Terraform Aws

CommunityPopular

BagelHole

terraform-aws

Provision AWS infrastructure with Terraform. Create modules, manage state, and implement IaC best practices. Use when deploying AWS resources declaratively.

Overview

Publisher	BagelHole
Repository	`DevOps-Security-Agent-Skills`
Skill name	`terraform-aws`
Stars	1.1K
Forks	161
Bundled files	3
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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by BagelHole on GitHub. Read the source before you install it.

Installation

Install the Terraform Aws 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.
https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-aws/terraform-aws
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-aws/terraform-aws

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/infrastructure/cloud-aws/terraform-aws .claude/skills/terraform-aws

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

Use it in TypingMind

Enable Terraform Aws 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 Aws 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 Aws 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 AWS

Provision and manage AWS infrastructure with Terraform.

Provider Configuration

hcl
terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
  
  backend "s3" {
    bucket = "terraform-state"
    key    = "prod/terraform.tfstate"
    region = "us-east-1"
  }
}

provider "aws" {
  region = var.region
  
  default_tags {
    tags = {
      Environment = var.environment
      ManagedBy   = "terraform"
    }
  }
}

Example Resources

hcl
resource "aws_vpc" "main" {
  cidr_block           = "10.0.0.0/16"
  enable_dns_hostnames = true
  
  tags = { Name = "main-vpc" }
}

resource "aws_instance" "web" {
  ami           = data.aws_ami.amazon_linux.id
  instance_type = "t3.micro"
  subnet_id     = aws_subnet.public.id
  
  tags = { Name = "web-server" }
}

Modules

hcl
module "vpc" {
  source = "terraform-aws-modules/vpc/aws"
  
  name = "my-vpc"
  cidr = "10.0.0.0/16"
  
  azs             = ["us-east-1a", "us-east-1b"]
  private_subnets = ["10.0.1.0/24", "10.0.2.0/24"]
  public_subnets  = ["10.0.101.0/24", "10.0.102.0/24"]
  
  enable_nat_gateway = true
}

Commands

bash
terraform init
terraform plan -out=plan.tfplan
terraform apply plan.tfplan
terraform destroy

Best Practices

Use remote state with locking
Implement module structure
Use workspaces or separate states per environment
Pin provider versions
Use data sources for AMIs

Related Skills

aws-vpc - VPC networking
aws-iam - IAM policies

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 Aws AI skill do?

Provision AWS infrastructure with Terraform. Create modules, manage state, and implement IaC best practices. Use when deploying AWS resources declaratively.

Why use Terraform Aws on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-aws/terraform-aws. 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 Aws?

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 Aws?

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

Is the Terraform Aws AI skill free?

Yes. It is published on GitHub by BagelHole 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

Terraform AWS

Provider Configuration

Example Resources

Modules

Commands

Best Practices

Related Skills

Bundled files

Frequently asked questions

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