Data visualization skill for AI coding agents based on Edward Tufte's principles from The Visual Display of Quantitative Information, Envisioning Information, Visual Explanations, and Beautiful Evidence.
npx skills add pjsny/tufte-vizGives your AI agent deep knowledge of Tufte's data visualization principles so it can:
- Design new visualizations with maximum data-ink ratio and zero chartjunk
- Critique existing charts, dashboards, and reports for graphical integrity
- Write code with library-specific Tufte configs for Recharts, Chart.js, matplotlib, Plotly, ECharts, and D3/SVG
- Detect anti-patterns like pie charts, dual y-axes, legends, rainbow palettes, and heavy gridlines
- Apply the Lie Factor, small multiples, sparklines, layering, and micro/macro design
| Source | Topics |
|---|---|
| Visual Display of Quantitative Information | Data-ink ratio, chartjunk, graphical integrity, lie factor, small multiples, data density |
| Envisioning Information | Layering & separation, micro/macro design, escaping flatland, 1+1=3 effect |
| Visual Explanations | Cause & effect, confections, parallelism, narrative graphics |
| Beautiful Evidence | Six principles of analytical design, sparklines, range-frames, dot-dash plots |
| File | What it covers |
|---|---|
| Implementation guide | 22 universal rules, color/typography reference, chart type guidance, validation checklist |
| Anti-patterns | Detection table with per-library fix patterns |
| Recharts rules | React component configs, custom tooltip, small multiples layout |
| Chart.js rules | Defaults registration, datalabels plugin, dark mode |
| matplotlib rules | Spine removal, rcParams, seaborn override |
| Plotly rules | Layout template, Plotly Express shorthand |
| ECharts rules | Theme registration, endLabel direct labeling |
| D3/SVG rules | CSS defaults, inline sparkline generator, accessibility |
MIT