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azure-diagramsAzure diagrams 图表绘制

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

总安装

8,608

周安装

366

GitHub Stars

17

下载量

3,016
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:azure-diagrams(Azure diagrams 图表绘制)
来源仓库:https://github.com/eraserlabs/eraser-io
仓库路径:skills/azure-diagrams
安装命令:
npx skills add https://github.com/eraserlabs/eraser-io --skill azure-diagrams
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/eraserlabs/eraser-io --skill azure-diagrams

简介

从 ARM 模板或自然语言描述自动生成 Azure 架构图,支持多种视图导出。

  • 适用于系统设计评审、迁移方案可视化及运维文档绘制。
  • 解析 Azure CLI 输出结果并转换为 Eraser 兼容格式,简化输入流程。
  • 调用 Eraser API 前需确保网络连通性与 API 密钥有效性。
  • 生成的图表仅供内部参考,正式发布前建议人工校验布局准确性。

SKILL.md

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

  1. 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

  1. 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

  1. Generate Eraser DSL Convert Azure resources to Eraser DSL: 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

- 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"]

  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: 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}'

- 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

  1. 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

  1. Handle the Response CRITICAL: Minimal Output Format Your response MUST always include these elements with clear headers: Additional content rules: The default output should be SHORT. The diagram image speaks for itself.

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` - 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.

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

  1. 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.
  2. 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

  1. Formats and calls API

适合场景

01

Azure 资源规划

02

云服务升级

03

基础设施检查

04

企业云环境自动化

能力概览

能力 1

整理 Azure 服务操作流程

能力 2

提示 CLI/MCP 前置条件

能力 3

辅助云资源检查和规划

能力 4

保留官方服务来源线索

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.92%
按下载量换算1,083

Claude

27.62%
按下载量换算833

Cursor

17.73%
按下载量换算535

Gemini CLI

8.75%
按下载量换算264

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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