Terraform Style Guide logo

Terraform Style Guide

Organization
hashicorp
terraform-style-guide

Generate Terraform HCL code following HashiCorp's official style conventions and best practices. Use when writing, reviewing, or generating Terraform configurations.

Overview

Publisherhashicorp
Repositoryagent-skills
Skill nameterraform-style-guide
Stars
880
Forks
130
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Terraform Style Guide 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/terraform-style-guide
  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/terraform-style-guide .claude/skills/terraform-style-guide
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Terraform Style Guide 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 Terraform Style Guide 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 Terraform Style Guide 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.

Terraform Style Guide

Generate and maintain Terraform code following HashiCorp's official style conventions and best practices.

Reference: HashiCorp Terraform Style Guide

Code Generation Strategy

When generating Terraform code:

  1. Start with provider configuration and version constraints
  2. Create data sources before dependent resources
  3. Build resources in dependency order
  4. Add outputs for key resource attributes
  5. Use variables for all configurable values

File Organization

FilePurpose
terraform.tfTerraform and provider version requirements
providers.tfProvider configurations
main.tfPrimary resources and data sources
variables.tfInput variable declarations (alphabetical)
outputs.tfOutput value declarations (alphabetical)
locals.tfLocal value declarations

Example Structure

hcl
# terraform.tf
terraform {
  required_version = ">= 1.14"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 6.0"
    }
  }
}

# variables.tf
variable "environment" {
  description = "Target deployment environment"
  type        = string

  validation {
    condition     = contains(["dev", "staging", "prod"], var.environment)
    error_message = "Environment must be dev, staging, or prod."
  }
}

# locals.tf
locals {
  common_tags = {
    Environment = var.environment
    ManagedBy   = "Terraform"
  }
}

# main.tf
resource "aws_vpc" "main" {
  cidr_block           = var.vpc_cidr
  enable_dns_hostnames = true

  tags = merge(local.common_tags, {
    Name = "${var.project_name}-${var.environment}-vpc"
  })
}

# outputs.tf
output "vpc_id" {
  description = "ID of the created VPC"
  value       = aws_vpc.main.id
}

Code Formatting

Indentation and Alignment

  • Use two spaces per nesting level (no tabs)
  • Align equals signs for consecutive arguments
hcl
resource "aws_instance" "web" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"
  subnet_id     = "subnet-12345678"

  tags = {
    Name        = "web-server"
    Environment = "production"
  }
}

Block Organization

Arguments precede blocks, with meta-arguments first:

hcl
resource "aws_instance" "example" {
  # Meta-arguments
  count = 3

  # Arguments
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"

  # Blocks
  root_block_device {
    volume_size = 20
  }

  # Lifecycle last
  lifecycle {
    create_before_destroy = true
  }
}

Naming Conventions

  • Use lowercase with underscores for all names
  • Use descriptive nouns excluding the resource type
  • Be specific and meaningful
  • Resource names must be singular, not plural
  • Default to main for resources where a specific descriptive name is redundant or unavailable, provided only one instance exists
hcl
# Bad
resource "aws_instance" "webAPI-aws-instance" {}
resource "aws_instance" "web_apis" {}
variable "name" {}

# Good
resource "aws_instance" "web_api" {}
resource "aws_vpc" "main" {}
variable "application_name" {}

Variables

Every variable must include type and description:

hcl
variable "instance_type" {
  description = "EC2 instance type for the web server"
  type        = string
  default     = "t2.micro"

  validation {
    condition     = contains(["t2.micro", "t2.small", "t2.medium"], var.instance_type)
    error_message = "Instance type must be t2.micro, t2.small, or t2.medium."
  }
}

variable "database_password" {
  description = "Password for the database admin user"
  type        = string
  sensitive   = true
}

Outputs

Every output must include description:

hcl
output "instance_id" {
  description = "ID of the EC2 instance"
  value       = aws_instance.web.id
}

output "database_password" {
  description = "Database administrator password"
  value       = aws_db_instance.main.password
  sensitive   = true
}

Dynamic Resource Creation

Prefer for_each over count

hcl
# Bad - count for multiple resources
resource "aws_instance" "web" {
  count = var.instance_count
  tags  = { Name = "web-${count.index}" }
}

# Good - for_each with named instances
variable "instance_names" {
  type    = set(string)
  default = ["web-1", "web-2", "web-3"]
}

resource "aws_instance" "web" {
  for_each = var.instance_names
  tags     = { Name = each.key }
}

count for Conditional Creation

hcl
resource "aws_cloudwatch_metric_alarm" "cpu" {
  count = var.enable_monitoring ? 1 : 0

  alarm_name = "high-cpu-usage"
  threshold  = 80
}

Security Best Practices

Refer to SECURITY.md. It includes guidance on encrypting resources, preventing sensitive data in state, and secure configurations.

Version Pinning

hcl
terraform {
  required_version = ">= 1.14"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 6.0"
    }
  }
}

Use the latest major version of each provider and the latest minor version of Terraform, unless otherwise constrained by a dependency lock file or by other modules used by the configuration.

Version constraint operators:

  • = 1.0.0 - Exact version
  • >= 1.0.0 - Greater than or equal
  • ~> 1.0 - Allow rightmost component to increment
  • >= 1.0, < 2.0 - Version range

Provider Configuration

hcl
provider "aws" {
  region = "us-west-2"

  default_tags {
    tags = {
      ManagedBy = "Terraform"
      Project   = var.project_name
    }
  }
}

# Aliased provider for multi-region
provider "aws" {
  alias  = "east"
  region = "us-east-1"
}

Version Control

Never commit:

  • terraform.tfstate, terraform.tfstate.backup
  • .terraform/ directory
  • *.tfplan
  • .tfvars files with sensitive data

Always commit:

  • All .tf configuration files
  • .terraform.lock.hcl (dependency lock file)

Validation Tools

Run before committing:

bash
terraform fmt -recursive
terraform validate

Additional tools:

  • tflint - Linting and best practices
  • checkov / tfsec - Security scanning

Code Review Checklist

  • Code formatted with terraform fmt
  • Configuration validated with terraform validate
  • Files organized according to standard structure
  • All variables have type and description
  • All outputs have descriptions
  • Resource names use descriptive nouns with underscores
  • Version constraints pinned explicitly
  • Sensitive values marked with sensitive = true
  • No hardcoded credentials or secrets
  • Security best practices applied

Based on: HashiCorp Terraform Style Guide

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 Terraform Style Guide AI skill do?

Generate Terraform HCL code following HashiCorp's official style conventions and best practices. Use when writing, reviewing, or generating Terraform configurations.

Why use Terraform Style Guide on TypingMind?

Because you install it once and use it with any model. Terraform Style Guide 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 Terraform Style Guide in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/terraform-style-guide. 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 Terraform Style Guide?

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 Terraform Style Guide?

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

Is the Terraform Style Guide 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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