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Azure AI Services

Official
microsoft·vlatest·cloud

Official microsoft skill covering Azure, AI for deploying and managing cloud infrastructure.

Repositoryskills.sh

Install on your platform

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

  1. 1

    Run this in your project

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

  2. 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

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-ai/SKILL.md
Scanned
17 files, 594 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 skill enables integration with Microsoft's Azure platform to leverage AI capabilities such as natural language processing, computer vision, and machine learning services. It allows developers to build intelligent applications using pre-built models and APIs hosted on Azure.

When to use it

  • To deploy AI-powered chatbots or virtual assistants within enterprise applications.
  • For image recognition tasks in apps that require analyzing visual content.
  • When building predictive analytics tools that rely on machine learning models.

Key capabilities

  • Access to pre-trained AI models for text, speech, and vision.
  • Integration with Azure Cognitive Services like Text Analytics and Computer Vision.
  • Support for deploying custom machine learning models on Azure.

Example prompts

  • "Create a chatbot using Azure AI services that can answer customer support queries."
  • "Implement image classification in my app by connecting to the Azure Computer Vision API."
  • "Train and deploy a custom machine learning model on Azure for sales forecasting."

Tips & gotchas

  • Ensure you have an active Azure subscription and proper authentication credentials.
  • Be mindful of usage limits and costs associated with Azure AI services, especially for high-volume applications.