Tufte Visualization
Skill
Applies Edward Tufte's principles—high data-ink ratio, zero chartjunk, direct labeling, and small multiples—to charts and dashboards.
By Vedang Manerikar · skills/tufte-viz/SKILL.md · View source
What it does
Default charting library themes are full of visual clutter: heavy gridlines, redundant legends, 3D effects, and decorative chrome. Tufte Visualization gives the agent a concrete checklist and code recipes (across matplotlib, D3, ggplot2, and Vega-Lite) for stripping away non-data ink and letting the numbers speak.
It enforces six core principles: graphical integrity (Lie Factor near 1.0), maximizing the data-ink ratio, eliminating chartjunk, maximizing data density (sparklines and tables), layering micro and macro detail, and replacing cluttered multi-series charts with small multiples.
When to reach for it
Invocation: Loaded when building or critiquing charts, plots, or dashboards, or invoked via /skill:tufte-viz.
- Generating a chart or dashboard
- Apply clean range-frame axes, direct data labels, muted palettes, and assertion titles ('Revenue grew 23% in Q3') from the start.
- Critiquing an existing visualization
- Run the Tufte audit checklist to remove gridlines, legends, and distortion.
What it adds
- A structured visualization audit checklist, chart-type selection table, and ready-to-use matplotlib styling defaults.
Commands: /skill:tufte-viz
How it fits
- Sharpen Communication — Tufte Visualization strips visual clutter from charts; Sharpen Communication strips verbal clutter from the surrounding prose.
Good to know
- Includes explicit accessibility guardrails so minimalist styling never sacrifices contrast, colorblind safety, or screen-reader labels.
Source and setup
- Loaded via
skills/tufte-viz/SKILL.md- Attribution
- By Vedang Manerikar