Come usare
- Copia il comando e controlla il pacchetto prima di installarlo nel tuo ambiente agente.
- Controlla strumenti, credenziali e ambienti richiesti nel documento originale.
- Descrivi input e risultato desiderato; confronta l’output con le fonti.
npx skills add https://github.com/owl-listener/designer-skills --skill data-visualizationPrima di iniziare
- L’installazione non include abbonamenti, quote API o accesso ai file.
- Stelle e installazioni indicano attività, non un test indipendente di qualità o sicurezza.
Documento Skill originale
Contenuto dal repository con titoli, esempi, codice, tabelle, link e immagini preservati.
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
