Azure Container Registry Cli logo

Azure Container Registry Cli

OrganizationPopular
github
azure-container-registry-cli

Manage Azure Container Registry via the az acr CLI including registries, images, cloud builds, ACR Tasks, authentication, tokens, geo-replication, and networking. Use when working with ACR, az acr commands, pushing/importing/purging container images in Azure, or when the user mentions Azure Container Registry.

Overview

Publishergithub
Repositoryawesome-copilot
Skill nameazure-container-registry-cli
Stars
39.1K
Forks
5K
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Azure Container Registry Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/azure-container-registry-cli .claude/skills/azure-container-registry-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Container Registry Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure Container Registry Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure Container Registry Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Azure Container Registry CLI

Manage Azure Container Registry (ACR) resources using the az acr command group of the Azure CLI.

CLI: az acr ships with core Azure CLI — no extension required (the acrtransfer extension is only needed for export/import pipelines).

Prerequisites

bash
# Install Azure CLI
brew install azure-cli  # macOS
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash  # Linux
winget install Microsoft.AzureCLI  # Windows

# Sign in and select subscription
az login
az account set --subscription {subscription-id}

Quick Start

bash
# Create a registry (SKU: Basic | Standard | Premium)
az acr create --resource-group {rg} --name {registry} --sku Standard

# Authenticate Docker/Podman against the registry
az acr login --name {registry}

# Build and push in the cloud — no local Docker needed
az acr build --registry {registry} --image app:v1 .

# Copy an image from another registry without pull/push
az acr import --name {registry} --source mcr.microsoft.com/hello-world:latest

# List repositories and tags
az acr repository list --name {registry} --output table
az acr repository show-tags --name {registry} --repository app --orderby time_desc

# Diagnose registry connectivity and configuration
az acr check-health --name {registry} --yes

Key Principles

  • Prefer az acr build / ACR Tasks over local docker build + docker push: builds run in Azure, work without a local daemon, and integrate with triggers.
  • Prefer az acr import to move images between registries: it is server-side, faster, and requires no local storage.
  • Never enable the admin user for production — use Microsoft Entra identities (RBAC roles AcrPull/AcrPush, or Container Registry Repository Reader/Writer on ABAC-enabled registries), repository-scoped tokens, or managed identities.
  • Premium-only features: geo-replication, private endpoints, retention policies, connected registries, agent pools. (Repository-scoped tokens work in all tiers; zone redundancy is automatic in all tiers in supported regions.)

CLI Structure

az acr
├── create / delete / list / show / update   # Registry lifecycle
├── login                  # Docker credential helper (or --expose-token)
├── check-health / check-name / show-usage   # Diagnostics & quota
├── build                  # Cloud image build (quick task)
├── run                    # Run a command / multi-step task once
├── task                   # ACR Tasks (triggers, timers, logs, runs)
├── agentpool              # Dedicated task agent pools (Premium)
├── import                 # Server-side image copy into the registry
├── repository             # List/show/delete/untag repos & tags, lock images
├── manifest               # Manifest metadata, delete, OCI referrers
├── credential             # Admin user credentials (avoid in production)
├── token / scope-map      # Repository-scoped tokens (Premium)
├── replication            # Geo-replication (Premium)
├── network-rule           # IP network rules
├── private-endpoint-connection  # Private Link approvals
├── config                 # content-trust, retention, soft-delete, ...
├── cache / credential-set # Artifact cache (pull-through cache) rules
├── webhook                # Push/delete event webhooks
├── connected-registry     # On-premises / IoT connected registries
└── export-pipeline / import-pipeline / pipeline-run  # acrtransfer extension

Reference Files

Read the relevant reference file based on the user's task. Each file contains complete command syntax and examples for its domain.

FileWhen to readCovers
references/auth-and-security.mdLogin failures, permissions, CI/CD or AKS pull accessaz acr login (incl. --expose-token), Entra RBAC roles, service principals, managed identities, --attach-acr for AKS, repository-scoped tokens & scope maps, admin user, content trust
references/build-and-tasks.mdBuilding images in Azure, automation, CI triggersaz acr build, az acr run, multi-step task YAML, az acr task (git/base-image/timer triggers, logs, runs), agent pools
references/images-and-artifacts.mdManaging repos, tags, cleanup, storage costsaz acr import, repository & manifest commands, untag vs delete, purge (acr purge), image locking, retention policy, soft delete, artifact cache, show-usage
references/networking-and-geo.mdMulti-region, private access, edge scenariosGeo-replication, zone redundancy, private endpoints, network rules, dedicated data endpoints, connected registries, registry transfer pipelines

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Azure Container Registry Cli AI skill do?

Manage Azure Container Registry via the az acr CLI including registries, images, cloud builds, ACR Tasks, authentication, tokens, geo-replication, and networking. Use when working with ACR, az acr commands, pushing/importing/purging container images in Azure, or when the user mentions Azure Container Registry.

Why use Azure Container Registry Cli on TypingMind?

Because you install it once and use it with any model. Azure Container Registry Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure Container Registry Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/azure-container-registry-cli. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Azure Container Registry Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure Container Registry Cli?

As many as you like. As long as a model supports skills, you can use Azure Container Registry Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure Container Registry Cli AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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