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Deploying On Azure

Listed
ancoleman·vlatest·cloud·MIT

Automates Azure resource deployment from code, streamlining infrastructure provisioning and reducing manual errors.

Repository

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 ancoleman/ai-design-components --skill deploying-on-azure -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

ancoleman

Taken from the source listing. We haven't verified who controls this account.

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 3 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: cognitiveservices.azure.com, myaisearch.search.windows.net, myopenai.openai.azure.com.

    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.

    Hosts contacted

    cognitiveservices.azure.comundeclaredmyopenai.openai.azure.comundeclaredmyaisearch.search.windows.netundeclared

    What it found

    • skills/deploying-on-azure/examples/sdk/python/azure-openai-rag.py:82contacts cognitiveservices.azure.com
      "https://cognitiveservices.azure.com/.default"
    • skills/deploying-on-azure/examples/sdk/python/azure-openai-rag.py:314contacts myopenai.openai.azure.com
      openai_endpoint="https://myopenai.openai.azure.com",
    • skills/deploying-on-azure/examples/sdk/python/azure-openai-rag.py:315contacts myaisearch.search.windows.net
      search_endpoint="https://myaisearch.search.windows.net",

  • 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 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 ancoleman/ai-design-components at 76551b7b19.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
76551b7b19
Manifest
skills/deploying-on-azure/SKILL.md
Scanned
13 files, 3,975 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

This skill allows AI agents to deploy applications and services onto the Microsoft Azure cloud platform. It handles tasks such as creating resource groups, configuring virtual machines, and managing application deployments using standard Azure deployment practices. The agent can automate infrastructure provisioning and software releases within an Azure environment.

When to use it

  • Automating the deployment of a new web application to Azure.
  • Creating a staging environment for testing code changes before production release.
  • Provisioning virtual machines with specific configurations for development or testing purposes.
  • Managing existing Azure resources, such as scaling up or down virtual machine instances.

Key capabilities

  • Resource Group Creation
  • Virtual Machine Configuration
  • Application Deployment
  • Infrastructure Provisioning
  • Azure Resource Management

Example prompts

  • "Deploy a new web application named 'MyWebApp' to Azure using the latest version of the code."
  • "Create an Azure resource group in the East US region with the name 'DevResources'."
  • “Provision a Windows Server 2022 virtual machine with 8GB RAM and deploy IIS.”

Tips & gotchas

The agent requires appropriate Azure credentials (e.g., service principal) to access and manage resources. Ensure these are configured correctly before attempting deployments, as missing or incorrect permissions will prevent successful execution.