Azure Deploy

OrganizationPopular

microsoft

azure-deploy

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

Overview

Publisher	microsoft
Repository	`azure-skills`
Skill name	`azure-deploy`
Stars	1.5K
Forks	246
Bundled files	34
License	MIT
Links	Skill source Repository

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.
34 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by microsoft on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/microsoft/azure-skills.git /tmp/azure-skills
mkdir -p .claude/skills
cp -r /tmp/azure-skills/skills/azure-deploy .claude/skills/azure-deploy

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Deploy 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 Deploy 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 Deploy 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 Deploy

AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE

PREREQUISITE: The azure-validate skill MUST be invoked and completed with status Validated BEFORE executing this skill.

⛔ STOP — PREREQUISITE CHECK REQUIRED Before proceeding, verify BOTH prerequisites are met:

azure-prepare was invoked and completed → .azure/deployment-plan.md exists

azure-validate was invoked and passed → plan status = Validated

If EITHER is missing, STOP IMMEDIATELY:

No plan? → Invoke azure-prepare skill first

Status not Validated? → Invoke azure-validate skill first

⛔ DO NOT MANUALLY UPDATE THE PLAN STATUS

You are FORBIDDEN from changing the plan status to Validated yourself. Only the azure-validate skill is authorized to set this status after running actual validation checks. If you update the status without running validation, deployments will fail.

DO NOT ASSUME the app is ready. DO NOT SKIP validation to save time. Skipping steps causes deployment failures. The complete workflow ensures success:

azure-prepare → azure-validate → azure-deploy

Triggers

Activate this skill when user wants to:

Execute deployment of an already-prepared application (azure.yaml and infra/ exist)
Push updates to an existing Azure deployment
Run azd up, azd deploy, or az deployment on a prepared project
Ship already-built code to production
Deploy an application that already includes API Management (APIM) gateway infrastructure

Scope: This skill executes deployments. It does not create applications, generate infrastructure code, or scaffold projects. For those tasks, use azure-prepare.

APIM / AI Gateway: Use this skill to deploy applications whose APIM/AI gateway infrastructure was already created during azure-prepare. For creating or changing APIM resources, see APIM deployment guide. For AI governance policies, invoke azure-aigateway skill.

Rules

Run after azure-prepare and azure-validate
.azure/deployment-plan.md must exist with status Validated
Pre-deploy checklist required — Pre-Deploy Checklist
⛔ Destructive actions require ask_user — global-rules
Scope: deployment execution only — This skill owns execution of azd up, azd deploy, terraform apply, and az deployment commands. These commands are run through this skill's error recovery and verification pipeline.

Steps

#	Action	Reference
1	Check Plan — Read `.azure/deployment-plan.md`, verify status = `Validated` AND Validation Proof section is populated	`.azure/deployment-plan.md`
2	Pre-Deploy Checklist — MUST complete ALL steps	Pre-Deploy Checklist
3	Load Recipe — Based on `recipe.type` in `.azure/deployment-plan.md`	recipes/README.md
4	RBAC Health Check — For Container Apps + ACR with managed identity: run `azd provision --no-prompt`, then verify `AcrPull` role has propagated before proceeding (see checklist)	Pre-Deploy Checklist — Container Apps RBAC
5	Execute Deploy — Follow recipe steps	Recipe README
6	Post-Deploy — Configure SQL managed identity and apply EF migrations if applicable	Post-Deployment
7	Handle Errors — See recipe's `errors.md`	—
8	Verify Success — Confirm deployment completed and endpoints are accessible	Verification
9	Live Role Verification — Query Azure to confirm provisioned RBAC roles are correct and sufficient	live-role-verification.md
10	Report Results — Present deployed endpoint URLs to the user as fully-qualified `https://` links	Verification

⛔ URL FORMAT RULE

When presenting endpoint URLs to the user, you MUST always use fully-qualified URLs with the https:// scheme (e.g. https://myapp.azurewebsites.net, not myapp.azurewebsites.net). Many Azure CLI commands return bare hostnames without a scheme — always prepend https:// before presenting them.

⛔ VALIDATION PROOF CHECK

When checking the plan, verify the Validation Proof section (Section 7) contains actual validation results with commands run and timestamps. If this section is empty, validation was bypassed — invoke azure-validate skill first.

SDK Quick References

Azure Developer CLI: azd
Azure Identity: Python | .NET | TypeScript | Java

MCP Tools

Tool	Purpose
`mcp_azure_mcp_subscription_list`	List available subscriptions
`mcp_azure_mcp_group_list`	List resource groups in subscription
`mcp_azure_mcp_azd`	Execute AZD commands
`azure__role`	List role assignments for live RBAC verification (step 9)

References

Troubleshooting - Common issues and solutions
Post-Deployment Steps - SQL + EF Core setup

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 Deploy AI skill do?

Why use Azure Deploy on TypingMind?

Because you install it once and use it with any model. Azure Deploy 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 Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/azure-skills/tree/main/skills/azure-deploy. 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 Deploy?

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 Deploy?

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

Is the Azure Deploy AI skill free?

Yes. It is published on GitHub by microsoft 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Azure Deploy

Triggers

Rules

Steps

SDK Quick References

MCP Tools

References

Bundled files

Frequently asked questions

Related AI Skills

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