image-generation
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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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Sourcesherifeldeeb/agentskills
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npx skill4agent add sherifeldeeb/agentskills image-generationTags
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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 |
|---|---|---|---|
| Output directory | No | |
| Default DPI | No | |
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 # macOSRelated Skills
- pptx: Embed images in presentations
- docx: Include visuals in reports
- pdf: Add charts to PDF reports
References
- Detailed API Reference
- Matplotlib Documentation
- Graphviz Documentation