Azure AI Gateway

Name: Azure AI Gateway
Author: microsoft

Official

microsoft·vlatest·cloud

Securely manage and monitor your Azure AI services through a centralized gateway for enhanced control.

Repository skills.sh

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add microsoft/github-copilot-for-azure --skill azure-aigateway --full-depth -a claude-code

Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

microsoft

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned 11 Oct 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned microsoft/github-copilot-for-azure at f2526ae581.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: f2526ae581
Manifest: plugins/azure-skills/skills/azure-aigateway/SKILL.md
Scanned: 10 files, 1,087 lines

This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.

What each check looks for →

About this skill

What it does

The Azure AI Gateway skill enables developers to integrate and manage AI models within the Azure cloud environment. It provides tools for deploying, scaling, and securing AI services, allowing seamless interaction between AI models and applications.

When to use it

Deploying machine learning models in production environments on Azure.
Managing multiple AI models with a unified API interface.
Securing AI endpoints with authentication and access control features.

Key capabilities

Model deployment and management
Unified API for interacting with AI services
Authentication and security controls
Scalability for handling high traffic loads

Example prompts

"Deploy my trained model to Azure using the AI Gateway."
"Set up authentication for the AI endpoint in Azure."
"Scale the AI service to handle 10,000 concurrent requests."

Tips & gotchas

Ensure you have an active Azure subscription and necessary permissions before deployment.
Monitor resource usage regularly to avoid unexpected costs from scaling operations.