terraform-module-library▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
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Production-ready Terraform module patterns for AWS, Azure, and GCP infrastructure.
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
- Use semantic versioning for modules
- Document all variables with descriptions
- Provide examples in examples/ directory
- Use validation blocks for input validation
- Output important attributes for module composition
- Pin provider versions in versions.tf
- Use locals for computed values
- Implement conditional resources with count/for_each
- Test modules with Terratest
- 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 exampleassets/rds-module/- RDS module examplereferences/aws-modules.md- AWS module patternsreferences/azure-modules.md- Azure module patternsreferences/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 decisionscost-optimization- For cost-effective designs
How to use terraform-module-library on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches terraform-module-library from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★27 reviews- ★★★★★Pratham Ware· Dec 16, 2024
Solid pick for teams standardizing on skills: terraform-module-library is focused, and the summary matches what you get after install.
- ★★★★★Ama Johnson· Dec 16, 2024
Solid pick for teams standardizing on skills: terraform-module-library is focused, and the summary matches what you get after install.
- ★★★★★Yash Thakker· Nov 7, 2024
We added terraform-module-library from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Diya Haddad· Nov 7, 2024
We added terraform-module-library from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Dhruvi Jain· Oct 26, 2024
terraform-module-library fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Diya Lopez· Oct 26, 2024
terraform-module-library fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Oshnikdeep· Sep 17, 2024
Registry listing for terraform-module-library matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Diya Bansal· Sep 17, 2024
Registry listing for terraform-module-library matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Piyush G· Sep 13, 2024
terraform-module-library is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Isabella Kapoor· Sep 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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