terraform-module-library

Production-ready Terraform module patterns for AWS, Azure, and GCP infrastructure.

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Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill terraform-module-library

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Installation Guide

How to use terraform-module-library on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add terraform-module-library
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill terraform-module-library

Fetches terraform-module-library from sickn33/antigravity-awesome-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/terraform-module-library

Restart Cursor to activate terraform-module-library. Access via /terraform-module-library in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

Terraform Module Library

Production-ready Terraform module patterns for AWS, Azure, and GCP infrastructure.

Do not use this skill when

  • The task is unrelated to terraform module library
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/implementation-playbook.md.

Purpose

Create reusable, well-tested Terraform modules for common cloud infrastructure patterns across multiple cloud providers.

Use this skill when

  • Build reusable infrastructure components
  • Standardize cloud resource provisioning
  • Implement infrastructure as code best practices
  • Create multi-cloud compatible modules
  • Establish organizational Terraform standards

Module Structure

terraform-modules/
├── aws/
│   ├── vpc/
│   ├── eks/
│   ├── rds/
│   └── s3/
├── azure/
│   ├── vnet/
│   ├── aks/
│   └── storage/
└── gcp/
    ├── vpc/
    ├── gke/
    └── cloud-sql/

Standard Module Pattern

module-name/
├── main.tf          # Main resources
├── variables.tf     # Input variables
├── outputs.tf       # Output values
├── versions.tf      # Provider versions
├── README.md        # Documentation
├── examples/        # Usage examples
│   └── complete/
│       ├── main.tf
│       └── variables.tf
└── tests/           # Terratest files
    └── module_test.go

AWS VPC Module Example

main.tf:

resource "aws_vpc" "main" {
  cidr_block           = var.cidr_block
  enable_dns_hostnames = var.enable_dns_hostnames
  enable_dns_support   = var.enable_dns_support

  tags = merge(
    {
      Name = var.name
    },
    var.tags
  )
}

resource "aws_subnet" "private" {
  count             = length(var.private_subnet_cidrs)
  vpc_id            = aws_vpc.main.id
  cidr_block        = var.private_subnet_cidrs[count.index]
  availability_zone = var.availability_zones[count.index]

  tags = merge(
    {
      Name = "${var.name}-private-${count.index + 1}"
      Tier = "private"
    },
    var.tags
  )
}

resource "aws_internet_gateway" "main" {
  count  = var.create_internet_gateway ? 1 : 0
  vpc_id = aws_vpc.main.id

  tags = merge(
    {
      Name = "${var.name}-igw"
    },
    var.tags
  )
}

variables.tf:

variable "name" {
  description = "Name of the VPC"
  type        = string
}

variable "cidr_block" {
  description = "CIDR block for VPC"
  type        = string
  validation {
    condition     = can(regex("^([0-9]{1,3}\\.){3}[0-9]{1,3}/[0-9]{1,2}$", var.cidr_block))
    error_message = "CIDR block must be valid IPv4 CIDR notation."
  }
}

variable "availability_zones" {
  description = "List of availability zones"
  type        = list(string)
}

variable "private_subnet_cidrs" {
  description = "CIDR blocks for private subnets"
  type        = list(string)
  default     = []
}

variable "enable_dns_hostnames" {
  description = "Enable DNS hostnames in VPC"
  type        = bool
  default     = true
}

variable "tags" {
  description = "Additional tags"
  type        = map(string)
  default     = {}
}

outputs.tf:

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

output "private_subnet_ids" {
  description = "IDs of private subnets"
  value       = aws_subnet.private[*].id
}

output "vpc_cidr_block" {
  description = "CIDR block of VPC"
  value       = aws_vpc.main.cidr_block
}

Best Practices

  1. Use semantic versioning for modules
  2. Document all variables with descriptions
  3. Provide examples in examples/ directory
  4. Use validation blocks for input validation
  5. Output important attributes for module composition
  6. Pin provider versions in versions.tf
  7. Use locals for computed values
  8. Implement conditional resources with count/for_each
  9. Test modules with Terratest
  10. Tag all resources consistently

Module Composition

module "vpc" {
  source = "../../modules/aws/vpc"

  name               = "production"
  cidr_block         = "10.0.0.0/16"
  availability_zones = ["us-west-2a", "us-west-2b", "us-west-2c"]

  private_subnet_cidrs = [
    "10.0.1.0/24",
    "10.0.2.0/24",
    "10.0.3.0/24"
  ]

  tags = {
    Environment = "production"
    ManagedBy   = "terraform"
  }
}

module "rds" {
  source = "../../modules/aws/rds"

  identifier     = "production-db"
  engine         = "postgres"
  engine_version = "15.3"
  instance_class = "db.t3.large"

  vpc_id     = module.vpc.vpc_id
  subnet_ids = module.vpc.private_subnet_ids

  tags = {
    Environment = "production"
  }
}

Reference Files

  • assets/vpc-module/ - Complete VPC module example
  • assets/rds-module/ - RDS module example
  • references/aws-modules.md - AWS module patterns
  • references/azure-modules.md - Azure module patterns
  • references/gcp-modules.md - GCP module patterns

Testing

// tests/vpc_test.go
package test

import (
    "testing"
    "github.com/gruntwork-io/terratest/modules/terraform"
    "github.com/stretchr/testify/assert"
)

func TestVPCModule(t *testing.T) {
    terraformOptions := &terraform.Options{
        TerraformDir: "../examples/complete",
    }

    defer terraform.Destroy(t, terraformOptions)
    terraform.InitAndApply(t, terraformOptions)

    vpcID := terraform.Output(t, terraformOptions, "vpc_id")
    assert.NotEmpty(t, vpcID)
}

Related Skills

  • multi-cloud-architecture - For architectural decisions
  • cost-optimization - For cost-effective designs

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.527 reviews
  • P
    Pratham WareDec 16, 2024

    Solid pick for teams standardizing on skills: terraform-module-library is focused, and the summary matches what you get after install.

  • A
    Ama JohnsonDec 16, 2024

    Solid pick for teams standardizing on skills: terraform-module-library is focused, and the summary matches what you get after install.

  • Y
    Yash ThakkerNov 7, 2024

    We added terraform-module-library from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • D
    Diya HaddadNov 7, 2024

    We added terraform-module-library from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • D
    Dhruvi JainOct 26, 2024

    terraform-module-library fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • D
    Diya LopezOct 26, 2024

    terraform-module-library fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • O
    OshnikdeepSep 17, 2024

    Registry listing for terraform-module-library matched our evaluation — installs cleanly and behaves as described in the markdown.

  • D
    Diya BansalSep 17, 2024

    Registry listing for terraform-module-library matched our evaluation — installs cleanly and behaves as described in the markdown.

  • P
    Piyush GSep 13, 2024

    terraform-module-library is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • I
    Isabella KapoorSep 5, 2024

    Solid pick for teams standardizing on skills: terraform-module-library is focused, and the summary matches what you get after install.

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