Detalle del Skill
terraform-patterns
Infrastructure engineering.
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SKILL.md
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---
name: "terraform-patterns"
description: "Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider configuration, security hardening, policy-as-code with Sentinel/OPA, and CI/CD plan/apply workflows. Use when: user wants to design Terraform modules, manage state backends, review Terraform security, implement multi-region deployments, or follow IaC best practices."
license: MIT
metadata:
version: 1.0.0
author: Alireza Rezvani
category: engineering
updated: 2026-03-15
---
# Terraform Patterns
> Predictable infrastructure. Secure state. Modules that compose. No drift.
Opinionated Terraform workflow that turns sprawling HCL into well-structured, secure, production-grade infrastructure code. Covers module design, state management, provider patterns, security hardening, and CI/CD integration.
Not a Terraform tutorial — a set of concrete decisions about how to write infrastructure code that doesn't break at 3 AM.
---
## Slash Commands
| Command | What it does |
|---------|-------------|
| `/terraform:review` | Analyze Terraform code for anti-patterns, security issues, and structure problems |
| `/terraform:module` | Design or refactor a Terraform module with proper inputs, outputs, and composition |
| `/terraform:security` | Audit Terraform code for security vulnerabilities, secrets exposure, and IAM misconfigurations |
---
## When This Skill Activates
Recognize these patterns from the user:
- "Review this Terraform code"
- "Design a Terraform module for..."
- "My Terraform state is..."
- "Set up remote state backend"
- "Multi-region Terraform deployment"
- "Terraform security review"
- "Module structure best practices"
- "Terraform CI/CD pipeline"
- Any request involving: `.tf` files, HCL, Terraform modules, state management, provider configuration, infrastructure-as-code
If the user has `.tf` files or wants to provision infrastructure with Terraform → this skill applies.
---
## Workflow
### `/terraform:review` — Terraform Code Review
1. **Analyze current state**
- Read all `.tf` files in the target directory
- Identify module structure (flat vs nested)
- Count resources, data sources, variables, outputs
- Check naming conventions
2. **Apply review checklist**
```
MODULE STRUCTURE
├── Variables have descriptions and type constraints
├── Outputs expose only what consumers need
├── Resources use consistent naming: {provider}_{type}_{purpose}
├── Locals used for computed values and DRY expressions
└── No hardcoded values — everything parameterized or in locals
STATE & BACKEND
├── Remote backend configured (S3, GCS, Azure Blob, Terraform Cloud)
├── State locking enabled (DynamoDB for S3, native for others)
├── State encryption at rest enabled
├── No secrets stored in state (or state access is restricted)
└── Workspaces or directory isolation for environments
PROVIDERS
├── Version constraints use pessimistic operator: ~> 5.0
├── Required providers block in terraform {} block
├── Provider aliases for multi-region or multi-account
└── No provider configuration in child modules
SECURITY
├── No hardcoded secrets, keys, or passwords
├── IAM follows least-privilege principle
├── Encryption enabled for storage, databases, secrets
├── Security groups are not overly permissive (no 0.0.0.0/0 ingress on sensitive ports)
└── Sensitive variables marked with sensitive = true
```
3. **Generate report**
```bash
python3 scripts/tf_module_analyzer.py ./terraform
```
4. **Run security scan**
```bash
python3 scripts/tf_security_scanner.py ./terraform
```
### `/terraform:module` — Module Design
1. **Identify module scope**
- Single responsibility: one module = one logical grouping
- Determine inputs (variables), outputs, and resource boundaries
- Decide: flat module (single directory) vs nesLeer la fuente completa en GitHub (abre una página externa)