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xxd-data-viz

Design
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Create chart and data visualization palettes from Chinese traditional colors. Use when a user needs categorical, sequential, diverging, highlight, dashboard, map, ECharts, D3, Chart.js, or colorblind-aware data palettes with Chinese traditional color identity.

QUICK START

How to use this skill

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  3. Review the proposed files and risks before you approve installation.
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Source SKILL.md: https://github.com/nevertoday/zhongguo-traditional-colors/blob/HEAD/skills/xxd-data-viz/SKILL.md

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xxd-data-viz

Purpose

Use this skill when colors must encode data. It should not turn a poster palette into a chart palette; it must choose colors by data meaning, distinguishability, ordering, and accessibility.

Pain Points This Solves

  • Attractive palettes fail charts because categories are not distinct or values are not ordered by lightness.
  • Designers mix categorical, sequential, and diverging color logic in one chart.
  • Chart color often relies on hue alone, which weakens accessibility and makes legends harder to read.

Data Contract

  • Use the bundled references inside this skill:
    • references/chinese-color-master-list.md: full 742-color Markdown source list.
    • references/chinese-color-harmony.csv: complete machine-readable harmony table for all 742 colors.
    • references/chinese-color-harmony.md: Markdown version of the same harmony relationships.
  • Do not treat all harmony colors as chart-ready; validate distinctness or ordering for the chart mode.
  • Do not rely on hue alone. Add label, order, pattern, stroke, marker shape, direct labeling, or interaction guidance when needed.

Chart Mode Workflow

  1. Identify data meaning before picking colors:
    • Categorical: unrelated groups.
    • Sequential: low to high values.
    • Diverging: two directions around a meaningful midpoint.
    • Highlight: one or two emphasized series against quiet context.
    • Dashboard semantic: success, warning, danger, info, selected, neutral.
  2. Choose selection criteria:
    • Categorical: maximize hue and lightness separation.
    • Sequential: monotonic lightness is more important than poetic harmony.
    • Diverging: balance perceived strength on both sides and reserve a neutral midpoint.
    • Highlight: keep background series quiet and the target unmistakable.
  3. Build the palette from project colors only.
  4. Add chart implementation details:
    • Background/grid/axis color.
    • Legend or direct labels.
    • Hover and selection color.
    • Missing data and disabled series.
  5. If requested, output ECharts, D3, Chart.js, or CSV arrays.

Output Shape

  • Data context: chart type, series count, background, data meaning.
  • Mode decision: categorical, sequential, diverging, highlight, or semantic.
  • Palette table: order or series, color name, HEX, role, reason.
  • Usage rules: legend, labels, grid, hover, selection, missing data.
  • Accessibility notes: where labels, markers, strokes, or patterns are required.
  • Optional code in the requested chart format.

For charts with more than 12 categories, recommend grouping, sorting, filtering, or interaction rather than forcing more colors.