Official agent skill

Azv Diagram Azure Sync

by Azure in Azure/AZVerify

Compare a Draw.io Azure architecture diagram against a live Azure environment to detect drift.

OfficialMITAuto-check passedDevOps & Cloud

Install Azv Diagram Azure Sync

skills CLI
$ npx skills add Azure/AZVerify --skill azv-diagram-azure-sync -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Azure/AZVerify azv-diagram-azure-sync --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Azure/AZVerify.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/azv-diagram-azure-sync .claude/skills/azv-diagram-azure-sync && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azv-diagram-azure-sync
GitHub stars
101
Token cost
~3.7k tokens
SKILL.md length
1,740 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Compare a Draw.io Azure architecture diagram against a live Azure environment to detect drift.

  • Works in 12 steps: Check Azure Authentication → Accept Inputs → Parse Diagram into Resource Model → …
  • Tasks that involve Diagrams
  • SKILL.md covers Steps and Important Notes
  • Calls az

What it does

Azv Diagram Azure Sync is an agent skill from Azure/AZVerify, published by the product's own GitHub organization. Compare a Draw.io Azure architecture diagram against a live Azure environment to detect drift. Supports quick mode (existence check) and deep mode (full property-level comparison). Reports differences and offers resolution — update the diagram, update Azure, or selectively resolve per resource.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Diagrams and Cloud architecture. It works with Microsoft Azure, draw.io, Model Context Protocol and GitHub. The licence is MIT.

When your agent uses it

  • Tasks that involve Diagrams
  • Tasks that involve Cloud architecture

Example prompts

  • “/azv-diagram-azure-sync”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Check Azure Authentication
  2. Accept Inputs
  3. Parse Diagram into Resource Model
  4. Discover Azure Environment
  5. Compare Models and Identify Drift
  6. Present Drift Report
  7. Offer Resolution Options
  8. Resolution: Update Diagram
  9. Resolution: Update Azure
  10. Resolution: Selective Updates
  11. Resolution: Property Drifts (Deep Mode Only)
  12. No Action

What it can do on your machine

Read from SKILL.md and the folder at commit d6a2b92. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • az

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use az, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azv Diagram Azure Sync loads about 3.7k tokens when it runs. Until then it costs about 80 tokens; SKILL.md has 1,740 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~80
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Azure/AZVerify at commit d6a2b92, republished under its MIT licence (© Azure). 1,740 words, ~3,678 tokens.

Download SKILL.mdSave it as .claude/skills/azv-diagram-azure-sync/SKILL.md (or your agent's skills folder).
name
azv-diagram-azure-sync
description
Compare a Draw.io Azure architecture diagram against a live Azure environment to detect drift. Supports quick mode (existence check) and deep mode (full property-level comparison). Reports differences and offers resolution — update the diagram, update Azure, or selectively resolve per resource.
license
MIT
metadata.author
AzVerify
metadata.version
1.0
metadata.project
AzVerify

Compare a Draw.io Azure architecture diagram against a live Azure environment and resolve drift. Supports two modes: quick (existence-level) and deep (existence + property-level comparison against all tracked configuration properties).

Input: A Draw.io diagram file (.drawio or .drawio.xml) and an Azure scope — a resource group name or subscription ID. The user can specify both, or the skill will prompt for missing inputs.

Tools required: File system tools (read/write files), Azure MCP server tools (mcp_azure_group_resource_list, mcp_azure_compute, mcp_azure_storage, mcp_azure_subscription_list, etc.), Draw.io MCP (mcp_drawio_create_diagram or mcp_draw_io_create_diagram)

Reference files:

  • .github/skills/shared/azure-resource-model.md — Shared resource metadata model definition
  • .github/skills/shared/azure-stencil-mapping.json — Azure resource type to Draw.io stencil mapping (used for reverse-lookup and diagram generation)
  • .github/skills/shared/azure-deployment-verification.md — Pre-deployment verification rules (MUST run before generating Azure update scripts)
  • .github/skills/shared/azure-resource-configs.md — Per-resource-type configuration schemas with defaults and auto-detection rules
  • .github/skills/shared/data/azure-property-paths.json — Azure Property Retrieval Mapping (MCP tools, CLI fallbacks, ARM JSON paths, severity classifications)

Shared procedures (MUST follow):

  • .github/skills/shared/procedures/azure-authentication.md — Azure session check procedure
  • .github/skills/shared/procedures/diagram-parsing.md — Diagram-to-resource-model parsing procedure
  • .github/skills/shared/procedures/resource-matching.md — Resource matching algorithm
  • .github/skills/shared/procedures/resource-filtering.md — Resource exclusion lists (use "Exclude for Diagrams" column)

Steps

1. Check Azure Authentication

Follow the procedure in .github/skills/shared/procedures/azure-authentication.md. HARD GATE — stop if not authenticated.

2. Accept Inputs

Identify the Draw.io diagram, the Azure scope, and the comparison depth.

2a. Identify Comparison Depth

Determine the depth mode from the user's request:

  • Quick (default): Existence-level comparison only — are the right resources deployed?
  • Deep: Existence + property-level comparison — checks every tracked configuration property (SKU, tier, size, security settings) against expected values from azure-property-paths.json

If the user says "deep", "detailed", "full", "property", or "configuration" → use deep mode. Otherwise default to quick.

2b. Identify the Draw.io Diagram

If the user specifies a file path:

  • Verify the file exists and is a .drawio or .drawio.xml file
  • Read the file contents

If no file is specified:

  • Search the workspace for .drawio files
  • If exactly one is found, use it (announce which file)
  • If multiple are found, present the list and ask the user to select one
  • If none are found, ask the user to provide a diagram file
2c. Identify the Azure Scope

If the user specifies a resource group:

  • Use that resource group as the comparison scope
  • Verify the resource group exists using Azure MCP tools

If the user specifies a subscription:

  • Use that subscription as the comparison scope
  • Note: subscription-level comparison can be noisy — warn the user

If no scope is specified:

  • Check if the diagram contains resource group containers — if so, use those resource group names as the scope
  • If the resource group name(s) can be inferred from the diagram, confirm with the user: "The diagram shows resources in resource group <name>. Should I compare against that resource group?"
  • If the scope cannot be inferred, ask the user: "Which Azure resource group or subscription should I compare this diagram against?"
3. Parse Diagram into Resource Model

Follow the procedure in .github/skills/shared/procedures/diagram-parsing.md to parse the Draw.io XML into a structured resource model.

Display the parsed resource model as a table with columns: #, Resource, Type, Container.

4. Discover Azure Environment

Query the Azure scope to build a resource model of what is actually deployed.

Discovery process:

  1. List all resources in scope:

    • For resource group scope: Use mcp_azure_group_resource_list to get all resources in the specified resource group
    • For subscription scope: Use mcp_azure_subscription_list to get subscriptions, then list resources across the target subscription
  2. Build the Azure resource model: For each discovered resource, create a resource model entry:

    json
    {
      "id": "<resource-name-slug>",
      "type": "<Microsoft.Provider/resourceType>",
      "name": "<resource-name>",
      "resourceGroup": "<resource-group-name>",
      "location": "<region>",
      "properties": {},
      "relationships": []
    }
  3. Enrich with resource-type-specific details where available:

    • Use mcp_azure_compute for VM details (size, OS, status)
    • Use mcp_azure_storage for Storage Account details (SKU, kind, access tier)
    • Use Azure MCP networking tools for VNet, subnet, NSG details
    • Use Azure MCP database tools for SQL, Cosmos DB details
    • Use Azure MCP web/app tools for App Service, Function App details
  4. Discover relationships:

    • VNets → Subnets (containment from resource hierarchy)
    • Resources → Resource Groups (containment)
    • NICs → VMs (connection via NIC's virtualMachine property)
    • Private Endpoints → target resources (connection via privateLinkServiceConnections)
    • App Services → App Service Plans (dependency)
    • Subnets → NSGs (security association)
  5. Exclude infrastructure-only resources: Apply the "Exclude for Diagrams" column from .github/skills/shared/procedures/resource-filtering.md.

  6. Output the Azure resource model as a table with columns: #, Resource, Type, Location.

5. Compare Models and Identify Drift

Follow the matching algorithm in .github/skills/shared/procedures/resource-matching.md to compare diagram resources (Step 3) against Azure resources (Step 4). Use label "Diagram Only" for Model A and "Azure Only" for Model B.

5b. Deep Mode Only: Retrieve and Compare Properties

Skip this step in quick mode.

For each resource matched in both models (In Sync or In Sync with name difference):

  1. Retrieve full properties from Azure using the Azure Property Retrieval Mapping in .github/skills/shared/data/azure-property-paths.json. Use the listed MCP tool (primary) or az CLI command (fallback) for each resource type. Extract all tracked properties using the ARM JSON paths specified in the mapping.

  2. Determine expected values: Use diagram-specified values if available; otherwise use defaults from azure-property-paths.json.

  3. Normalize before comparing: Case-insensitive for enum values (SKUs, tiers, regions). Boolean normalization (true/"true"/"True" → true). Empty collection equivalence ([]/null/absent → equal). Numeric strings ("30" = 30). Region normalization ("West Europe" → "westeurope").

  4. Record property drifts where normalized expected ≠ normalized actual, including property name, expected value (source: diagram/default), actual Azure value, and severity level from azure-property-paths.json.

  5. Refine classification: Matched resources get sub-status: "all properties match" or "properties drifted" (with count per severity level).

6. Present Drift Report

Display a categorized drift report.

Quick mode: Summary table (In Sync / Diagram Only / Azure Only counts), details table (Resource, Type, Status, Notes). If fully in sync, show "✅ Fully in sync!" and stop.

Deep mode: Add property drift information:

  • Summary table adds columns: Critical, Warning, Info (counts of property drifts per resource)
  • For each resource with property drifts, show per-property diff table (Property, Expected, Actual, Severity, Source)
  • Only show properties where expected ≠ actual — matching properties go in a separate "Confirmed In Sync" table

If drift is detected, proceed to Step 7.

7. Offer Resolution Options

When drift is detected, present resolution options to the user.

Quick mode options: Update Diagram (1), Update Azure (2), Selective (3), No action (4).

Deep mode options (vary by drift type):

Drift TypeOptions
Existence onlyUpdate Diagram, Update Azure, Selective, No action
Property onlyResolve Property Drifts, No action
BothUpdate Diagram, Update Azure, Selective, Resolve Property Drifts, No action

Wait for the user's choice before proceeding.

Show full SKILL.md (707 more words)Show less
8. Resolution: Update Diagram

If the user chooses to update the diagram to match Azure:

8a. Confirm destructive operations

List resources to add and remove from the diagram. Warn that diagram removals are irreversible without a backup. Wait for explicit "yes" confirmation; "no" returns to Step 7.

8b. Generate updated diagram

  1. Load the existing diagram XML
  2. Azure-only resources → add mxCell elements with icons from .github/skills/shared/azure-stencil-mapping.json, placed in correct containers. For container resources, create both container and icon cells.
  3. Diagram-only resources → remove the mxCell, its -icon child, and any connected edges
  4. Re-layout, adjust container sizes, save via Draw.io MCP tool

8c. Update Bicep files to match the updated diagram

If main.bicep + .bicepparam exist in the diagram's directory:

  • Re-parse the updated diagram into a resource model
  • Regenerate Bicep files following azv-diagram-to-bicep conventions (reference azure-resource-configs.md, bicep-best-practices.md)
  • Run pre-deployment verification from azure-deployment-verification.md
  • Preserve user-customized .bicepparam values where parameters still apply; add/remove as needed
  • Update module files and main.bicep outputs

If no Bicep files exist, skip this step.

8d. Present result

Show summary: resources added/removed from diagram, path to saved file. If Bicep was regenerated, show a table of changed Bicep files with their changes.

9. Resolution: Update Azure

If the user chooses to update Azure to match the diagram:

9a. Confirm destructive operations

List resources to create and delete, warn that Azure deletions are destructive and may cause data loss. Require user to type "confirm" to proceed; any other response returns to Step 7.

9b. Run deployment verification

Before generating Bicep, read and run the full verification ruleset from .github/skills/shared/azure-deployment-verification.md:

  1. SKU dependency rules — verify companion resources exist
  2. Resource compatibility rules — verify backend protocols, DNS zones
  3. Networking rules — verify subnet sizing, no overlaps

Present verification results. Errors must be auto-fixed where possible. Do not generate code with known errors.

9c. Generate Bicep for resources to create

For diagram-only resources, generate Bicep templates using azure-resource-configs.md and bicep-best-practices.md. Generate .bicepparam with descriptive comments. Follow diagram-to-bicep conventions (parent:, @secure(), @description(), secure defaults).

9d. Generate Bicep for resources to delete

For Azure-only resources that need to be removed, generate a Bicep template that omits those resources. Note: the user can deploy this template in Complete mode to remove them, or manually delete via the Azure portal or CLI.

9e. Present output

Show a summary table of generated files (create Bicep + removal notes) with deployment commands. Warn user to review all files before deploying.

10. Resolution: Selective Updates

If the user chooses selective resolution:

10a. Present per-resource choices

Show a table with columns: #, Resource, Type, Status, Resolve. For each drifted resource, offer direction-specific options (Diagram Only → "Create in Azure / Remove from diagram / Skip"; Azure Only → "Add to diagram / Delete from Azure / Skip"). Wait for user decisions.

10b. Apply decisions

Group into two buckets: diagram updates (follow Step 8 flow including 8c Bicep regeneration) and Azure updates (follow Step 9 flow). Apply confirmation gates per bucket separately.

10c. Present combined result

Show what was changed in each direction and what was skipped.

11. Resolution: Property Drifts (Deep Mode Only)

If the user chooses to resolve property drifts:

11a. Present per-resource property choices: table with columns #, Property, Expected, Actual, Severity, Action (Update Azure / Accept Azure / Skip). Wait for per-property decisions.

11b. For "Update Azure" properties: generate Bicep snippets using existing references targeting only drifted properties, plus CLI command alternatives. Note VM deallocation when vmSize changes.

11c. For "Accept Azure" decisions: update .bicepparam values to match Azure actuals. Present for confirmation before writing.

11d. Show summary of all resolutions and wait for explicit confirmation before applying.

12. No Action

If the user chooses no action, confirm the report is for reference only and suggest related skills (azv-diagram-to-bicep, azv-sketch-to-diagram).


Important Notes

  • This skill operates independently — it does not require sketch-to-diagram or diagram-to-bicep.
  • Quick mode: Existence-level comparison only (type + name matching). Deep mode: Also compares all tracked properties from azure-property-paths.json with severity classification (Critical/Warning/Info) and normalization rules.
  • When the diagram is updated (Step 8 or selective Step 10), Bicep files are automatically regenerated if they already exist in the diagram's directory.
  • Destructive operations always require explicit confirmation — both for deleting Azure resources and removing diagram elements.
  • Filter out infrastructure resources per .github/skills/shared/procedures/resource-filtering.md.
  • Generated update Bicep includes deployment instructions using az deployment group create or New-AzResourceGroupDeployment.

© Azure, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/azv-diagram-azure-sync of Azure/AZVerify.

Open the folder on GitHubat commit d6a2b92

Compare with similar skills

Azv Diagram Azure Sync next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Azure Well Architected Reviewgithub/awesome-copilot40k—~2.5kAutomated safety check: PassMIT
Drawio Azuresparklabx/drawio-ai-kit655—~1.6kAutomated safety check: PassMIT
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Questions about Azv Diagram Azure Sync

What does Azv Diagram Azure Sync do?

Compare a Draw.io Azure architecture diagram against a live Azure environment to detect drift. Azv Diagram Azure Sync is an agent skill from Azure/AZVerify, published by the product's own GitHub organization.io Azure architecture diagram against a live Azure environment to detect drift.

When should I use Azv Diagram Azure Sync?

Azv Diagram Azure Sync fits situations like: tasks that involve Diagrams; tasks that involve Cloud architecture.

How do I install Azv Diagram Azure Sync in Claude Code?

Run `npx skills add Azure/AZVerify --skill azv-diagram-azure-sync -a claude-code`. Or copy the skill folder (.github/skills/azv-diagram-azure-sync in Azure/AZVerify) into .claude/skills/azv-diagram-azure-sync in your project. Claude Code loads it when a task matches its description.

How do I install Azv Diagram Azure Sync in Codex?

Run `npx skills add Azure/AZVerify --skill azv-diagram-azure-sync -a codex`. Or copy the skill folder (.github/skills/azv-diagram-azure-sync in Azure/AZVerify) into .agents/skills/azv-diagram-azure-sync in your project. Codex loads it when a task matches its description.

Can I use Azv Diagram Azure Sync in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Azure/AZVerify --skill azv-diagram-azure-sync -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azv-diagram-azure-sync, .gemini/skills/azv-diagram-azure-sync, .github/skills/azv-diagram-azure-sync and .opencode/skills/azv-diagram-azure-sync in your project.

What does Azv Diagram Azure Sync need to run?

Going by SKILL.md and its folder, Azv Diagram Azure Sync needs the command-line tools its instructions call (az).

Does Azv Diagram Azure Sync access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Azv Diagram Azure Sync safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azv Diagram Azure Sync use?

Azv Diagram Azure Sync is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azv Diagram Azure Sync use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azv Diagram Azure Sync?

Skills that share tags, products or a category with Azv Diagram Azure Sync: Azure Draw.io MCP Diagrams (thomast1906/github-copilot-agent-skills, 202 stars), Azure Well Architected Review (github/awesome-copilot, 40k stars), Drawio Azure (sparklabx/drawio-ai-kit, 655 stars) and Drawio MCP Diagramming (thomast1906/github-copilot-agent-skills, 202 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azv Diagram Azure Sync?

Azure (a GitHub organization, an official publisher) maintains it in Azure/AZVerify, which has 101 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on August 27, 2026.

Source: Azure/AZVerify on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.