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Azure Verified Modules

Organization
hashicorp
azure-verified-modules

Azure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.

Overview

Publisherhashicorp
Repositoryagent-skills
Skill nameazure-verified-modules
Stars
880
Forks
130
Bundled files
Instructions only
LicenseMPL-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Azure Verified Modules 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.
    https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/azure-verified-modules
  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/hashicorp/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/plugins/terraform/skills/azure-verified-modules .claude/skills/azure-verified-modules
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Verified Modules 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 Verified Modules 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 Verified Modules 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 Verified Modules (AVM) Requirements

This guide covers the mandatory requirements for Azure Verified Modules certification. These requirements ensure consistency, quality, and maintainability across Azure Terraform modules.

References:

Table of Contents


Module Cross-Referencing

Severity: MUST | Requirement: TFFR1

When building Resource or Pattern modules, module owners MAY cross-reference other modules. However:

  • Modules MUST be referenced using HashiCorp Terraform registry reference to a pinned version
    • Example: source = "Azure/xxx/azurerm" with version = "1.2.3"
  • Modules MUST NOT use git references (e.g., git::https://xxx.yyy/xxx.git or github.com/xxx/yyy)
  • Modules MUST NOT contain references to non-AVM modules

Azure Provider Requirements

Severity: MUST | Requirement: TFFR3

Authors MUST only use the following Azure providers:

ProviderMin VersionMax Version
azapi>= 2.0< 3.0
azurerm>= 4.0< 5.0

Requirements:

  • Authors MAY select either Azurerm, Azapi, or both providers
  • MUST use required_providers block to enforce provider versions
  • SHOULD use pessimistic version constraint operator (~>)

Example:

hcl
terraform {
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 4.0"
    }
    azapi = {
      source  = "Azure/azapi"
      version = "~> 2.0"
    }
  }
}

Code Style Standards

Lower snake_casing

Severity: MUST | Requirement: TFNFR4

MUST use lower snake_casing for:

  • Locals
  • Variables
  • Outputs
  • Resources (symbolic names)
  • Modules (symbolic names)

Example: snake_casing_example

Resource & Data Source Ordering

Severity: SHOULD | Requirement: TFNFR6

  • Resources that are depended on SHOULD come first
  • Resources with dependencies SHOULD be defined close to each other

Count & for_each Usage

Severity: MUST | Requirement: TFNFR7

  • Use count for conditional resource creation
  • MUST use map(xxx) or set(xxx) as resource's for_each collection
  • The map's key or set's element MUST be static literals

Example:

hcl
resource "azurerm_subnet" "pair" {
  for_each             = var.subnet_map  # map(string)
  name                 = "${each.value}-pair"
  resource_group_name  = azurerm_resource_group.example.name
  virtual_network_name = azurerm_virtual_network.example.name
  address_prefixes     = ["10.0.1.0/24"]
}

Resource & Data Block Internal Ordering

Severity: SHOULD | Requirement: TFNFR8

Order within resource/data blocks:

  1. Meta-arguments (top):

    • provider
    • count
    • for_each
  2. Arguments/blocks (middle, alphabetical):

    • Required arguments
    • Optional arguments
    • Required nested blocks
    • Optional nested blocks
  3. Meta-arguments (bottom):

    • depends_on
    • lifecycle (with sub-order: create_before_destroy, ignore_changes, prevent_destroy)

Separate sections with blank lines.

Module Block Ordering

Severity: SHOULD | Requirement: TFNFR9

Order within module blocks:

  1. Top meta-arguments:

    • source
    • version
    • count
    • for_each
  2. Arguments (alphabetical):

    • Required arguments
    • Optional arguments
  3. Bottom meta-arguments:

    • depends_on
    • providers

Lifecycle ignore_changes Syntax

Severity: MUST | Requirement: TFNFR10

The ignore_changes attribute MUST NOT be enclosed in double quotes.

Good:

hcl
lifecycle {
  ignore_changes = [tags]
}

Bad:

hcl
lifecycle {
  ignore_changes = ["tags"]
}

Null Comparison for Conditional Creation

Severity: SHOULD | Requirement: TFNFR11

For parameters requiring conditional resource creation, wrap with object type to avoid "known after apply" issues during plan stage.

Recommended:

hcl
variable "security_group" {
  type = object({
    id = string
  })
  default = null
}

Dynamic Blocks for Optional Nested Objects

Severity: MUST | Requirement: TFNFR12

Nested blocks under conditions MUST use this pattern:

hcl
dynamic "identity" {
  for_each = <condition> ? [<some_item>] : []

  content {
    # block content
  }
}

Default Values with coalesce/try

Severity: SHOULD | Requirement: TFNFR13

Good:

hcl
coalesce(var.new_network_security_group_name, "${var.subnet_name}-nsg")

Bad:

hcl
var.new_network_security_group_name == null ? "${var.subnet_name}-nsg" : var.new_network_security_group_name

Provider Declarations in Modules

Severity: MUST | Requirement: TFNFR27

  • provider MUST NOT be declared in modules (except for configuration_aliases)
  • provider blocks in modules MUST only use alias
  • Provider configurations SHOULD be passed in by module users

Variable Requirements

Not Allowed Variables

Severity: MUST | Requirement: TFNFR14

Module owners MUST NOT add variables like enabled or module_depends_on to control entire module operation. Boolean feature toggles for specific resources are acceptable.

Variable Definition Order

Severity: SHOULD | Requirement: TFNFR15

Variables SHOULD follow this order:

  1. All required fields (alphabetical)
  2. All optional fields (alphabetical)

Variable Naming Rules

Severity: SHOULD | Requirement: TFNFR16

Variables with Descriptions

Severity: SHOULD | Requirement: TFNFR17

  • description SHOULD precisely describe the parameter's purpose and expected data type
  • Target audience is module users, not developers
  • For object types, use HEREDOC format

Variables with Types

Severity: MUST | Requirement: TFNFR18

  • type MUST be defined for every variable
  • type SHOULD be as precise as possible
  • any MAY only be used with adequate reasons
  • Use bool instead of string/number for true/false values
  • Use concrete object instead of map(any)

Sensitive Data Variables

Severity: SHOULD | Requirement: TFNFR19

If a variable's type is object and contains sensitive fields, the entire variable SHOULD be sensitive = true, or extract sensitive fields into separate variables.

Non-Nullable Defaults for Collections

Severity: SHOULD | Requirement: TFNFR20

Nullable SHOULD be set to false for collection values (sets, maps, lists) when using them in loops. For scalar values, null may have semantic meaning.

Discourage Nullability by Default

Severity: MUST | Requirement: TFNFR21

nullable = true MUST be avoided unless there's a specific semantic need for null values.

Avoid sensitive = false

Severity: MUST | Requirement: TFNFR22

sensitive = false MUST be avoided (this is the default).

Sensitive Default Value Conditions

Severity: MUST | Requirement: TFNFR23

A default value MUST NOT be set for sensitive inputs (e.g., default passwords).

Handling Deprecated Variables

Severity: MUST | Requirement: TFNFR24

  • Move deprecated variables to deprecated_variables.tf
  • Annotate with DEPRECATED at the beginning of description
  • Declare the replacement's name
  • Clean up during major version releases

Output Requirements

Additional Terraform Outputs

Severity: SHOULD | Requirement: TFFR2

Authors SHOULD NOT output entire resource objects as these may contain sensitive data and the schema can change with API or provider versions.

Best Practices:

  • Output computed attributes of resources as discrete outputs (anti-corruption layer pattern)
  • SHOULD NOT output values that are already inputs (except name)
  • Use sensitive = true for sensitive attributes
  • For resources deployed with for_each, output computed attributes in a map structure

Examples:

hcl
# Single resource computed attribute
output "foo" {
  description = "MyResource foo attribute"
  value       = azurerm_resource_myresource.foo
}

# for_each resources
output "childresource_foos" {
  description = "MyResource children's foo attributes"
  value = {
    for key, value in azurerm_resource_mychildresource : key => value.foo
  }
}

# Sensitive output
output "bar" {
  description = "MyResource bar attribute"
  value       = azurerm_resource_myresource.bar
  sensitive   = true
}

Sensitive Data Outputs

Severity: MUST | Requirement: TFNFR29

Outputs containing confidential data MUST be declared with sensitive = true.

Handling Deprecated Outputs

Severity: MUST | Requirement: TFNFR30

  • Move deprecated outputs to deprecated_outputs.tf
  • Define new outputs in outputs.tf
  • Clean up during major version releases

Local Values Standards

locals.tf Organization

Severity: MAY | Requirement: TFNFR31

  • locals.tf SHOULD only contain locals blocks
  • MAY declare locals blocks next to resources for advanced scenarios

Alphabetical Local Arrangement

Severity: MUST | Requirement: TFNFR32

Expressions in locals blocks MUST be arranged alphabetically.

Precise Local Types

Severity: SHOULD | Requirement: TFNFR33

Use precise types (e.g., number for age, not string).


Terraform Configuration Requirements

Terraform Version Requirements

Severity: MUST | Requirement: TFNFR25

terraform.tf requirements:

  • MUST contain only one terraform block
  • First line MUST define required_version
  • MUST include minimum version constraint
  • MUST include maximum major version constraint
  • SHOULD use ~> #.# or >= #.#.#, < #.#.# format

Example:

hcl
terraform {
  required_version = "~> 1.6"
  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 4.0"
    }
  }
}

Providers in required_providers

Severity: MUST | Requirement: TFNFR26

  • terraform block MUST contain required_providers block
  • Each provider MUST specify source and version
  • Providers SHOULD be sorted alphabetically
  • Only include directly required providers
  • source MUST be in format namespace/name
  • version MUST include minimum and maximum major version constraints
  • SHOULD use ~> #.# or >= #.#.#, < #.#.# format

Testing Requirements

Test Tooling

Severity: MUST | Requirement: TFNFR5

Required testing tools for AVM:

  • Terraform (terraform validate/fmt/test)
  • terrafmt
  • Checkov
  • tflint (with azurerm ruleset)
  • Go (optional for custom tests)

Test Provider Configuration

Severity: SHOULD | Requirement: TFNFR36

For robust testing, prevent_deletion_if_contains_resources SHOULD be explicitly set to false in test provider configurations.


Documentation Requirements

Module Documentation Generation

Severity: MUST | Requirement: TFNFR2

  • Documentation MUST be automatically generated via Terraform Docs
  • A .terraform-docs.yml file MUST be present in the module root

Breaking Changes & Feature Management

Using Feature Toggles

Severity: MUST | Requirement: TFNFR34

New resources added in minor/patch versions MUST have a toggle variable to avoid creation by default:

hcl
variable "create_route_table" {
  type     = bool
  default  = false
  nullable = false
}

resource "azurerm_route_table" "this" {
  count = var.create_route_table ? 1 : 0
  # ...
}

Reviewing Potential Breaking Changes

Severity: MUST | Requirement: TFNFR35

Breaking changes requiring caution:

Resource blocks:

  1. Adding new resource without conditional creation
  2. Adding arguments with non-default values
  3. Adding nested blocks without dynamic
  4. Renaming resources without moved blocks
  5. Changing count to for_each or vice versa

Variable/Output blocks:

  1. Deleting/renaming variables
  2. Changing variable type
  3. Changing variable default values
  4. Changing nullable to false
  5. Changing sensitive from false to true
  6. Adding variables without default
  7. Deleting outputs
  8. Changing output value
  9. Changing output sensitive value

Contribution Standards

GitHub Repository Branch Protection

Severity: MUST | Requirement: TFNFR3

Module owners MUST set branch protection policies on the default branch (typically main):

  1. Require Pull Request before merging
  2. Require approval of most recent reviewable push
  3. Dismiss stale PR approvals when new commits are pushed
  4. Require linear history
  5. Prevent force pushes
  6. Not allow deletions
  7. Require CODEOWNERS review
  8. No bypassing settings allowed
  9. Enforce for administrators

Compliance Checklist

Use this checklist when developing or reviewing Azure Verified Modules:

Module Structure

  • Module cross-references use registry sources with pinned versions
  • Azure providers (azurerm/azapi) versions meet AVM requirements
  • .terraform-docs.yml present in module root
  • CODEOWNERS file present

Code Style

  • All names use lower snake_casing
  • Resources ordered with dependencies first
  • for_each uses map() or set() with static keys
  • Resource/data/module blocks follow proper internal ordering
  • ignore_changes not quoted
  • Dynamic blocks used for conditional nested objects
  • coalesce() or try() used for default values

Variables

  • No enabled or module_depends_on variables
  • Variables ordered: required (alphabetical) then optional (alphabetical)
  • All variables have precise types (avoid any)
  • All variables have descriptions
  • Collections have nullable = false
  • No sensitive = false declarations
  • No default values for sensitive inputs
  • Deprecated variables moved to deprecated_variables.tf

Outputs

  • Outputs use anti-corruption layer pattern (discrete attributes)
  • Sensitive outputs marked sensitive = true
  • Deprecated outputs moved to deprecated_outputs.tf

Terraform Configuration

  • terraform.tf has version constraints (~> format)
  • required_providers block present with all providers
  • No provider declarations in module (except aliases)
  • Locals arranged alphabetically

Testing & Quality

  • Required testing tools configured
  • New resources have feature toggles
  • Breaking changes reviewed and documented

Summary Statistics

  • Functional Requirements: 3
  • Non-Functional Requirements: 34
  • Total Requirements: 37

By Severity

  • MUST: 21 requirements
  • SHOULD: 14 requirements
  • MAY: 2 requirements

Based on: Azure Verified Modules - Terraform Requirements

Frequently asked questions

What does the Azure Verified Modules AI skill do?

Azure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.

Why use Azure Verified Modules on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/azure-verified-modules. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Azure Verified Modules?

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 Verified Modules?

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

Is the Azure Verified Modules AI skill free?

Yes. It is published on GitHub by hashicorp under the MPL-2.0 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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