Azure Skills Plugin is an agent plugin that packages Azure-specific guidance with MCP server configurations for carrying out Azure work. Coding agents use it to plan, deploy, troubleshoot, monitor, govern, and optimize Azure applications and services. The catalogue entries are the plugin's skills, instructions, and execution integrations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add microsoft/azure-skills --skill aks-gpu-inferencegit clone --depth 1 https://github.com/microsoft/azure-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/azure-skills/aks-gpu-inference)<a href="https://agentmods.dev/skills/microsoft/azure-skills/aks-gpu-inference"><img src="https://agentmods.dev/badge/skills/microsoft/azure-skills/aks-gpu-inference/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/azure-skills/aks-gpu-inference"><img src="https://agentmods.dev/badge/skills/microsoft/azure-skills/aks-gpu-inference.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00114 | $0.00688 |
| Opus 5.5 | $0.00046 | $0.00275 |
| Sonnet 5.5 | $0.00023 | $0.00138 |
| Haiku 4.5 | $0.00011 | $0.00069 |
Grade A, and why
aks-gpu-inference scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to aks-gpu-inference — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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-windowFB_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.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 69 lines · 114 tokens per session scan A 0968850f574d
aks-gpu-inference is a skill published in the GitHub repository microsoft/azure-skills (1,572 stars, last pushed yesterday), licensed MIT. It adds 114 tokens to every session and 688 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to aks-gpu-inference, differing in 0 lines, and is treated as a copy.
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