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

2. Identify all resource blocks (AWS, Azure, GCP, etc.)

3. Extract module blocks and their configurations
4. Note data sources and their dependencies

5. Identify variable and output definitions

6. Map Relationships

7. Track resource dependencies (e.g., subnet_id = aws_subnet.public.id)

8. Group resources by provider (AWS, Azure, GCP)
9. Identify VPCs/VNets as containers for other resources

10. Note security groups, IAM roles, and networking rules

11. Generate Eraser DSL Convert Terraform resources to Eraser DSL:

12. 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

1. 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 }'

1. 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

• 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 Codeeraser
   {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.

1. Handle Multiple Providers
2. If Terraform uses multiple providers, group by provider
3. Create separate sections for AWS, Azure, GCP resources
4. 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

# 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:

2. AWS: VPC, subnet, EC2 instance

3. Azure: Resource group, VNet (multi-provider setup)

4. Module: Database module with dependency on VPC

5. 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.

1. 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