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terraform-diagrams — Claude Code skill: architecture diagrams

Reads .tf files and draws the infrastructure: resources, modules, connections. Useful when you need a picture of the architecture instead of reading HCL.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add eraserlabs/eraser-io --skill terraform-diagrams -a claude-code
Open on GitHub

What terraform-diagrams does

The skill parses Terraform code and picks out resource, module and data blocks, plus variables and outputs. Then it maps dependencies — which resource points at which through subnet_id or vpc_id — groups everything by provider and turns it into Eraser DSL. VPCs and VNets become containers holding subnets and instances.

The DSL goes to /api/render/elements as a POST with diagramType: "cloud-architecture-diagram". The response carries an image URL and a link to the Eraser editor. You need ERASER_API_KEY in your environment and network access, otherwise the request fails. Theme comes from ERASER_THEME and defaults to dark.

Output stays short: the diagram, the editor link, a list of files it read, and the DSL in a code block. No extra sections unless you ask for them. Multi-provider Terraform gets split into AWS, Azure and GCP sections.

What it helps with

  • see a VPC layout with subnets and instances without drawing it by hand
  • show teammates the architecture behind existing .tf files
  • map Terraform modules to their boundaries and links
  • put AWS, Azure and GCP resources on one diagram
  • open the result in an editor and adjust it there

Example prompts for the agent

  • Diagram my Terraform in infra/main.tf
  • Visualize the Terraform under infra/
  • Draw the architecture from my .tf files

How to install terraform-diagrams

1Skills CLI (Vercel)

npx skills add eraserlabs/eraser-io --skill terraform-diagrams -a claude-code

2Manually: put the files in place

~/.claude/skills/terraform-diagrams/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/terraform-diagrams/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about terraform-diagrams

How do I install terraform-diagrams in Claude?

Run npx skills add eraserlabs/eraser-io --skill terraform-diagrams -a claude-code. The skill lands at ~/.claude/skills/terraform-diagrams/SKILL.md.

What does terraform-diagrams do?

It reads Terraform files, extracts resources and their relationships, converts them to Eraser DSL and calls the Eraser API to render an architecture image.

What does the skill need to run?

Network access for the Eraser API call and an ERASER_API_KEY environment variable. The diagram theme comes from ERASER_THEME and defaults to dark.

Source text

SKILL.md · MIT
---
name: terraform-diagrams
description: 'Generates architecture diagrams from Terraform code. Use when user has .tf files or asks to visualize Terraform infrastructure.'
license: MIT
compatibility: Requires network access to call Eraser API
allowed-tools: Read Write Bash(curl:*)
metadata:
  version: "1.0.0"
  author: Eraser Labs
  tags: terraform, diagram, infrastructure, aws, azure, gcp, iac, hcl
---

# Terraform Diagram Generator

Generates architecture diagrams directly from Terraform `.tf` files. Specializes in parsing Terraform code and visualizing infrastructure resources, modules, and their relationships.

## When to Use

Activate this skill when:

- User has Terraform files (`.tf`, `.tfvars`) and wants to visualize the infrastructure
- User asks to "diagram my Terraform" or "visualize this infrastructure"
- User mentions Terraform, HCL, or infrastructure-as-code
- User wants to see the architecture of their Terraform-managed resources

## How It Works

This skill generates Terraform-specific diagrams by parsing Terraform code and calling the Eraser API directly:

1. **Parse Terraform Files**: Identify resources, modules, data sources, and variables
2. **Extract Relationships**: Map dependencies, resource connections, and module hierarchies
3. **Generate Eraser DSL**: Create Eraser DSL code from Terraform resources
4. **Call Eraser API**: Use `/api/render/elements` with `diagramType: "cloud-architecture-diagram"`

## Instructions

When the user provides Terraform code:

1. **Parse the Terraform**

   - Identify all `resource` blocks (AWS, Azure, GCP, etc.)
   - Extract `module` blocks and their configurations
   - Note `data` sources and their dependencies
   - Identify `variable` and `output` definitions

2. **Map Relationships**

   - Track resource dependencies (e.g., `subnet_id = aws_subnet.public.id`)
   - Group resources by provider (AWS, Azure, GCP)
   - Identify VPCs/VNets as containers for other resources
   - Note security groups, IAM roles, and networking rules

3. **Generate Eraser DSL** Convert Terraform resources to Eraser DSL:

   - **CRITICAL: Label Formatting Rules**
     - Labels MUST be on a single line - NEVER use newlines inside label attributes
     - Keep labels simple and readable - prefer separate labels over concatenating too much metadata
     - Format DSL with proper line breaks (one node/group per line, but labels stay on single lines)
     - If including metadata like CIDR blocks or instance types, include them in the same quoted label string: `[label: "VPC 10.0.0.0/16"]`

   Example:

   ```
   main-vpc [label: "VPC 10.0.0.0/16"] {
     public-subnet [label: "Public Subnet 10.0.1.0/24"] {
       web-server [icon: aws-ec2, label: "Web Server t3.micro"]
       load-balancer [icon: aws-elb]
     }
     private-subnet [label: "Private Subnet"] {
       database [icon: aws-rds]
     }
   }
   load-balancer -> web-server
   web-server -> database
   ```

4. **Make the HTTP Request**

   **IMPORTANT**: You MUST execute this curl command after generating the DSL. Never stop after generating DSL without making the API call.

   **CRITICAL**: In the `X-Skill-Source` header below, you MUST replace the value with your AI agent name:
   - If you are Claude (Anthropic), use: `claude`
   - If you are running in Cursor, use: `cursor`
   - If you are ChatGPT (OpenAI), use: `chatgpt`
   - If you are Gemini (Google), use: `gemini`
   - Otherwise, use your model/agent name in lowercase

   ```bash
   curl -X POST https://app.eraser.io/api/render/elements \
     -H "Content-Type: application/json" \
     -H "X-Skill-Source: eraser-skill" \
     -H "Authorization: Bearer ${ERASER_API_KEY}" \
     -d '{
       "elements": [{
         "type": "diagram",
         "id": "diagram-1",
         "code": "<your generated DSL>",
         "diagramType": "cloud-architecture-diagram"
       }],
       "scale": 2,
       "theme": "${ERASER_THEME:-dark}",
       "background": true
     }'
   ```

5. **Track Sources During Analysis**

   As you analyze Terraform files and resources to generate the diagram, track:

   - **Internal files**: Record each Terraform file path you read and what resources were extracted (e.g., `infra/main.tf` - VPC and subnet definitions, `infra/rds.tf` - Database configuration)
   - **External references**: Note any documentation, examples, or URLs consulted (e.g., Terraform AWS provider documentation, AWS architecture best practices)
   - **Annotations**: For each source, note what it contributed to the diagram

6. **Handle the Response**

   **CRITICAL: Minimal Output Format**

   Your response MUST always include these elements with clear headers:

   1. **Diagram Preview**: Display with a header
      ```
      ## Diagram
      ![{Title}]({imageUrl})
      ```
      Use the ACTUAL `imageUrl` from the API response.

   2. **Editor Link**: Display with a header
      ```
      ## Open in Eraser
      [Edit this diagram in the Eraser editor]({createEraserFileUrl})
      ```
      Use the ACTUAL URL from the API response.

   3. **Sources section**: Brief list of files/resources analyzed (if applicable)
      ```
      ## Sources
      - `path/to/file` - What was extracted
      ```

   4. **Diagram Code section**: The Eraser DSL in a code block with `eraser` language tag
      ```
      ## Diagram Code
      ```eraser
      {DSL code here}
      ```
      ```

   5. **Learn More link**: `You can learn more about Eraser at https://docs.eraser.io/docs/using-ai-agent-integrations`

   **Additional content rules:**
   - If the user ONLY asked for a diagram, include NOTHING beyond the 5 elements above
   - If the user explicitly asked for more (e.g., "explain the architecture", "suggest improvements"), you may include that additional content
   - Never add unrequested sections like Overview, Security Considerations, Testing, etc.

   The default output should be SHORT. The diagram image speaks for itself.

7. **Handle Multiple Providers**
   - If Terraform uses multiple providers, group by provider
   - Create separate sections for AWS, Azure, GCP resources
   - Show cross-provider connections if applicable

## Terraform-Specific Tips

- **Group by Module**: If modules are used, show module boundaries
- **Show VPCs/VNets as Containers**: These should visually contain subnets and resources
- **Include Data Flows**: Show how resources connect (e.g., ALB → EC2 → RDS)
- **Highlight Security**: Include security groups, IAM roles, and network ACLs
- **Show Resource Types**: Use provider-specific icons (AWS, Azure, GCP)
- **Include CIDR Blocks**: Show network addressing for VPCs and subnets

## Example: Multi-Provider Terraform

### User Input

```hcl
# AWS Resources
resource "aws_vpc" "main" {
  cidr_block = "10.0.0.0/16"
}

resource "aws_subnet" "public" {
  vpc_id     = aws_vpc.main.id
  cidr_block = "10.0.1.0/24"
}

resource "aws_instance" "web" {
  subnet_id     = aws_subnet.public.id
  instance_type = "t3.micro"
}

# Azure Resources (multi-provider)
resource "azurerm_resource_group" "main" {
  name     = "rg-main"
  location = "East US"
}

resource "azurerm_virtual_network" "main" {
  name                = "vnet-main"
  resource_group_name  = azurerm_resource_group.main.name
  address_space        = ["10.1.0.0/16"]
}

# Module usage
module "database" {
  source = "./modules/rds"
  vpc_id = aws_vpc.main.id
}
```

### Expected Behavior

1. Parses Terraform:

   - **AWS**: VPC, subnet, EC2 instance
   - **Azure**: Resource group, VNet (multi-provider setup)
   - **Module**: Database module with dependency on VPC

2. Generates DSL showing multi-provider and module structure:

   ```
   # AWS Resources
   aws-vpc [label: "AWS VPC 10.0.0.0/16"] {
     aws-subnet [label: "Public Subnet 10.0.1.0/24"] {
       web-server [icon: aws-ec2, label: "Web Server t3.micro"]
     }
   }

   # Azure Resources
   resource-group [label: "Resource Group rg-main"] {
     azure-vnet [label: "Azure VNet 10.1.0.0/16"]
   }

   # Module
   database-module [label: "Database Module"] {
     rds-instance [icon: aws-rds]
   }

   aws-vpc -> database-module
   ```

   **Important**: All label text must be on a single line within quotes. Terraform-specific: Show modules as containers, group by provider, include resource dependencies.

3. Calls `/api/render/elements` with `diagramType: "cloud-architecture-diagram"`

### Result

User receives a diagram showing:

- VPC as a container
- Public subnet nested inside VPC
- EC2 instance in the subnet
- Proper AWS styling

© Eraser Labs · MIT · eraserlabs/eraser-io

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