Terraform Module Library

Terraform Module Library

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/terraform-module-library from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

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

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, Module Structure, Standard Module Pattern, Module Composition, Testing, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• The task is unrelated to terraform module library
• You need a different domain or tool outside this scope
• Build reusable infrastructure components
• Standardize cloud resource provisioning
• Implement infrastructure as code best practices
• Create multi-cloud compatible modules

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Clarify goals, constraints, and required inputs.
2. Apply relevant best practices and validate outcomes.
3. Provide actionable steps and verification.
4. If detailed examples are required, open resources/implementation-playbook.md.
5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
6. Read the overview and provenance files before loading any copied upstream support files.
7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: 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.

Imported: Purpose

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

Examples

Example 1: Ask for the upstream workflow directly

Use @terraform-module-library to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @terraform-module-library against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @terraform-module-library for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @terraform-module-library using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: 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

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/terraform-module-library, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• aws-modules.md
• aws-modules.md

Imported Reference Notes

Imported: 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

Imported: Module Structure

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

Imported: 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

Imported: 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"
  }
}

Imported: 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)
}

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Source: diegosouzapw/awesome-omni-skills — distributed by TomeVault.