| name | tufte-viz |
| description | Use when designing or critiquing charts, dashboards, reports, or other data visualizations; choosing between visualization approaches; reducing chartjunk; improving data-ink ratio; or planning small multiples and high-density displays. |
| metadata | {"short-description":"Tufte-style viz design and critique with personal house style"} |
Tufte Visualization Ideation
Apply Edward Tufte's principles to design clear, honest, high-density data visualizations, layered with the user's house style.
Load Preferences First
ALWAYS read preferences.md in this skill directory before producing or critiquing a chart. The user's preferences override generic Tufte defaults wherever they conflict, except on graphical integrity (lie factor, honest scales, etc.), which is non-negotiable.
Workflow
For new visualizations
-
Clarify the data story
- What comparisons matter?
- What is the key insight to communicate?
- Who is the audience?
-
Select an approach using Tufte principles plus the user's preferences:
- High comparison need -> small multiples
- Dense data -> data tables, sparklines
- Time series -> line charts with minimal grid
- Part-to-whole -> avoid pie charts; prefer bar or table
-
Design with data-ink in mind
- Start minimal, add only what is necessary
- Every element must earn its ink
- Default to grayscale; use color purposefully (subject to
preferences.md)
-
Apply the Tufte test (see references/tufte-principles.md)
For critiquing visualizations
-
Check graphical integrity
- Calculate lie factor if proportions seem off
- Verify baselines and scales
- Look for 3D distortion
-
Identify chartjunk
- Decorative elements
- Heavy grids
- Unnecessary 3D effects
- Moire patterns
-
Evaluate data-ink ratio
- What can be erased?
- What is redundant?
-
Suggest improvements with specific before/after recommendations, aligned with preferences.md.
References
preferences.md -- the user's house style. Load first; it overrides generic guidance where it conflicts (except integrity).references/tufte-principles.md -- core principles from The Visual Display of Quantitative Information: lie factor, data-ink, chartjunk, small multiples, integrity.references/analytical-design.md -- extensions from Envisioning Information, Visual Explanations, and Beautiful Evidence: the six principles of analytical design, sparklines, layering and separation, micro/macro, range-frames, causality, confections. Load when designing dashboards, dense displays, sparklines, or explanatory graphics.
Quick checklist
