azure CLI tool alone does not establish these capabilities. Equivalent host reads may replace commands only where their advertised schemas provide the required evidence.

If execution is unavailable or prohibited, say so and analyze supplied or redacted events, status, logs, and metrics, or give the operator a scoped collection plan. State which reads did not run and leave conclusions requiring missing evidence unconfirmed. Never route kubectl through Azure MCP or bypass host policy. The authorization requirements below still apply.

Workflow

Bind subscription, cluster, kube context, pool, and affected resource.
Capture exact events/status and observed gpuProfile; state which reads ran.
Route to scheduling, observability, KAITO, or scaling.
Separate container/host OOM from device-allocation failures. For OOMKilled, correlate container memory limits/usage and node conditions. For Managed+Install device-memory evidence, use the exporter on port 19400 and incident-window FB_USED/FB_FREE; sizing tables do not establish a cause.
For KAITO not-ready, warn that Workspace deletion leaves its GPU pools; cleanup is separate and needs explicit authorization.
Report evidence, confidence, missing evidence, and owner handoff.

Require explicit authorization before scaling, cordon/drain, deletion, add-on enablement, or monitoring mutation.

Error Handling

Condition	Response
Missing/contradictory evidence	Mark unconfirmed; request the owner/read
Unknown profile	Preserve evidence; do not prescribe stack repair
Mutation required	Propose separately and wait for authorization

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 Aks Gpu Inference AI skill do?

Why use Aks Gpu Inference on TypingMind?

Because you install it once and use it with any model. Aks Gpu Inference 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 Aks Gpu Inference in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/aks-skills/skills/aks-gpu-inference. 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 Aks Gpu Inference?

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 Aks Gpu Inference?

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

Is the Aks Gpu Inference 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

AKS GPU Inference Day-2

Quick Reference

When to Use This Skill

MCP Tools

Host Capability Gate

Workflow

Error Handling

Bundled files

Frequently asked questions

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