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Azure Diagrams

  • 506 installs
  • 30 repo stars
  • Updated April 7, 2026
  • eraserlabs/eraser-io

azure-diagrams is an agent skill that calls the Eraser API to render Azure architecture diagrams from ARM templates, CLI output, or descriptions for developers documenting cloud infrastructure.

About

azure-diagrams is version 1.0.0 skill from eraserlabs/eraser-io that generates clean Azure architecture diagrams through the Eraser API. Agents activate it when users supply ARM (Azure Resource Manager) JSON templates, Azure CLI command output, or plain-language infrastructure descriptions covering resource groups, VNets, VMs, and storage. The skill requires network access and uses Read, Write, and Bash curl tooling to submit payloads and retrieve diagram artifacts. Developers reach for azure-diagrams when onboarding teammates, writing runbooks, or reviewing deployments without manually dragging icons in a diagram editor. It tags common Azure resources—arm, vnet, vm, storage—and fits teams standardizing infra visuals alongside IaC repos under MIT license from Eraser Labs. Metadata tags include azure, diagram, arm, resource-group, vnet, vm, and storage for retrieval. Outputs complement IaC pull requests, architecture decision records, and onboarding docs where ARM JSON already defines the source of truth for deployed resources.

  • Parses ARM JSON templates, Azure CLI output, and natural language descriptions
  • Automatically maps Resource Groups, VNets, subnets, VMs, Storage Accounts and service connections
  • Generates Eraser DSL then renders via Eraser /api/render/elements endpoint
  • Produces publication-ready cloud-architecture diagrams in seconds
  • Requires only network access to call the Eraser API

Azure Diagrams by the numbers

  • 506 all-time installs (skills.sh)
  • Ranked #369 of 1,039 Cloud & Infrastructure skills by installs in the Skillselion catalog
  • Data as of Jul 24, 2026 (Skillselion catalog sync)
npx skills add https://github.com/eraserlabs/eraser-io --skill azure-diagrams

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Listed on Skillselion
Installs506
repo stars30
Last updatedApril 7, 2026
Repositoryeraserlabs/eraser-io

How do you diagram Azure infra from ARM templates?

Instantly turn Azure ARM templates, CLI output, or plain descriptions into clean architecture diagrams.

Who is it for?

Cloud engineers documenting Azure deployments who already maintain ARM templates or CLI inventories and want automated Eraser diagrams.

Skip if: Teams on AWS-only or GCP-only stacks without Azure assets should skip azure-diagrams.

When should I use this skill?

User provides ARM JSON, Azure CLI output, or asks to visualize Azure resource groups, VNets, VMs, or storage.

What you get

Eraser-generated Azure architecture diagrams covering resource groups, VNets, VMs, and storage layouts.

  • Azure architecture diagrams
  • Documented cloud resource topology

By the numbers

  • Ships as version 1.0.0 from Eraser Labs under MIT license
  • Targets ARM templates, Azure CLI output, and natural language Azure descriptions

Files

SKILL.mdMarkdownGitHub ↗

Azure Diagram Generator

Generates architecture diagrams for Azure infrastructure from ARM templates, Azure CLI output, or natural language descriptions.

When to Use

Activate this skill when:

  • User has ARM (Azure Resource Manager) templates (JSON)
  • User provides Azure CLI output (e.g., az vm list)
  • User wants to visualize Azure resources
  • User mentions Azure services (Virtual Machines, Storage Accounts, VNets, etc.)
  • User asks to "diagram my Azure infrastructure"

How It Works

This skill generates Azure-specific diagrams by parsing Azure resources and calling the Eraser API directly:

1. Parse Azure Resources: Extract resources from ARM templates, CLI output, or descriptions 2. Map Azure Relationships: Identify Resource Groups, VNets, subnets, and service connections 3. Generate Eraser DSL: Create Eraser DSL code from Azure resources 4. Call Eraser API: Use /api/render/elements with diagramType: "cloud-architecture-diagram"

Instructions

When the user provides Azure infrastructure information:

1. Parse the Source

  • ARM Templates: Extract resources array, identify types (Microsoft.Compute/virtualMachines, etc.)
  • CLI Output: Parse JSON output from az commands
  • Description: Identify Azure service names and relationships

2. Identify Azure Components

  • Networking: Virtual Networks (VNets), Subnets, Network Security Groups, Load Balancers
  • Compute: Virtual Machines, Virtual Machine Scale Sets, App Services, Functions
  • Storage: Storage Accounts, Blob Storage, File Shares
  • Databases: SQL Databases, Cosmos DB, Redis Cache
  • Security: Network Security Groups, Azure AD, Key Vault
  • Load Balancing: Application Gateway, Load Balancer, Traffic Manager
  • Other: Service Bus, Event Hubs, API Management

3. Map Relationships

  • VMs in subnets
  • Subnets in VNets
  • VNets in Resource Groups
  • Storage accounts accessed by VMs
  • Databases accessed by applications
  • Network Security Groups attached to subnets

4. Generate Eraser DSL Convert Azure 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: "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

5. 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
     }'

6. Track Sources During Analysis

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

  • Internal files: Record each file path you read and what information was extracted (e.g., infra/main.bicep - VNet and subnet definitions)
  • External references: Note any documentation, examples, or URLs consulted (e.g., Azure architecture best practices documentation)
  • Annotations: For each source, note what it contributed to the diagram

7. 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

{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.

Azure-Specific Tips

  • Resource Groups: Show Resource Groups as logical containers
  • VNets as Containers: Always show VNets containing subnets and resources
  • Network Security Groups: Include NSG rules and attachments
  • Subscriptions: Note subscription context if provided
  • Data Flow: Show traffic flow (Internet → Application Gateway → VM → SQL Database)
  • Use Azure Icons: Request Azure-specific styling in the description

Example: ARM Template with Multiple Azure Services

User Input

{
  "resources": [
    {
      "type": "Microsoft.Resources/resourceGroups",
      "name": "rg-main"
    },
    {
      "type": "Microsoft.Network/virtualNetworks",
      "name": "myVNet",
      "properties": {
        "addressSpace": {
          "addressPrefixes": ["10.0.0.0/16"]
        },
        "subnets": [
          {
            "name": "subnet1",
            "properties": {
              "addressPrefix": "10.0.1.0/24"
            }
          }
        ]
      }
    },
    {
      "type": "Microsoft.Compute/virtualMachines",
      "name": "myVM",
      "properties": {
        "hardwareProfile": {
          "vmSize": "Standard_B1s"
        }
      }
    },
    {
      "type": "Microsoft.Web/sites",
      "name": "myAppService",
      "properties": {
        "serverFarmId": "/subscriptions/.../serverfarms/myPlan"
      }
    },
    {
      "type": "Microsoft.Storage/storageAccounts",
      "name": "mystorageaccount"
    },
    {
      "type": "Microsoft.Sql/servers",
      "name": "mysqlserver",
      "properties": {
        "administratorLogin": "admin"
      }
    }
  ]
}

Expected Behavior

1. Parses ARM template:

  • Resource Group: rg-main (container)
  • Networking: VNet with subnet
  • Compute: VM, App Service
  • Storage: Storage Account
  • Database: SQL Server

2. Generates DSL showing Azure service diversity:

   resource-group [label: "Resource Group rg-main"] {
     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"]
       }
     }
     myAppService [icon: azure-app-service, label: "App Service"]
     mystorageaccount [icon: azure-storage, label: "Storage Account"]
     mysqlserver [icon: azure-sql, label: "SQL Server"]
   }

   myAppService -> mystorageaccount
   myVM -> mysqlserver

Important: All label text must be on a single line within quotes. Azure-specific: Show Resource Groups as containers, include App Services, Storage Accounts, and SQL databases with proper Azure icons.

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

Example: Azure CLI Output

User Input

User runs: az vm list --output json
Provides JSON output

Expected Behavior

1. Parses JSON to extract:

  • VM names, sizes, states
  • Resource groups
  • Network interfaces
  • Storage accounts

2. Formats and calls API

Related skills

How it compares

Pick azure-diagrams over generic diagram skills when inputs are Azure ARM or CLI artifacts and you want Eraser API-native Azure resource visuals.

FAQ

What inputs does azure-diagrams accept?

azure-diagrams accepts Azure ARM JSON templates, Azure CLI command output, or natural language descriptions of Azure infrastructure, then sends them to the Eraser API to produce architecture diagrams.

Does azure-diagrams require network access?

azure-diagrams requires network access to call the Eraser API and lists Bash curl among allowed tools alongside Read and Write for submitting diagram requests.

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