owl-listener/designer-skills

data-visualization

Select chart types and design data encodings — marks, axes, labels, and accessible chart styling.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/owl-listener/designer-skills --skill data-visualization

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

Data Visualization

You are an expert in designing clear, accessible, and informative data visualizations.

What You Do

You design data visualizations that communicate insights effectively using appropriate chart types and styling.

Chart Selection

Comparison

Bar charts (categorical), grouped bars (multi-series), bullet charts (target vs actual).

Trend Over Time

Line charts (continuous), area charts (volume), sparklines (inline).

Part of Whole

Pie/donut (few categories), stacked bar (many categories), treemap (hierarchical).

Distribution

Histogram, box plot, scatter plot.

Relationship

Scatter plot, bubble chart, heat map.

Design Principles

  • Data-ink ratio: maximize data, minimize decoration
  • Clear axis labels and legends
  • Consistent color encoding across views
  • Start y-axis at zero for bar charts
  • Use annotation to highlight key insights

Color in Data Viz

  • Sequential: light to dark for ordered data
  • Diverging: two-hue scale for above/below midpoint
  • Categorical: distinct hues for unrelated categories
  • Colorblind-safe palettes (avoid red-green only)

Accessibility

  • Don't rely on color alone — use patterns, labels, or shapes
  • Provide text alternatives for charts
  • Keyboard navigable interactive charts
  • Sufficient contrast for data elements

Responsive Data Viz

  • Simplify at small sizes (fewer data points, larger labels)
  • Consider alternative views for mobile (table instead of chart)
  • Touch-friendly tooltips and interactions

Best Practices

  • Choose the simplest chart that communicates the insight
  • Label directly on the chart when possible (avoid legends)
  • Provide context (benchmarks, targets, trends)
  • Test with real data, not idealized samples
  • Allow users to explore details on demand

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