# terraform-service-scaffold

Generates service-level Terraform infrastructure with AWS modules, environment configurations, and ArgoCD GitOps templates.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 109
- Author: c0x12c
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/c0x12c/ai-toolkit/tree/HEAD/toolkit/skills/terraform-service-scaffold/SKILL.md
- Updated: 2026-06-18
- HTML: https://affpapa.org/en/nevibecode/skills/terraform-service-scaffold

## What it does

The skill asks for the target service name, compute runtime (ECS or EKS), and supporting cloud resources such as RDS Postgres, Redis cache, S3 buckets, or SQS queues. Rather than crafting HCL from scratch, it relies on the `spartan-stratos/spartan-sre-wiki` repository as the primary template origin. It stamps out single-root or multiple-root layouts using `templates/scaffold.sh`.

When the wiki repo is unreachable, the skill uses an internal HCL blueprint as a fallback. It organizes live orchestration inside `terraform/live/` with provider blocks, common tags, and remote state lookups reading shared VPC subnets from S3. Resource definitions split cleanly into separate files within `terraform/modules/{service}/`.

GitOps onboarding requires cloning `spartan-sre-wiki` beforehand to execute the monorepo scaffold and wire up ArgoCD manifests.

## Requirements
- Works with: Terraform

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add c0x12c/ai-toolkit --skill terraform-service-scaffold -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/terraform-service-scaffold/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/terraform-service-scaffold/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add c0x12c/ai-toolkit --skill terraform-service-scaffold -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/terraform-service-scaffold/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add c0x12c/ai-toolkit --skill terraform-service-scaffold -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/terraform-service-scaffold/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install c0x12c/ai-toolkit terraform-service-scaffold
```

2. **Manually: put the files in place**
- File: `.github/skills/terraform-service-scaffold/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add c0x12c/ai-toolkit --skill terraform-service-scaffold -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/c0x12c/ai-toolkit --path toolkit/skills/terraform-service-scaffold
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/terraform-service-scaffold/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add c0x12c/ai-toolkit --skill terraform-service-scaffold -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/c0x12c/ai-toolkit/tree/HEAD/toolkit/skills/terraform-service-scaffold/SKILL.md

## When to use it
- Scaffold service-level Terraform code for a new microservice
- Configure AWS modules for RDS, Redis, S3, and ECR repositories
- Link service stacks to shared VPC state via S3 remote backends
- Generate data-driven ArgoCD manifests for EKS deployments

## Example prompts
- Generate Terraform infrastructure for a new billing service on ECS with RDS Postgres and an SQS queue.
- Scaffold a single-root Terraform layout for an EKS service using the spartan-sre-wiki templates.
- Create service modules for auth-api with Redis caching and an S3 bucket.

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From the same set: [c0x12c/ai-toolkit](https://affpapa.org/en/nevibecode/by/c0x12c/ai-toolkit.md) — 33 cards

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