Azure Resource Visualizer logo

Azure Resource Visualizer

OrganizationPopular
microsoft
azure-resource-visualizer

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. WHEN: create architecture diagram, visualize Azure resources, show resource relationships, generate Mermaid diagram, analyze resource group, diagram my resources, architecture visualization, resource topology, map Azure infrastructure.

Overview

Publishermicrosoft
Repositoryazure-skills
Skill nameazure-resource-visualizer
Stars
1.5K
Forks
246
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Azure Resource Visualizer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/azure-skills.git /tmp/azure-skills
mkdir -p .claude/skills
cp -r /tmp/azure-skills/skills/azure-resource-visualizer .claude/skills/azure-resource-visualizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Resource Visualizer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure Resource Visualizer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure Resource Visualizer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Azure Resource Visualizer - Architecture Diagram Generator

A user may ask for help understanding how individual resources fit together, or to create a diagram showing their relationships. Your mission is to examine Azure resource groups, understand their structure and relationships, and generate comprehensive Mermaid diagrams that clearly illustrate the architecture.

Core Responsibilities

  1. Resource Group Discovery: List available resource groups when not specified
  2. Deep Resource Analysis: Examine all resources, their configurations, and interdependencies
  3. Relationship Mapping: Identify and document all connections between resources
  4. Diagram Generation: Create detailed, accurate Mermaid diagrams
  5. Documentation Creation: Produce clear markdown files with embedded diagrams

Workflow Process

Step 1: Resource Group Selection

If the user hasn't specified a resource group:

  1. Use your tools to query available resource groups. If you do not have a tool for this, use az.
  2. Present a numbered list of resource groups with their locations
  3. Ask the user to select one by number or name
  4. Wait for user response before proceeding

If a resource group is specified, validate it exists and proceed.

Step 2: Resource Discovery & Analysis

For bulk resource discovery across subscriptions, use Azure Resource Graph queries. See Azure Resource Graph Queries for cross-subscription inventory and relationship discovery patterns.

Once you have the resource group:

  1. Query all resources in the resource group using Azure MCP tools or az.

  2. Analyze each resource type and capture:

    • Resource name and type
    • SKU/tier information
    • Location/region
    • Key configuration properties
    • Network settings (VNets, subnets, private endpoints)
    • Identity and access (Managed Identity, RBAC)
    • Dependencies and connections
  3. Map relationships by identifying:

    • Network connections: VNet peering, subnet assignments, NSG rules, private endpoints
    • Data flow: Apps → Databases, Functions → Storage, API Management → Backends
    • Identity: Managed identities connecting to resources
    • Configuration: App Settings pointing to Key Vaults, connection strings
    • Dependencies: Parent-child relationships, required resources

Important: You must only use placeholder names to represent secret values, such as keys, connection strings, Key Vault secrets, etc. Use meaningful placeholder names to represent each secret in the diagram. Never put secret values in the resource diagram.

Step 3: Diagram Construction

Create a detailed Mermaid diagram using the graph TB (top-to-bottom) or graph LR (left-to-right) format.

See example-diagram.md for a complete sample architecture diagram.

Key Diagram Requirements:

  • Group by layer or purpose: Network, Compute, Data, Security, Monitoring
  • Include details: SKUs, tiers, important settings in node labels (use <br/> for line breaks)
  • Label all connections: Describe what flows between resources (data, identity, network)
  • Use meaningful node IDs: Abbreviations that make sense (APP, FUNC, SQL, KV)
  • Visual hierarchy: Subgraphs for logical grouping
  • Connection types:
    • --> for data flow or dependencies
    • -.-> for optional/conditional connections
    • ==> for critical/primary paths

Resource Type Examples:

  • App Service: Include plan tier (B1, S1, P1v2)
  • Functions: Include runtime (.NET, Python, Node)
  • Databases: Include tier (Basic, Standard, Premium)
  • Storage: Include redundancy (LRS, GRS, ZRS)
  • VNets: Include address space
  • Subnets: Include address range

Step 4: File Creation

Use template-architecture.md as a template and create a markdown file named [resource-group-name]-architecture.md with:

  1. Header: Resource group name, subscription, region
  2. Summary: Brief overview of the architecture (2-3 paragraphs)
  3. Resource Inventory: Table listing all resources with types and key properties
  4. Architecture Diagram: The complete Mermaid diagram
  5. Relationship Details: Explanation of key connections and data flows
  6. Notes: Any important observations, potential issues, or recommendations

Operating Guidelines

Quality Standards

  • Accuracy: Verify all resource details before including in diagram
  • Completeness: Don't omit resources; include everything in the resource group
  • Clarity: Use clear, descriptive labels and logical grouping
  • Detail Level: Include configuration details that matter for architecture understanding
  • Relationships: Show ALL significant connections, not just obvious ones

Tool Usage Patterns

  1. Azure MCP Search:

    • Use intent="list resource groups" to discover resource groups
    • Use intent="list resources in group" with group name to get all resources
    • Use intent="get resource details" for individual resource analysis
    • Use command parameter when you need specific Azure operations
  2. File Creation:

    • Always create in workspace root or a docs/ folder if it exists
    • Use clear, descriptive filenames: [rg-name]-architecture.md
    • Ensure Mermaid syntax is valid (test syntax mentally before output)
  3. Terminal (when needed):

    • Use Azure CLI for complex queries not available via MCP
    • Example: az resource list --resource-group <name> --output json
    • Example: az network vnet show --resource-group <name> --name <vnet-name>

Constraints & Boundaries

Always Do:

  • ✅ List resource groups if not specified
  • ✅ Wait for user selection before proceeding
  • ✅ Analyze ALL resources in the group
  • ✅ Create detailed, accurate diagrams
  • ✅ Include configuration details in node labels
  • ✅ Group resources logically with subgraphs
  • ✅ Label all connections descriptively
  • ✅ Create a complete markdown file with diagram

Never Do:

  • ❌ Skip resources because they seem unimportant
  • ❌ Make assumptions about resource relationships without verification
  • ❌ Create incomplete or placeholder diagrams
  • ❌ Omit configuration details that affect architecture
  • ❌ Proceed without confirming resource group selection
  • ❌ Generate invalid Mermaid syntax
  • ❌ Modify or delete Azure resources (read-only analysis)

Edge Cases & Error Handling

  • No resources found: Inform user and verify resource group name
  • Permission issues: Explain what's missing and suggest checking RBAC
  • Complex architectures (50+ resources): Consider creating multiple diagrams by layer
  • Cross-resource-group dependencies: Note external dependencies in diagram notes
  • Resources without clear relationships: Group in "Other Resources" section

Output Format Specifications

Mermaid Diagram Syntax

  • Use graph TB (top-to-bottom) for vertical layouts
  • Use graph LR (left-to-right) for horizontal layouts (better for wide architectures)
  • Subgraph syntax: subgraph "Descriptive Name"
  • Node syntax: ID["Display Name<br/>Details"]
  • Connection syntax: SOURCE -->|"Label"| TARGET

Markdown Structure

  • Use H1 for main title
  • Use H2 for major sections
  • Use H3 for subsections
  • Use tables for resource inventories
  • Use bullet lists for notes and recommendations
  • Use code blocks with mermaid language tag for diagrams

Success Criteria

A successful analysis includes:

  • ✅ Valid resource group identified
  • ✅ All resources discovered and analyzed
  • ✅ All significant relationships mapped
  • ✅ Detailed Mermaid diagram with proper grouping
  • ✅ Complete markdown file created
  • ✅ Clear, actionable documentation
  • ✅ Valid Mermaid syntax that renders correctly
  • ✅ Professional, architect-level output

Your goal is to provide clarity and insight into Azure architectures, making complex resource relationships easy to understand through excellent visualization.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Azure Resource Visualizer AI skill do?

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. WHEN: create architecture diagram, visualize Azure resources, show resource relationships, generate Mermaid diagram, analyze resource group, diagram my resources, architecture visualization, resource topology, map Azure infrastructure.

Why use Azure Resource Visualizer on TypingMind?

Because you install it once and use it with any model. Azure Resource Visualizer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure Resource Visualizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/azure-skills/tree/main/skills/azure-resource-visualizer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Azure Resource Visualizer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure Resource Visualizer?

As many as you like. As long as a model supports skills, you can use Azure Resource Visualizer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure Resource Visualizer AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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