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Checked
mindrally·vlatest·cloud·Apache-2.0

Automates Azure resource provisioning, configuration, and monitoring tasks using MindRally's intelligent automation engine.

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 mindrally/skills --skill 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

mindrally

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 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 mindrally/skills at 7682ca7771.

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

Commit
7682ca7771
Manifest
azure/SKILL.md
Scanned
1 file, 77 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

The Azure skill enables AI agents to interact directly with Microsoft Azure cloud infrastructure, allowing for automated resource management and deployment. It provides programmatic access to core services like virtual machines, storage accounts, and networking components within the Azure ecosystem.

When to use it

  • Automating the provisioning of new Virtual Machines or App Services for development environments.
  • Managing blob storage lifecycles by creating containers and setting retention policies.
  • Deploying containerized applications using Azure Kubernetes Service (AKS) clusters.
  • Monitoring resource usage and scaling infrastructure based on demand.

Key capabilities

  • Authentication against Microsoft Entra ID (formerly Azure AD).
  • Creation and deletion of compute resources including VMs and containers.
  • Management of storage accounts, blobs, and file shares.
  • Configuration of networking elements like virtual networks and load balancers.

Example prompts

  • "Provision a new Linux-based Virtual Machine in the East US region with 4 vCPUs."
  • "Create a secure blob container named 'app-backups' with private access settings."
  • "Deploy my Docker image to an existing Azure Kubernetes Service cluster."

Tips & gotchas

Ensure your AI agent has valid credentials with appropriate RBAC permissions before attempting resource creation. Be mindful of cost implications when automating the deployment of long-running services like virtual machines.