terraform-module-library

wshobson/agents · updated Apr 8, 2026

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$npx skills add https://github.com/wshobson/agents --skill terraform-module-library
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summary

Reusable Terraform modules for AWS, Azure, GCP, and OCI infrastructure with standardized patterns and best practices.

  • Provides pre-built module templates across four cloud providers covering core services like VPC/VNet, Kubernetes clusters, databases, and object storage
  • Enforces consistent module structure with input variables, outputs, documentation, examples, and Terratest-based testing
  • Includes validation blocks, conditional resources via count/for_each, and tagging strategies for
skill.md

Terraform Module Library

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

Purpose

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

When to Use

  • 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/
└── oci/
    ├── vcn/
    ├── oke/
    └── object-storage/

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

Reference: See references/aws-modules.md and references/oci-modules.md

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"
  }
}

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
how to use terraform-module-library

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 development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add terraform-module-library
2

Execute installation command

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

$npx skills add https://github.com/wshobson/agents --skill terraform-module-library

The skills CLI fetches terraform-module-library from GitHub repository wshobson/agents and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/terraform-module-library

Reload or restart Cursor to activate terraform-module-library. Access the skill through slash commands (e.g., /terraform-module-library) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

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

Installation Steps

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

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.662 reviews
  • Li Patel· Dec 28, 2024

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

  • Emma Perez· Dec 24, 2024

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

  • Chaitanya Patil· Dec 20, 2024

    Useful defaults in terraform-module-library — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Tariq Srinivasan· Dec 16, 2024

    I recommend terraform-module-library for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Zara Shah· Dec 12, 2024

    terraform-module-library reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Jin Chawla· Dec 8, 2024

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

  • Tariq Shah· Nov 27, 2024

    I recommend terraform-module-library for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Tariq Reddy· Nov 23, 2024

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

  • Alexander Shah· Nov 15, 2024

    Keeps context tight: terraform-module-library is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Piyush G· Nov 11, 2024

    terraform-module-library has been reliable in day-to-day use. Documentation quality is above average for community skills.

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