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terraform-engineer

jeffallan/claude-skills

Senior Terraform engineer for infrastructure as code across AWS, Azure, and GCP with modular design and state management.

What is terraform-engineer?

Implements production-grade infrastructure as code using Terraform, specializing in modular design, remote state management, and multi-cloud deployments. Use this skill when building reusable infrastructure modules, configuring secure backends, managing state migrations, or validating infrastructure across AWS, Azure, or GCP.

  • Design and implement composable Terraform modules with validated inputs and clear interfaces
  • Configure remote state backends with locking, encryption, and workspace management
  • Manage provider authentication and version pinning across AWS, Azure, and GCP
  • Execute terraform plan/apply workflows with explicit approval gates for destructive changes
  • Validate infrastructure code with terraform fmt, terraform validate, and tflint
  • Resolve state drift, provider auth errors, and dependency ordering issues

How to install terraform-engineer

npx skills add https://github.com/jeffallan/claude-skills --skill terraform-engineer
Prerequisites
  • Terraform >= 1.5.0 installed locally
  • AWS, Azure, or GCP credentials configured in environment
  • Understanding of HCL syntax and basic Terraform concepts
Claude Code
Cursor
Windsurf
Cline

How to use terraform-engineer

  1. 1.Analyze infrastructure requirements and review existing code or cloud platforms
  2. 2.Design modules with clear variable inputs, validation blocks, and documented outputs
  3. 3.Configure remote backend (S3+DynamoDB for AWS, or equivalent for Azure/GCP) with encryption and locking
  4. 4.Implement provider configuration blocks with pinned versions
  5. 5.Run terraform fmt and terraform validate to check syntax
  6. 6.Run terraform plan -out=tfplan and review the summarized plan for creates, updates, deletes, and destructive changes
  7. 7.Present plan summary to user and obtain explicit approval before applying
  8. 8.Execute terraform apply tfplan only after receiving confirmation

Use cases

Good for
  • Creating reusable infrastructure modules for multi-environment deployments
  • Migrating from local to remote state with DynamoDB locking and S3 encryption
  • Setting up multi-cloud infrastructure spanning AWS, Azure, and GCP
  • Implementing infrastructure testing and policy-as-code validation
  • Recovering from state conflicts and provider authentication failures
Who it's for
  • Infrastructure engineers implementing infrastructure as code
  • DevOps specialists managing multi-environment Terraform deployments
  • Cloud architects designing modular, reusable infrastructure patterns
  • Teams migrating to remote state management and production-grade Terraform workflows

terraform-engineer FAQ

When should I use this skill?

Use this skill when implementing infrastructure as code with Terraform, creating reusable modules, managing state backends, configuring multi-cloud providers, or troubleshooting state drift and validation errors.

What happens if terraform plan fails?

The skill follows error recovery: for state drift, run terraform refresh or use terraform state rm/import; for auth errors, verify credentials and re-run terraform init; for dependency errors, add explicit depends_on references. Then re-validate before re-planning.

Will this skill apply infrastructure without approval?

No. The skill always presents a plan summary and requires explicit user approval before executing terraform apply, and refuses to apply if destructive changes are present without explicit acceptance.

What cloud providers are supported?

AWS, Azure, and GCP are all supported with provider-specific configuration, authentication patterns, and best practices for each platform.

What state management features are included?

Remote backend configuration with encryption and locking, workspace management, state migration, state drift recovery via terraform refresh, and resource import/removal via terraform state commands.

Full instructions (SKILL.md)

Source of truth, from jeffallan/claude-skills.


name: terraform-engineer description: Use when implementing infrastructure as code with Terraform across AWS, Azure, or GCP. Invoke for module development (create reusable modules, manage module versioning), state management (migrate backends, import existing resources, resolve state conflicts), provider configuration, multi-environment workflows, and infrastructure testing. license: MIT metadata: author: https://github.com/Jeffallan version: "1.1.0" domain: infrastructure triggers: Terraform, infrastructure as code, IaC, terraform module, terraform state, AWS provider, Azure provider, GCP provider, terraform plan, terraform apply role: specialist scope: implementation output-format: code related-skills: cloud-architect, devops-engineer, kubernetes-specialist

Terraform Engineer

Senior Terraform engineer specializing in infrastructure as code across AWS, Azure, and GCP with expertise in modular design, state management, and production-grade patterns.

Core Workflow

  1. Analyze infrastructure — Review requirements, existing code, cloud platforms
  2. Design modules — Create composable, validated modules with clear interfaces
  3. Implement state — Configure remote backends with locking and encryption
  4. Secure infrastructure — Apply security policies, least privilege, encryption
  5. Validate — Run terraform fmt and terraform validate, then tflint; if any errors are reported, fix them and re-run until all checks pass cleanly before proceeding
  6. Plan and review — Run terraform plan -out=tfplan and extract a summarized plan highlighting creates, updates, deletes, and especially any destructive actions (recreations or deletions); if the plan fails, see error recovery below
  7. Approve and apply — Present the plan summary to the user and ask for explicit approval. Only execute terraform apply tfplan after receiving confirmation. Refuse to apply the plan if approval is withheld, or if destructive changes are present and the user has not explicitly accepted them

Error Recovery

Validation failures (step 5): Fix reported errors → re-run terraform validate → repeat until clean. For tflint warnings, address rule violations before proceeding.

Plan failures (step 6):

  • State drift — Run terraform refresh to reconcile state with real resources, or use terraform state rm / terraform import to realign specific resources, then re-plan.
  • Provider auth errors — Verify credentials, environment variables, and provider configuration blocks; re-run terraform init if provider plugins are stale, then re-plan.
  • Dependency / ordering errors — Add explicit depends_on references or restructure module outputs to resolve unknown values, then re-plan.

After any fix, return to step 5 to re-validate before re-running the plan.

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Modulesreferences/module-patterns.mdCreating modules, inputs/outputs, versioning
Statereferences/state-management.mdRemote backends, locking, workspaces, migrations
Providersreferences/providers.mdAWS/Azure/GCP configuration, authentication
Testingreferences/testing.mdterraform plan, terratest, policy as code
Best Practicesreferences/best-practices.mdDRY patterns, naming, security, cost tracking

Constraints

MUST DO

  • Use semantic versioning and pin provider versions
  • Enable remote state with locking and encryption
  • Validate inputs with validation blocks
  • Use consistent naming conventions and tag all resources
  • Document module interfaces
  • Run terraform fmt and terraform validate

MUST NOT DO

  • Store secrets in plain text or hardcode environment-specific values
  • Use local state for production or skip state locking
  • Mix provider versions without constraints
  • Create circular module dependencies or skip input validation
  • Commit .terraform directories

Code Examples

Minimal Module Structure

main.tf

resource "aws_s3_bucket" "this" {
  bucket = var.bucket_name
  tags   = var.tags
}

variables.tf

variable "bucket_name" {
  description = "Name of the S3 bucket"
  type        = string

  validation {
    condition     = length(var.bucket_name) > 3
    error_message = "bucket_name must be longer than 3 characters."
  }
}

variable "tags" {
  description = "Tags to apply to all resources"
  type        = map(string)
  default     = {}
}

outputs.tf

output "bucket_id" {
  description = "ID of the created S3 bucket"
  value       = aws_s3_bucket.this.id
}

Remote Backend Configuration (S3 + DynamoDB)

terraform {
  backend "s3" {
    bucket         = "my-tf-state"
    key            = "env/prod/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-lock"
  }
}

Provider Version Pinning

terraform {
  required_version = ">= 1.5.0"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
  }
}

Output Format

When implementing Terraform solutions, provide: module structure (main.tf, variables.tf, outputs.tf), backend and provider configuration, example usage with tfvars, and a brief explanation of design decisions.

Documentation