Designer — Chart / Infographic / Data Visualization Generator

Step 2: SUGGEST the Best Approach (ALWAYS DO THIS)

You MUST suggest before generating. Present your recommendation like this:

Suggested visualization:

• Chart type: [e.g., Grouped bar chart] — [why this fits the data]
• Output format: [e.g., PNG at 300 DPI] — [why this fits the medium]
• Color palette: [e.g., Government Blue] — [why this fits the context]
• Alternative options: [1-2 other chart types that could work]

Shall I proceed with this, or would you prefer a different approach?

Wait for user confirmation or adjustment before generating.

Exception: If the user explicitly specifies the chart type, format, and style, skip the suggestion and generate directly.

Step 3: Generate the Visualization

Use the appropriate Python library:

Step 4: Output and Iterate

• Save the file to the user's specified location or the current working directory
• Show the file path
• Ask if adjustments are needed (colors, labels, sizing, etc.)

Chart Type Selection Guide

Refer to references/chart-types.md for the full decision matrix. Quick reference:

Color Palettes

Refer to references/color-palettes.md for the full collection. Key rules:

• NEVER use purple (#800080, #9B59B6, #8E44AD, or any purple hue)
• Default to the palette that matches the document context
• Government/formal documents: Government Blue or Neutral Professional
• Cooperative reports: Cooperative Green or Earth Tones
• Financial data: Financial Trust or Corporate Steel
• Presentations: Vibrant Professional or Warm Confidence
• Always ensure sufficient contrast for readability
• Use colorblind-safe palettes when accessibility matters

Output Format Guide

Standard Chart Settings

Apply these defaults unless the user specifies otherwise:

# matplotlib defaults
import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.rcParams.update({
    'figure.dpi': 300,
    'savefig.dpi': 300,
    'savefig.bbox': 'tight',
    'savefig.pad_inches': 0.3,
    'font.family': 'sans-serif',
    'font.sans-serif': ['Inter', 'Helvetica Neue', 'Arial', 'sans-serif'],
    'font.size': 10,
    'axes.titlesize': 14,
    'axes.titleweight': 'bold',
    'axes.labelsize': 11,
    'xtick.labelsize': 9,
    'ytick.labelsize': 9,
    'legend.fontsize': 9,
    'figure.figsize': (10, 6),
    'axes.spines.top': False,
    'axes.spines.right': False,
    'axes.grid': True,
    'grid.alpha': 0.3,
    'grid.linestyle': '--',
})

# plotly defaults
import plotly.io as pio
import plotly.graph_objects as go

pio.templates.default = "plotly_white"
PLOTLY_LAYOUT_DEFAULTS = dict(
    font=dict(family="Inter, Helvetica Neue, Arial, sans-serif", size=12),
    title_font_size=16,
    margin=dict(l=60, r=40, t=60, b=60),
    plot_bgcolor="white",
    width=1000,
    height=600,
)

Diagram Generation (Graphviz)

For org charts, flowcharts, and process diagrams:

import graphviz

# Default graph attributes
GRAPH_DEFAULTS = {
    'fontname': 'Helvetica Neue',
    'fontsize': '11',
    'bgcolor': 'white',
    'rankdir': 'TB',  # Top to bottom; use 'LR' for left-to-right
}

NODE_DEFAULTS = {
    'fontname': 'Helvetica Neue',
    'fontsize': '10',
    'style': 'filled',
    'shape': 'box',
    'fillcolor': '#E8F4FD',
    'color': '#2C3E50',
    'penwidth': '1.5',
}

EDGE_DEFAULTS = {
    'fontname': 'Helvetica Neue',
    'fontsize': '9',
    'color': '#7F8C8D',
    'arrowsize': '0.8',
}

Output graphviz diagrams as PNG (default) or SVG. Use format='png' with graph.render().

File Naming Convention

Name output files descriptively:

• chart_cooperative_member_growth_2024.png
• diagram_csea_process_flow.svg
• infographic_barmm_budget_allocation.png
• chart_financial_ratios_comparison.png

Data Reading Patterns

import pandas as pd

# Excel
df = pd.read_excel("path/to/file.xlsx", sheet_name="Sheet1")

# CSV
df = pd.read_csv("path/to/file.csv")

# Inline data
data = {
    'Category': ['A', 'B', 'C'],
    'Value': [100, 200, 150],
}
df = pd.DataFrame(data)

Accessibility and Quality Checklist

Before delivering any visualization, verify:

• Title is clear and descriptive
• Axes are labeled with units where applicable
• Legend is present if multiple series
• Font sizes are readable at target display size
• Colors have sufficient contrast
• No purple colors used anywhere
• Data source annotation if applicable
• File saved at appropriate DPI for target medium
• Background color matches target document (usually white)

Error Handling

• If a font is not available, fall back to system sans-serif
• If data has issues (nulls, wrong types), report to user before proceeding
• If graphviz is not in PATH, install via brew install graphviz or guide user
• If kaleido fails for plotly export, fall back to writing HTML then screenshotting

Integration with Other Skills

• /docx — Generate PNG charts, pass file path to docx skill for embedding
• /pdf — Generate PNG/SVG charts, embed in PDF layout
• /pptx — Generate PNG charts at presentation dimensions (13.33 x 7.5 inches)
• /xlsx — Generate charts using openpyxl's chart module or as image overlays