Official agent skill

Avm Tf Classifications

by Azure in Azure/terraform-azurerm-avm-ptn-alz

A skill your agent uses whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module /…

OfficialMITAuto-check passedDevOps & Cloud

Install Avm Tf Classifications

skills CLI
$ npx skills add Azure/terraform-azurerm-avm-ptn-alz --skill avm-tf-classifications -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Azure/terraform-azurerm-avm-ptn-alz avm-tf-classifications --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Azure/terraform-azurerm-avm-ptn-alz.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/avm-tf-classifications .claude/skills/avm-tf-classifications && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
avm-tf-classifications
GitHub stars
135
Token cost
~2.9k tokens
SKILL.md length
932 words
Files
1
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module /…

  • A contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module
  • SKILL.md covers The three classes, Decision tree, Naming conventions and Common pitfalls
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Utility module —

What it does

Avm Tf Classifications is an agent skill from Azure/terraform-azurerm-avm-ptn-alz, published by the product's own GitHub organization. Use this skill whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module / GitHub repo / Terraform Registry entry. Covers the three module classes, the criteria that separate them ("single resource only" vs "opinionated multi-resource solution" vs "shared logic"), the naming conventions per class (avm-res-, avm-ptn-, avm-utl-), and the corresponding GitHub repo name (terraform-azure-avm-<class-<name for…

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Infrastructure as code. It works with Microsoft Azure, Terraform and GitHub. The repository describes itself as: Terraform Azure Verified Pattern Module for Azure Landing Zone Management Groups and Policy. The licence is MIT.

When your agent uses it

  • A contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module
  • Utility module —
  • Is naming a module / GitHub repo / Terraform Registry entry
  • Phrases like resource module vs pattern module

Example prompts

  • “single resource only”
  • “opinionated multi-resource solution”
  • “shared logic”
  • “/avm-tf-classifications”

What it can do on your machine

Read from SKILL.md and the folder at commit e2a318c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are hcl).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • raw.githubusercontent.com
    • azure.github.io
    • registry.terraform.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Avm Tf Classifications loads about 2.9k tokens when it runs. Until then it costs about 211 tokens; SKILL.md has 932 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~211
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Azure/terraform-azurerm-avm-ptn-alz at commit e2a318c, republished under its MIT licence (© Azure). 932 words, ~2,884 tokens.

Download SKILL.mdSave it as .claude/skills/avm-tf-classifications/SKILL.md (or your agent's skills folder).
name
avm-tf-classifications
description
Use this skill whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module / GitHub repo / Terraform Registry entry. Covers the three module classes, the criteria that separate them ("single resource only" vs "opinionated multi-resource solution" vs "shared logic"), the naming conventions per class (`avm-res-`, `avm-ptn-`, `avm-utl-`), and the corresponding GitHub repo name (`terraform-azure-avm-<class>-<name>` for new modules; `terraform-azurerm-avm-<class>-<name>` for legacy ones). Trigger on phrases like "resource module vs pattern module", "what class is this", "how do I name my AVM module", "wrapper module", "single resource", "multi-resource", "utility module", "avm-res-", "avm-ptn-", "avm-utl-".

AVM module classifications & naming (Terraform)

Every AVM module is exactly one of three classes. The class drives the naming convention, the repo name, the spec set that applies, and the review process.

Classification does not change the provider rule. Every new resource, pattern, or utility module repository that deploys Azure resources MUST use AzAPI for every control-plane and supported direct Azure operation. Each permitted azurerm_* resource or data-source block must independently implement one specific unsupported data-plane/non-ARM operation, document the exact block and AzAPI gap with an upstream AzAPI issue or pull request, and be replaced when support ships. One valid block does not authorize another.

Fetch https://azure.github.io/Azure-Verified-Modules/llms.txt and confirm the current versions of these sources:

The three classes

Resource module (avm-res-)

Deploys a single instance of one primary Azure resource (RMFR1) — e.g. one Key Vault, one Storage Account, one Search Service — plus the standard cross-cutting interfaces (lock, RBAC, diagnostic settings, private endpoints, etc. — see avm-tf-interfaces) and child resources that don't add value as standalone modules.

The primary resource MUST be implemented with AzAPI. Do not create a new AzureRM-based resource module.

If a consumer needs N instances of the resource, they call the module N times. The module itself never loops over the primary resource.

Must add value over raw azapi_resource (RMFR2) — usually via the standard interfaces, validation, and sensible WAF-aligned defaults. If your module is a thin wrapper that just passes inputs through to a single azapi_resource, you don't have a resource module — you have a useless module.

Pattern module (avm-ptn-)

Deploys an opinionated multi-resource solution to a recurring problem — e.g. "hub-and-spoke landing zone", "AKS baseline", "AI Foundry workspace with all dependencies". Pattern modules compose resource modules (TFFR1 — Cross-Referencing Modules requires them to consume AVM resource modules where available rather than re-implementing).

If a resource module doesn't exist for a resource the pattern needs, the pattern owner MUST log an issue on the central AVM repo requesting it (PMNFR4).

Any control-plane resource implemented directly in a pattern module MUST use AzAPI. The absence of an AVM resource module is not permission to use AzureRM.

Utility module (avm-utl-)

Provides shared logic with no resource deployments of its own, or rarely with a single supporting resource (e.g. a deployment script). Today the canonical example is avm-utl-interfaces — the variable schemas for the standard cross-cutting interfaces. Utility modules are introduced gradually and the specifications around them are still maturing.

If a utility module deploys a supporting control-plane Azure resource, that resource MUST use AzAPI.

If a utility module deploys no resources, telemetry collection MUST NOT be added (SFR3).

Decision tree

Are you deploying Azure resources?
  ├─ No → utility module (avm-utl-)
  └─ Yes
       ├─ Exactly one primary resource (+ standard interfaces + child resources)?
       │    └─ Yes → resource module (avm-res-)
       └─ Multiple primary resources composed into a solution?
            └─ Yes → pattern module (avm-ptn-)

If you find yourself wanting to deploy "a Key Vault AND a Storage Account" as one module, that's a pattern module composing two resource modules — not a single resource module.

Naming conventions

Module name (used in the Terraform Registry and in the proposal issue)
ClassFormatExample
Resourceavm-res-<resource provider>-<ARM resource type>avm-res-keyvault-vault, avm-res-search-searchservice, avm-res-compute-virtualmachine
Patternavm-ptn-<short pattern name>avm-ptn-aks-production, avm-ptn-alz-management
Utilityavm-utl-<utility name>avm-utl-interfaces, avm-utl-types

Notes on the resource segment:

  • <resource provider> is the lowercased and trimmed ARM provider name — Microsoft.KeyVault → keyvault, Microsoft.Storage → storage, Microsoft.Search → search.
  • <ARM resource type> is the lowercased and singular-ish resource type — vaults → vault, storageAccounts → storageaccount, searchServices → searchservice, virtualMachines → virtualmachine.
  • For sub-resources that warrant their own module: avm-res-keyvault-vault-key, avm-res-storage-storageaccount-blob. But sub-resources within a single resource module live under modules/ (TFRMNFR1) — not every child resource becomes its own AVM module.
Show full SKILL.md (353 more words)Show less
GitHub repo name (in the Azure org)

The repo name prefixes the module name with terraform-azure- (RMNFR1). The <provider> segment is a legacy Terraform Registry requirement; the spec now fixes it to azure for new modules — even though AVM Terraform modules use AzAPI:

ClassRepo
Resourceterraform-azure-avm-res-<rp>-<type> — e.g. terraform-azure-avm-res-storage-storageaccount
Patternterraform-azure-avm-ptn-<name> — e.g. terraform-azure-avm-ptn-aks-production
Utilityterraform-azure-avm-utl-<name> — e.g. terraform-azure-avm-utl-interfaces

This expands to the Terraform Registry source string Azure/avm-res-<rp>-<type>/azure (the /azure suffix is the Registry's "provider" namespace, fixed by convention even though the module's code uses AzAPI).

Legacy note. Most existing repos are still named terraform-azurerm-avm-* with an Azure/avm-res-.../azurerm Registry source — RMNFR1 changed the required <provider> segment from azurerm to azure, and the bulk of published modules pre-date the change. Keep an existing module's published name/source as-is; use azure only for new modules. The template repo itself remains terraform-azurerm-avm-template.

Primary resource name in code

Inside a new module, the primary azapi_resource MUST be named this (TFRMNFR2):

hcl
resource "azapi_resource" "this" {
  type      = var.resource_types.search_search_services
  parent_id = var.parent_id
  name      = var.name
  location  = var.location
  body      = { properties = { ... } }

  ignore_body_changes    = length(var.ignore_body_changes.search_search_services) > 0 ? var.ignore_body_changes.search_search_services : null
  response_export_values = []
  retry                  = var.retry

  dynamic "timeouts" {
    for_each = var.timeouts == null ? [] : [var.timeouts]
    content {
      create = timeouts.value.create
      read   = timeouts.value.read
      update = timeouts.value.update
      delete = timeouts.value.delete
    }
  }
}

When maintaining a pre-existing AzureRM module, keep its existing primary resource label this until migration. Do not copy that legacy implementation into a new module.

Common pitfalls

  • Treating "I want to deploy 5 VMs" as a resource module. It isn't — RMFR1 requires single-resource. Call a avm-res-compute-virtualmachine module 5 times, or write a pattern module if there's reusable orchestration.
  • Inventing a new naming convention. The repo name terraform-azure-avm-... is mechanical — don't substitute terraform-azapi-avm-... "because we're using AzAPI now". The Registry-side convention is fixed.
  • Treating the Registry namespace as provider selection. A legacy /azurerm Registry source identifies an existing published module; it does not allow a new module to use AzureRM as its primary provider.
  • Using AzureRM for supporting resources. Examples, tests, fixtures, and E2E setup use AzAPI for control-plane dependencies even when AzureRM would be easier. Every AzureRM block must independently satisfy the unsupported data-plane/non-ARM exception.
  • Adding a primary-resource name default. Resource modules MUST NOT default the primary resource's name (RMNFR2 / SNFR25) — the consumer must always supply it. Defaults are permitted (and required) for the standard-interface child resources like pep-<name>.
  • Forgetting that pattern modules consume resource modules. A pattern that re-implements a Key Vault inline instead of using avm-res-keyvault-vault violates TFFR1.

© Azure, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/avm-tf-classifications of Azure/terraform-azurerm-avm-ptn-alz.

Open the folder on GitHubat commit e2a318c

Compare with similar skills

Avm Tf Classifications next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Avm Tf Classifications compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Avm Tf Classifications this skillAzure/terraform-azurerm-avm-ptn-alz135—~2.9kAutomated safety check: PassMIT
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Terravision Cloud Diagramspatrickchugh/terravision1.6k—~5.6kAutomated safety check: NotesAGPL-3.0-only
TerrasharkLukasNiessen/terrashark714—~843Automated safety check: PassMIT
Datadog Data Source GeneratorDataDog/terraform-provider-datadog468—~2.7kAutomated safety check: PassMPL-2.0
Provider Verificationmondoohq/mql411—~3.7kAutomated safety check: PassCustom licence

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Categories

Questions about Avm Tf Classifications

What does Avm Tf Classifications do?

A skill your agent uses whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module /…. Avm Tf Classifications is an agent skill from Azure/terraform-azurerm-avm-ptn-alz, published by the product's own GitHub organization. Use this skill whenever a contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module, pattern module, or utility module — or is naming a module / GitHub repo / Terraform Registry entry.

When should I use Avm Tf Classifications?

Avm Tf Classifications fits situations like: A contributor is deciding what KIND of Azure Verified Module to build in Terraform — resource module; utility module —; is naming a module / GitHub repo / Terraform Registry entry; phrases like resource module vs pattern module.

How do I install Avm Tf Classifications in Claude Code?

Run `npx skills add Azure/terraform-azurerm-avm-ptn-alz --skill avm-tf-classifications -a claude-code`. Or copy the skill folder (.github/skills/avm-tf-classifications in Azure/terraform-azurerm-avm-ptn-alz) into .claude/skills/avm-tf-classifications in your project. Claude Code loads it when a task matches its description.

How do I install Avm Tf Classifications in Codex?

Run `npx skills add Azure/terraform-azurerm-avm-ptn-alz --skill avm-tf-classifications -a codex`. Or copy the skill folder (.github/skills/avm-tf-classifications in Azure/terraform-azurerm-avm-ptn-alz) into .agents/skills/avm-tf-classifications in your project. Codex loads it when a task matches its description.

Can I use Avm Tf Classifications in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Azure/terraform-azurerm-avm-ptn-alz --skill avm-tf-classifications -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/avm-tf-classifications, .gemini/skills/avm-tf-classifications, .github/skills/avm-tf-classifications and .opencode/skills/avm-tf-classifications in your project.

What does Avm Tf Classifications need to run?

SKILL.md names no scripts, command-line tools or credentials: Avm Tf Classifications is instructions for the agent only.

Does Avm Tf Classifications access the network?

SKILL.md names 3 domains. As links in the text: raw.githubusercontent.com, azure.github.io and registry.terraform.io. This is read from the text; nothing was executed.

Is Avm Tf Classifications safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Avm Tf Classifications use?

Avm Tf Classifications is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Avm Tf Classifications use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Avm Tf Classifications?

Skills that share tags, products or a category with Avm Tf Classifications: Apex GitHub Operations (jonathan-vella/apex, 217 stars), Terravision Cloud Diagrams (patrickchugh/terravision, 1.6k stars), Terrashark (LukasNiessen/terrashark, 714 stars) and Datadog Data Source Generator (DataDog/terraform-provider-datadog, 468 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Avm Tf Classifications?

Azure (a GitHub organization, an official publisher) maintains it in Azure/terraform-azurerm-avm-ptn-alz, which has 135 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 6, 2026.

Source: Azure/terraform-azurerm-avm-ptn-alz on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.