Break monolithic Terraform configurations into reusable, well-structured modules with clear contracts and migration paths.
Works with
Analyzes existing code to identify refactoring candidates, groups resources by logical function, and assesses complexity before design
Generates module interfaces with typed variables, validation rules, and descriptive outputs following HashiCorp best practices
Provides state migration strategies using moved blocks (Terraform 1.1+) or manual terraform state mv co
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrefactor-moduleExecute the skills CLI command in your project's root directory to begin installation:
Fetches refactor-module from hashicorp/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate refactor-module. Access via /refactor-module in your agent's command palette.
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.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill guides AI agents in transforming monolithic Terraform configurations into reusable, maintainable modules following HashiCorp's module design principles and community best practices.
The agent will analyze existing Terraform code and systematically refactor it into well-structured modules with:
| 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) |
**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
# 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 }
}
**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
# 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
cidr_block = "10.0.2.0/24"
availability_zone = "us-east-1b"
tags = {
Name = "public-subnet-2"
Type = "public"
}
}
resource "aws_internet_gateway" "main" {
vpc_id = aws_vpc.main.id
tags = {
Name = "production-igw"
}
}
# ... more repetitive subnet and routing resources
# modules/vpc/main.tf
locals {
subnet_count = length(var.availability_zones)
}
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(
var.tags,
{
Name = var.name
}
)
}
resource "aws_subnet" "public" {
for_each = var.create_public_subnets ? toset(var.availability_zones) : []
vpc_id = aws_vpc.main.id
cidr_block = cidrsubnet(var.cidr_block, 8, index(var.availability_zones, each.value))
availability_zone = each.value
map_public_ip_on_launch = true
tags = merge(
var.tags,
{
Name = "${var.name}-public-${each.value}"
Type = "public"
}
)
}
resource "aws_internet_gateway" "main" {
count = var.create_public_subnets ? 1 : 0
vpc_id = aws_vpc.main.id
tags = merge(
var.tags,
{
Name = "${var.name}-igw"
}
)
}
# modules/vpc/variables.tf
variable "name" {
description = "Name prefix for all resources"
type = string
}
variable "cidr_block" {
description = "CIDR block for the VPC"
type = string
validation {
condition = can(cidrhost(var.cidr_block, 0))
error_message = "Must be a valid IPv4 CIDR block."
}
}
variable "availability_zones" {
description = "List of availability zones"
type = list(string)
}
variable "create_public_subnets" {
description = "Whether to create public subnets"
type = bool
default = true
}
variable "enable_dns_hostnames" {
description = "Enable DNS hostnames in the VPC"
type = bool
default = true
}
variable "enable_dns_support" {
description = "Enable DNS support in the VPC"
type = bool
default = true
}
variable "tags" Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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parcadei/continuous-claude-v3
cursor/plugins
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mattpocock/skills
refactor-module reduced setup friction for our internal harness; good balance of opinion and flexibility.
refactor-module is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
refactor-module is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
refactor-module reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in refactor-module — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend refactor-module for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
refactor-module is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
refactor-module has been reliable in day-to-day use. Documentation quality is above average for community skills.
refactor-module reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend refactor-module for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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