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Expert system for selecting and designing optimal data visualizations based on data dimensionality, integrity, and communication goals.

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SKILL.md

name chart-architect
description Expert system for selecting and designing optimal data visualizations based on data dimensionality, integrity, and communication goals.

Chart Architect Skill

When the user requests to "visualize," "chart," or "graph" data, execute the following multi-step analytical framework.

1. Data Classification

Analyze the input data to identify its "Flavor":

  • Temporal: Contains dates, years, or timestamps.
  • Categorical: Strings, names, or discrete groups.
  • Geospatial: Countries, cities, or coordinates.
  • Numerical: Continuous values or measurements.
  • Hierarchical: Parent-child relationships (e.g., Department > Team).

2. Decision Logic Matrix

If Data Contains... And the Goal is... Recommended Visualization
Time + Value Show continuity/trends Line Chart
Time + Volatility Emphasize volume over time Area Chart
Categories + Value Comparison of magnitudes Bar Chart (Horizontal)
Categories (Ordinal) Comparison (e.g., Low to High) Column Chart (Vertical)
Part-to-Whole (<6 categories) Simple proportions Pie/Donut Chart
Part-to-Whole (>6 categories) Complex proportions Treemap or Stacked Bar
2 Numerical Variables Find correlations/outliers Scatter Plot
3 Numerical Variables Correlation + Magnitude Bubble Chart
Geospatial Data Regional patterns Choropleth Map
Process Stages Show leakage or conversion Funnel Chart

3. The "Golden Rules" of Visualization

  1. The Zero-Baseline: For Bar and Column charts, the Y-axis (or X-axis for horizontal) must start at 0. Never truncate the axis.
  2. Sorting Logic: - Always sort Bar Charts by value (descending) unless there is a natural order (e.g., Age groups, Months).
  3. The "Spaghetti" Limit: - If a Line Chart has >5 categories, suggest Small Multiples (multiple small charts) instead of one crowded chart.
  4. Color Accessibility: - Use high-contrast palettes. Mention color-blind friendly options (e.g., Viridis or Colorbrewer) if the user asks for styling.
  5. Simplicity First: - Remove "chart junk" (heavy gridlines, 3D effects, or redundant labels).

4. Implementation Protocol

When a request is made, respond in this structure:

  1. The Recommendation: State the chart type clearly.
  2. The "Why": Explain based on the Data Classification (e.g., "Since you have 12 categories, a Treemap is better than a Pie Chart to maintain readability.")
  3. Design Specs: Provide specific instructions:
    • "X-Axis: [Field Name]"
    • "Y-Axis: [Field Name]"
    • "Sorting: [Ascending/Descending/None]"
  4. Alternative View: Suggest one other way to look at the same data if applicable.