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by cmb211087cmb211087/azure-diagrams-skill149 stars
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Comprehensive technical diagramming toolkit for solutions architects, presales, and developers. Creates Azure architecture diagrams (800+ Azure service icons), business process flows (swimlanes, workflows), ERD diagrams (database schemas), project timelines, UI wireframes, and network topology diagrams. Perfect for proposals, documentation, and architecture reviews. Also generates diagrams from Bicep, Terraform, and ARM templates.

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referencesbusiness-process-flows.md

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Business Process Flow Diagrams

Generate professional business process flow diagrams showing user actions, system steps, and outcomes.

Approach: Graphviz with Custom Styling (Recommended)

For business process flows, we use Graphviz directly for more control over shapes and styling.

Basic Setup

from graphviz import Digraph

def create_process_flow(title: str, filename: str):
    dot = Digraph(title, filename=filename, format='png')
    dot.attr(rankdir='TB', bgcolor='white', pad='0.5', nodesep='0.5', ranksep='0.7')
    dot.attr('node', fontname='Segoe UI, Arial', fontsize='11')
    dot.attr('edge', fontname='Segoe UI, Arial', fontsize='9')
    return dot

# Node style presets
STYLES = {
    'start_end': {'shape': 'ellipse', 'style': 'filled', 'fillcolor': '#E8F5E9', 'color': '#4CAF50'},
    'process': {'shape': 'box', 'style': 'filled,rounded', 'fillcolor': '#E3F2FD', 'color': '#2196F3'},
    'decision': {'shape': 'diamond', 'style': 'filled', 'fillcolor': '#FFF8E1', 'color': '#FFC107'},
    'user_action': {'shape': 'box', 'style': 'filled', 'fillcolor': '#F3E5F5', 'color': '#9C27B0'},
    'system': {'shape': 'box', 'style': 'filled', 'fillcolor': '#E0F7FA', 'color': '#00BCD4'},
    'document': {'shape': 'note', 'style': 'filled', 'fillcolor': '#FFFDE7', 'color': '#FFEB3B'},
    'data': {'shape': 'cylinder', 'style': 'filled', 'fillcolor': '#FBE9E7', 'color': '#FF5722'},
}

Example: Scanning & Indexing Process

dot = create_process_flow('Scanning and Indexing Process', 'scanning-process')

# Add nodes
dot.node('start', 'Start', **STYLES['start_end'])
dot.node('scan', 'User Scans\nDocument', **STYLES['user_action'])
dot.node('upload', 'System Uploads\nto Storage', **STYLES['system'])
dot.node('ocr', 'OCR Processing', **STYLES['system'])
dot.node('valid', 'Valid\nDocument?', **STYLES['decision'])
dot.node('index', 'Index in\nDatabase', **STYLES['system'])
dot.node('reject', 'Flag for\nReview', **STYLES['process'])
dot.node('notify', 'Notify User', **STYLES['system'])
dot.node('end', 'End', **STYLES['start_end'])

# Add edges
dot.edge('start', 'scan')
dot.edge('scan', 'upload')
dot.edge('upload', 'ocr')
dot.edge('ocr', 'valid')
dot.edge('valid', 'index', label='Yes')
dot.edge('valid', 'reject', label='No')
dot.edge('index', 'notify')
dot.edge('reject', 'notify')
dot.edge('notify', 'end')

dot.render(cleanup=True)

Swimlane Process Flow (Multiple Actors)

from graphviz import Digraph

dot = Digraph('Email Processing Flow', format='png')
dot.attr(rankdir='TB', compound='true', bgcolor='white')
dot.attr('node', fontname='Segoe UI', fontsize='10')

# Create swimlanes using subgraphs
with dot.subgraph(name='cluster_user') as user:
    user.attr(label='User', style='filled', fillcolor='#F3E5F5', color='#9C27B0')
    user.node('u1', 'Receive Email', shape='box', style='rounded,filled', fillcolor='white')
    user.node('u2', 'Review Content', shape='box', style='rounded,filled', fillcolor='white')
    user.node('u3', 'Approve/Reject', shape='diamond', style='filled', fillcolor='white')

with dot.subgraph(name='cluster_system') as system:
    system.attr(label='Contoso Docs System', style='filled', fillcolor='#E3F2FD', color='#2196F3')
    system.node('s1', 'Parse Email', shape='box', style='rounded,filled', fillcolor='white')
    system.node('s2', 'Extract Attachments', shape='box', style='rounded,filled', fillcolor='white')
    system.node('s3', 'Store Document', shape='cylinder', style='filled', fillcolor='white')

# Connect across swimlanes
dot.edge('u1', 's1')
dot.edge('s1', 's2')
dot.edge('s2', 'u2')
dot.edge('u2', 'u3')
dot.edge('u3', 's3', label='Approve')

dot.render('email-processing-swimlane', cleanup=True)

Current vs Future State Comparison

from graphviz import Digraph

dot = Digraph('Process Comparison', format='png')
dot.attr(rankdir='TB', bgcolor='white')

# Current State
with dot.subgraph(name='cluster_current') as current:
    current.attr(label='Current State (Legacy)', style='filled', fillcolor='#FFEBEE', color='#F44336')
    current.node('c1', 'Manual Scan', shape='box', style='rounded,filled', fillcolor='white')
    current.node('c2', 'Save to File Share', shape='box', style='rounded,filled', fillcolor='white')
    current.node('c3', 'Manual Indexing', shape='box', style='rounded,filled', fillcolor='white')
    current.edge('c1', 'c2')
    current.edge('c2', 'c3')

# Future State
with dot.subgraph(name='cluster_future') as future:
    future.attr(label='Future State (Contoso Docs)', style='filled', fillcolor='#E8F5E9', color='#4CAF50')
    future.node('f1', 'Scan with Auto-Upload', shape='box', style='rounded,filled', fillcolor='white')
    future.node('f2', 'AI-Powered OCR', shape='box', style='rounded,filled', fillcolor='white')
    future.node('f3', 'Auto Classification', shape='box', style='rounded,filled', fillcolor='white')
    future.edge('f1', 'f2')
    future.edge('f2', 'f3')

dot.render('process-comparison', cleanup=True)

Style Guide

Element Shape Color Use For
Start/End ellipse Green (#4CAF50) Process boundaries
Process rounded box Blue (#2196F3) System/automated steps
Decision diamond Amber (#FFC107) Yes/No branching
User Action box Purple (#9C27B0) Manual user steps
System box Cyan (#00BCD4) Backend processing
Document note Yellow (#FFEB3B) Document/form
Data/Storage cylinder Orange (#FF5722) Database/storage

Alternative Approach 1: Using Python Diagrams Library

The diagrams library can create process flows using generic and programming nodes.

from diagrams import Diagram, Cluster, Edge
from diagrams.generic.blank import Blank
from diagrams.generic.compute import Rack
from diagrams.generic.storage import Storage
from diagrams.generic.database import SQL
from diagrams.onprem.client import Users, Client
from diagrams.onprem.compute import Server
from diagrams.programming.flowchart import (
    Action, Collate, Database, Decision, Delay, Display,
    Document, InputOutput, ManualInput, ManualLoop, Merge,
    MultipleDocuments, OffPageConnectorLeft, OffPageConnectorRight,
    Or, PredefinedProcess, Preparation, Sort, StartEnd,
    StoredData, SummingJunction
)

# Example: Document Processing Workflow
with Diagram("Document Processing Flow", show=False, filename="process-flow", direction="TB"):
    
    start = StartEnd("Start")
    
    with Cluster("User Actions"):
        user = Users("User")
        scan = ManualInput("Scan Document")
    
    with Cluster("System Processing"):
        validate = Decision("Valid\nFormat?")
        ocr = Action("OCR\nExtraction")
        classify = Action("Auto\nClassification")
        store = Database("Store in\nDocument DB")
    
    with Cluster("Outcomes"):
        success = Display("Document\nIndexed")
        error = Display("Error\nNotification")
    
    end = StartEnd("End")
    
    start >> user >> scan >> validate
    validate >> Edge(label="Yes") >> ocr >> classify >> store >> success >> end
    validate >> Edge(label="No") >> error >> end

Approach 2: Mermaid Flowcharts (Alternative)

For simpler flows, generate Mermaid syntax that can be rendered.

def generate_mermaid_flowchart(title, steps):
    """Generate Mermaid flowchart syntax."""
    mermaid = f"---\ntitle: {title}\n---\nflowchart TD\n"
    for step in steps:
        mermaid += f"    {step}\n"
    return mermaid

# Example usage
steps = [
    "A[Start] --> B{Document Received?}",
    "B -->|Yes| C[Validate Format]",
    "B -->|No| D[Wait for Input]",
    "C --> E{Valid?}",
    "E -->|Yes| F[Process Document]",
    "E -->|No| G[Return Error]",
    "F --> H[Store in Database]",
    "H --> I[Send Confirmation]",
    "I --> J[End]",
    "G --> J",
    "D --> B",
]

mermaid_code = generate_mermaid_flowchart("Document Processing", steps)

Approach 3: Graphviz Direct (Maximum Control)

import graphviz

def create_process_flow(title, filename):
    dot = graphviz.Digraph(title, filename=filename, format='png')
    dot.attr(rankdir='TB', splines='spline')
    dot.attr('node', shape='box', style='rounded,filled', fillcolor='lightblue')
    
    # Start/End nodes
    dot.node('start', 'Start', shape='ellipse', fillcolor='lightgreen')
    dot.node('end', 'End', shape='ellipse', fillcolor='lightcoral')
    
    # Decision nodes
    dot.node('decision1', 'Valid?', shape='diamond', fillcolor='lightyellow')
    
    # Process nodes
    dot.node('step1', 'Receive\nDocument')
    dot.node('step2', 'Validate\nFormat')
    dot.node('step3', 'Process')
    dot.node('step4', 'Store')
    dot.node('error', 'Handle\nError', fillcolor='lightcoral')
    
    # Edges
    dot.edge('start', 'step1')
    dot.edge('step1', 'step2')
    dot.edge('step2', 'decision1')
    dot.edge('decision1', 'step3', label='Yes')
    dot.edge('decision1', 'error', label='No')
    dot.edge('step3', 'step4')
    dot.edge('step4', 'end')
    dot.edge('error', 'end')
    
    dot.render(cleanup=True)
    return f"{filename}.png"

# Usage
create_process_flow("Document Flow", "document-flow")

Common Process Flow Patterns

Pattern 1: Linear Process

start >> step1 >> step2 >> step3 >> end

Pattern 2: Decision Branch

step >> decision
decision >> Edge(label="Yes") >> path_a >> end
decision >> Edge(label="No") >> path_b >> end

Pattern 3: Parallel Processing

step >> [parallel_a, parallel_b, parallel_c] >> merge >> next_step

Pattern 4: Loop/Retry

process >> decision
decision >> Edge(label="Success") >> next
decision >> Edge(label="Retry") >> process

Pattern 5: Swimlanes (Actors)

with Cluster("Customer"):
    customer_actions = [Action("Submit"), Action("Review")]

with Cluster("System"):
    system_actions = [Action("Validate"), Action("Process")]

with Cluster("Admin"):
    admin_actions = [Action("Approve"), Action("Archive")]

Styling Guide

Node Shapes by Type

  • Start/End: Ellipse (rounded)
  • Process/Action: Rectangle with rounded corners
  • Decision: Diamond
  • Data/Document: Parallelogram or document shape
  • Manual Input: Trapezoid
  • Delay/Wait: Half-circle

Color Coding

# Suggested colors
USER_ACTION = "#E3F2FD"      # Light blue
SYSTEM_PROCESS = "#E8F5E9"   # Light green
DECISION = "#FFF3E0"         # Light orange
ERROR = "#FFEBEE"            # Light red
SUCCESS = "#E8F5E9"          # Light green
DATA = "#F3E5F5"             # Light purple

Converting ASCII Process Flows

When converting ASCII diagrams like:

┌─────────┐    ┌─────────┐    ┌─────────┐
│  User   │───►│ Submit  │───►│ Validate│
└─────────┘    └─────────┘    └────┬────┘
                                   │
                              ┌────▼────┐
                              │ Valid?  │
                              └────┬────┘
                         Yes │    │ No
                        ┌────▼──┐ │
                        │Process│ │
                        └───────┘ ▼
                              ┌───────┐
                              │ Error │
                              └───────┘

Map to:

  1. Identify actors/swimlanes (User, System)
  2. Identify decision points (diamonds in ASCII)
  3. Identify process steps (boxes)
  4. Trace flow direction (arrows)
  5. Note any parallel or branching paths

Source: SKILL.md on GitHub

Third-party checks

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    The Azure Diagrams Skill is a professional toolkit for generating technical architecture diagrams. It provides comprehensive reference guides and scripts to facilitate the creation of diagrams using the 'diagrams' Python library and Graphviz. Analysis shows the skill follows best practices for file handling, implements appropriate sanitization for its transformation tasks, and contains no malicious code or exfiltration patterns.

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    Risk: MEDIUM · No issues

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Provenance

Signed by skilld at ce0fc67. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 months ago.

Steadyupdated 3 months ago

Capability

Other metadata
compatibility
Requires the Graphviz system package and the Python diagrams library (>=0.25.1). Works with Claude Code, GitHub Copilot, Cursor, Windsurf, VS Code, and any Agent Skills or AGENTS.md compatible tool.
metadata
{
  "author": "community",
  "version": "2.0.0",
  "repository": "https://github.com/cmb211087/azure-diagrams-skill"
}

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