.github/plugins/azure-skills/skills/azure-resource-visualizer/SKILL.md
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.
npx skillsauth add microsoft/skills azure-resource-visualizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
If the user hasn't specified a resource group:
az.If a resource group is specified, validate it exists and proceed.
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:
Query all resources in the resource group using Azure MCP tools or az.
Analyze each resource type and capture:
Map relationships by identifying:
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:
<br/> for line breaks)--> for data flow or dependencies-.-> for optional/conditional connections==> for critical/primary pathsResource Type Examples:
Use template-architecture.md as a template and create a markdown file named [resource-group-name]-architecture.md with:
Azure MCP Search:
intent="list resource groups" to discover resource groupsintent="list resources in group" with group name to get all resourcesintent="get resource details" for individual resource analysiscommand parameter when you need specific Azure operationsFile Creation:
docs/ folder if it exists[rg-name]-architecture.mdTerminal (when needed):
az resource list --resource-group <name> --output jsonaz network vnet show --resource-group <name> --name <vnet-name>Always Do:
Never Do:
graph TB (top-to-bottom) for vertical layoutsgraph LR (left-to-right) for horizontal layouts (better for wide architectures)subgraph "Descriptive Name"ID["Display Name<br/>Details"]SOURCE -->|"Label"| TARGETmermaid language tag for diagramsA successful analysis includes:
Your goal is to provide clarity and insight into Azure architectures, making complex resource relationships easy to understand through excellent visualization.
tools
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
development
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
testing
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
testing
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".