Agent skill

image-generation

Create diagrams, charts, and visual assets for security documentation. Generate network diagrams, architecture visuals, and data visualizations. Use when creating visual content for reports or presentations.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/image-generation-sherifeldeeb-agentskills

Metadata

Additional technical details for this skill

author
SherifEldeeb
version
1.0.0
category
baseline

SKILL.md

Image Generation Skill

Create diagrams, charts, and visual assets for security documentation with support for network diagrams, data visualizations, and flowcharts.

Capabilities

  • Diagrams: Generate network topology and architecture diagrams
  • Charts: Create data visualizations (bar, pie, line, heatmaps)
  • Flowcharts: Build process and workflow diagrams
  • Risk Matrices: Generate risk assessment visualizations
  • Timelines: Create incident and event timelines
  • Export: Save to PNG, SVG, and PDF formats

Quick Start

python
import matplotlib.pyplot as plt

# Create a simple bar chart
severities = ['Critical', 'High', 'Medium', 'Low']
counts = [3, 8, 15, 22]

plt.figure(figsize=(10, 6))
plt.bar(severities, counts, color=['#e74c3c', '#e67e22', '#f1c40f', '#3498db'])
plt.title('Findings by Severity')
plt.savefig('severity_chart.png', dpi=150)

Usage

Bar Charts

Create bar charts for comparisons.

Example:

python
import matplotlib.pyplot as plt
from typing import Dict

def create_severity_chart(data: Dict[str, int], output_path: str = 'chart.png'):
    """Create a severity distribution bar chart."""
    colors = {
        'Critical': '#e74c3c', 'High': '#e67e22',
        'Medium': '#f1c40f', 'Low': '#3498db'
    }

    severities = list(data.keys())
    counts = list(data.values())
    bar_colors = [colors.get(s, '#333') for s in severities]

    plt.figure(figsize=(10, 6))
    plt.bar(severities, counts, color=bar_colors)
    plt.title('Findings by Severity', fontsize=14, fontweight='bold')
    plt.savefig(output_path, dpi=150, bbox_inches='tight')
    plt.close()

# Usage
create_severity_chart({'Critical': 3, 'High': 8, 'Medium': 15, 'Low': 22})

Network Diagrams

Create network topology diagrams using Graphviz.

Example:

python
from graphviz import Digraph

def create_network_diagram(nodes: list, edges: list, output_path: str = 'network'):
    """Create a network topology diagram."""
    dot = Digraph()
    dot.attr(rankdir='TB')

    shapes = {'firewall': 'box3d', 'server': 'box', 'database': 'cylinder'}

    for node in nodes:
        dot.node(node['id'], node['label'],
                shape=shapes.get(node.get('type', 'server'), 'box'),
                style='filled', fillcolor=node.get('color', 'lightblue'))

    for edge in edges:
        dot.edge(edge['from'], edge['to'], label=edge.get('label', ''))

    dot.render(output_path, format='png', cleanup=True)

# Usage
nodes = [
    {'id': 'fw', 'label': 'Firewall', 'type': 'firewall', 'color': 'lightcoral'},
    {'id': 'web', 'label': 'Web Server', 'type': 'server'},
    {'id': 'db', 'label': 'Database', 'type': 'database'}
]
edges = [{'from': 'fw', 'to': 'web'}, {'from': 'web', 'to': 'db'}]
create_network_diagram(nodes, edges)

Flowcharts

Create process flowcharts.

Example:

python
from graphviz import Digraph

def create_flowchart(steps: list, output_path: str = 'flowchart'):
    """Create a process flowchart."""
    dot = Digraph()
    dot.attr(rankdir='TB')

    shapes = {'start': 'ellipse', 'end': 'ellipse',
              'process': 'box', 'decision': 'diamond'}
    colors = {'start': 'lightgreen', 'end': 'lightcoral',
              'process': 'lightblue', 'decision': 'lightyellow'}

    for step in steps:
        dot.node(step['id'], step['label'],
                shape=shapes.get(step.get('type', 'process'), 'box'),
                style='filled',
                fillcolor=colors.get(step.get('type', 'process'), 'white'))

        if 'next' in step:
            for n in (step['next'] if isinstance(step['next'], list) else [step['next']]):
                if isinstance(n, dict):
                    dot.edge(step['id'], n['to'], label=n.get('label', ''))
                else:
                    dot.edge(step['id'], n)

    dot.render(output_path, format='png', cleanup=True)

Risk Heatmaps

Create risk assessment heatmaps.

Example:

python
import matplotlib.pyplot as plt
import numpy as np

def create_risk_heatmap(data: list, x_labels: list, y_labels: list, output_path: str):
    """Create a risk assessment heatmap."""
    fig, ax = plt.subplots(figsize=(10, 8))
    im = ax.imshow(data, cmap='RdYlGn_r')

    ax.set_xticks(np.arange(len(x_labels)))
    ax.set_yticks(np.arange(len(y_labels)))
    ax.set_xticklabels(x_labels)
    ax.set_yticklabels(y_labels)

    for i in range(len(y_labels)):
        for j in range(len(x_labels)):
            ax.text(j, i, data[i][j], ha='center', va='center',
                   color='white' if data[i][j] > 5 else 'black')

    ax.set_title('Risk Matrix')
    plt.colorbar(im)
    plt.savefig(output_path, dpi=150)
    plt.close()

Configuration

Environment Variables

Variable Description Required Default
IMAGE_OUTPUT_DIR Output directory No ./output
IMAGE_DPI Default DPI No 150

Limitations

  • Interactive: Static images only
  • 3D: Limited 3D support
  • Graphviz: Required for diagrams

Troubleshooting

Graphviz Not Found

Install the system package:

bash
apt-get install graphviz  # Ubuntu
brew install graphviz      # macOS

Related Skills

  • pptx: Embed images in presentations
  • docx: Include visuals in reports
  • pdf: Add charts to PDF reports

References

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