skills/eraserlabs/eraser-io/bicep-diagrams

bicep-diagrams

SKILL.md

Bicep Diagram Generator

Generates architecture diagrams directly from Azure Bicep files. Bicep is a domain-specific language (DSL) for deploying Azure resources declaratively.

When to Use

Activate this skill when:

  • User has Bicep files (.bicep) and wants to visualize the infrastructure
  • User asks to "diagram my Bicep" or "visualize this Bicep infrastructure"
  • User mentions Bicep or Azure Bicep
  • User wants to see the architecture of their Bicep-deployed resources

How It Works

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

  1. Parse Bicep Files: Identify resource declarations, modules, parameters, and outputs
  2. Extract Relationships: Map dependencies, resource references, and module hierarchies
  3. Generate Eraser DSL: Create Eraser DSL code from Bicep resources
  4. Call Eraser API: Use /api/render/elements with diagramType: "cloud-architecture-diagram"

Instructions

When the user provides Bicep code:

  1. Parse the Bicep

    • Identify all resource declarations (Microsoft.Compute/virtualMachines, etc.)
    • Extract module declarations and their configurations
    • Note param and output definitions
    • Identify var variables and their usage
  2. Map Relationships

    • Track resource dependencies (e.g., dependsOn or implicit dependencies)
    • Group resources by type (compute, networking, storage, etc.)
    • Identify VNets as containers for subnets and resources
    • Note Network Security Groups, Key Vaults, and other security resources
  3. Generate Eraser DSL Convert Bicep 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 VM sizes, include them in the same quoted label string: [label: "VNet 10.0.0.0/16"]

    Example:

    myVNet [label: "VNet 10.0.0.0/16"] {
      subnet1 [label: "Subnet 1"] {
        myVM [icon: azure-vm, label: "Virtual Machine"]
        gateway [icon: azure-app-gateway]
      }
      subnet2 [label: "Subnet 2"] {
        database [icon: azure-sql]
      }
    }
    storage [icon: azure-storage]
    myVNet -> myVM
    myVM -> 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
    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 Bicep files and resources to generate the diagram, track:

    • Internal files: Record each Bicep file path you read and what resources were extracted (e.g., infra/main.bicep - VNet and subnet definitions, infra/sql.bicep - SQL Database configuration)
    • External references: Note any documentation, examples, or URLs consulted (e.g., Azure Bicep documentation, Azure 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 Modules

    • If modules are used, show module boundaries
    • Include module parameters and outputs
    • Show how modules connect to main resources

Bicep-Specific Tips

  • Show Resource Groups: Bicep deployments target resource groups
  • VNets as Containers: Show VNets containing subnets and resources
  • Include Dependencies: Show dependsOn relationships
  • Module Structure: If modules are used, show their boundaries
  • Parameters: Note key parameters that affect resource configuration
  • Use Azure Icons: Request Azure-specific styling

Example: Bicep with Parameters and Modules

User Input

@description('The name of the Virtual Network')
param vnetName string = 'myVNet'
@description('The address prefix for the VNet')
param vnetAddressPrefix string = '10.0.0.0/16'
@description('The address prefix for the subnet')
param subnetAddressPrefix string = '10.0.1.0/24'
@description('VM size')
param vmSize string = 'Standard_B1s'

// Main VNet resource
resource virtualNetwork 'Microsoft.Network/virtualNetworks@2021-05-01' = {
  name: vnetName
  location: resourceGroup().location
  properties: {
    addressSpace: {
      addressPrefixes: [vnetAddressPrefix]
    }
    subnets: [
      {
        name: 'subnet1'
        properties: {
          addressPrefix: subnetAddressPrefix
        }
      }
    ]
  }
}

// VM resource with dependsOn
resource virtualMachine 'Microsoft.Compute/virtualMachines@2021-11-01' = {
  name: 'myVM'
  location: resourceGroup().location
  properties: {
    hardwareProfile: {
      vmSize: vmSize
    }
  }
  dependsOn: [virtualNetwork]
}

// Module usage
module storageModule './modules/storage.bicep' = {
  name: 'storage'
  params: {
    location: resourceGroup().location
  }
}

Expected Behavior

  1. Parses Bicep:

    • Parameters: vnetName, vnetAddressPrefix, subnetAddressPrefix, vmSize
    • Resources: VNet with subnet, VM with dependsOn relationship
    • Module: Storage module with parameters
  2. Generates DSL showing Bicep-specific features:

    myVNet [label: "VNet 10.0.0.0/16"] {
      subnet1 [label: "Subnet 1 10.0.1.0/24"] {
        myVM [icon: azure-vm, label: "VM Standard_B1s"]
      }
    }
    
    storage-module [label: "Storage Module"] {
      storage-account [icon: azure-storage]
    }
    
    myVNet -> myVM
    

    Important: All label text must be on a single line within quotes. Bicep-specific: Show modules as containers, include dependsOn relationships, note parameter usage in resource configuration.

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

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

Result

User receives a diagram showing:

  • VNet as a container
  • Subnet nested inside VNet
  • VM in the subnet
  • Dependency relationship shown
  • Proper Azure styling
Weekly Installs
195
GitHub Stars
9
First Seen
Jan 27, 2026
Installed on
gemini-cli165
codex161
opencode159
github-copilot156
amp142
kimi-cli141