refactor-module

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• SKILL.md

SKILL.md (first lines)

# Skill: Refactor Module

## Overview
This skill guides AI agents in transforming monolithic Terraform configurations into reusable, maintainable modules following HashiCorp's module design principles and community best practices.

## Capability Statement
The agent will analyze existing Terraform code and systematically refactor it into well-structured modules with:
- Clear interface contracts (variables and outputs)
- Proper encapsulation and abstraction
- Versioning and documentation
- Testing frameworks
- Migration path for existing state

## Prerequisites
- Existing Terraform configuration to refactor
- Understanding of resource dependencies
- Access to inspect current state via `terraform state list` / `terraform show -json` (for migration planning)
- Knowledge of module registry patterns

## Input Parameters

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `source_directory` | string | Yes | Path to existing Terraform configuration |
| `module_name` | string | Yes | Name for the new module |
| `abstraction_level` | string | No | "simple", "intermediate", "advanced" (default: intermediate) |
| `preserve_state` | boolean | Yes | Whether to maintain state compatibility |
| `target_registry` | string | No | Target module registry (local, private, public) |

## Execution Steps

### 1. Analysis Phase
```markdown
**Identify Refactoring Candidates**
- Group resources by logical function
- Identify repeated patterns
- Map resource dependencies
- Detect configuration coupling
- Analyze variable usage patterns

**Complexity Assessment**
- Count resource relationships
- Measure variable propagation depth
- Identify cross-resource references
- Evaluate state migration complexity
```

### 2. Module Design

#### Interface Design
```hcl
# Define clear input contract
variable "network_config" {
  description = "Network configuration parameters"
  type = object({
    cidr_block         = string
    availability_zones = list(string)
    enable_nat         = bool
  })

  validation {
    condition     = can(cidrhost(var.network_config.cidr_block, 0))
    error_message = "CIDR block must be valid IPv4 CIDR."
  }
}

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

output "private_subnet_ids" {
  description = "List of private subnet IDs"
  value       = { for k, v in aws_subnet.private : k => v.id }
}
```

#### Encapsulation Strategy
```markdown
**What to Include in Module:**
- Tightly coupled resources (VPC + subnets)
- Resources with shared lifecycle
- Configuration with clear boundaries

**What to Keep Separate:**
- Cross-cutting concerns (monitoring, tagging)
- Resources with different lifecycles
- Provider-specific configurations
```

### 3. Code Transformation

#### Before: Monolithic Configuration
```hcl
# main.tf (monolithic)
resource "aws_vpc" "main" {
  cidr_block = "10.0.0.0/16"
  enable_dns_hostnames = true

  tags = {
    Name = "production-vpc"
    Environment = "prod"
  }
}

resource "aws_subnet" "public_1" {
  vpc_id            = aws_vpc.main.id
  cidr_block        = "10.0.1.0/24"
  availability_zone = "us-east-1a"

  tags = {
    Name = "public-subnet-1"
    Type = "public"
  }
}

resource "aws_subnet" "public_2" {
  vpc_id            = aws_vpc.main.id

From hashicorp/agent-skills, MPL-2.0.

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