terraform-engineer — Claude Code skill: IaC on AWS, Azure, GCP
Skill for writing and managing infrastructure with Terraform. Designs reusable modules, configures remote state, validates code, and safely applies changes across AWS, Azure, and GCP.
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a claude-codeWhat terraform-engineer does
terraform-engineer is a specialized skill for infrastructure as code on AWS, Azure, and GCP. It analyses requirements, designs composable modules with clear interfaces, and configures remote backends with locking and encryption. At each step it validates code via terraform fmt, terraform validate, and tflint, runs terraform plan, extracts a summary highlighting creates, updates, and deletes—then asks for explicit approval before terraform apply. It refuses to apply if destructive changes are present without user confirmation.
The skill handles error recovery: if terraform refresh detects state drift, it realigns via terraform state rm or terraform import; if credentials fail, it checks environment variables and provider configuration. It enforces semantic versioning, requires pinned provider versions, forbids hardcoded secrets and local state in production. Outputs ready-made module structure (main.tf, variables.tf, outputs.tf) with backend and provider configuration examples.
What it helps with
- Design reusable Terraform modules with input validation and clear outputs
- Set up remote state with locking for multi-user teams
- Resolve state drift and conflicts through import and removal
- Validate configuration and review plans before applying infrastructure changes
- Manage multi-cloud infrastructure with consistent structure
Example prompts for the agent
- Create an S3 module with bucket name validation and resource tags
- Configure a remote backend on S3 with DynamoDB locking for production
- Migrate state from local to remote backend and resolve conflicts
How to install terraform-engineer
1Skills CLI (Vercel)
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a claude-code2Manually: put the files in place
~/.claude/skills/terraform-engineer/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/terraform-engineer/
1Skills CLI (Vercel)
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a codex2Manually: put the files in place
.agents/skills/terraform-engineer/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a cursor2Manually: put the files in place
.cursor/skills/terraform-engineer/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install Jeffallan/claude-skills terraform-engineer2Manually: put the files in place
.github/skills/terraform-engineer/SKILL.md1Skills CLI (Vercel)
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a gemini-cli2Platform CLI
gemini skills install https://github.com/Jeffallan/claude-skills --path skills/terraform-engineerManually: put the files in place
.devin/skills/terraform-engineer/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add Jeffallan/claude-skills --skill terraform-engineer -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set61
The whole set →Similar
Questions about terraform-engineer
How do I install terraform-engineer in Claude Code?
Run npx skills add Jeffallan/claude-skills --skill terraform-engineer -a claude-code, then verify the SKILL.md file is available at ~/.claude/skills/terraform-engineer/SKILL.md.
What does terraform-engineer do?
It handles the full cycle: analyses infrastructure, designs modules, configures state and providers, validates code, creates a plan, and requests approval before apply. It catches and resolves errors like state drift, auth issues, and dependency problems.
Which cloud platforms are supported?
AWS, Azure, and GCP. The skill configures each provider and can work with them simultaneously in a single project.
Source text
SKILL.md · MIT
---
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
company: https://synergetic.solutions
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:
| Topic | Reference | Load When |
|-------|-----------|-----------|
| Modules | `references/module-patterns.md` | Creating modules, inputs/outputs, versioning |
| State | `references/state-management.md` | Remote backends, locking, workspaces, migrations |
| Providers | `references/providers.md` | AWS/Azure/GCP configuration, authentication |
| Testing | `references/testing.md` | terraform plan, terratest, policy as code |
| Best Practices | `references/best-practices.md` | DRY 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`**
```hcl
resource "aws_s3_bucket" "this" {
bucket = var.bucket_name
tags = var.tags
}
```
**`variables.tf`**
```hcl
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`**
```hcl
output "bucket_id" {
description = "ID of the created S3 bucket"
value = aws_s3_bucket.this.id
}
```
### Remote Backend Configuration (S3 + DynamoDB)
```hcl
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
```hcl
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.
Maintained by [@jeffallan](https://github.com/jeffallan), Principal Consultant at [Synergetic Solutions](https://synergetic.solutions)
[Documentation](https://jeffallan.github.io/claude-skills/skills/infrastructure/terraform-engineer/)
© https://github.com/Jeffallan · MIT · Jeffallan/claude-skills