---
name: tufte-viz
description: Applies Tufte principles to chart design and critique. Use for graphical integrity, chartjunk reduction, or high-density comparison layouts.
---

# Tufte Visualization Ideation

Apply Edward Tufte's principles to design clear, honest, high-density data visualizations.

## Workflow

### For new visualizations:

1. **Clarify the data story**
   - What comparisons matter?
   - What's the key insight to communicate?
   - Who's the audience?

2. **Select approach** using Tufte principles:
   - High comparison need → Small multiples
   - Dense data → Consider data tables, sparklines
   - Time-series → Line charts with minimal grid
   - Part-to-whole → Avoid pie charts; prefer bar/table

3. **Design with data-ink in mind**
   - Start minimal, add only what's necessary
   - Every element must earn its ink
   - Default to grayscale; use color purposefully

4. **Apply the Tufte test** (see references/tufte-principles.md)

### For critiquing visualizations:

1. **Check graphical integrity**
   - Calculate lie factor if proportions seem off
   - Verify baselines and scales
   - Look for 3D distortion

2. **Identify chartjunk**
   - Decorative elements
   - Heavy grids
   - Unnecessary 3D effects
   - Moiré patterns

3. **Evaluate data-ink ratio**
   - What can be erased?
   - What's redundant?

4. **Suggest improvements** with specific before/after recommendations

## Key Principles Reference

- `references/tufte-principles.md` — core principles from _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 6 principles of analytical design, sparklines, layering & separation, micro/macro, range-frames, causality, confections. Load when designing dashboards, dense displays, sparklines, or explanatory graphics.

**Quick checklist:**

- [ ] Lie Factor ≈ 1.0 (no visual distortion)
- [ ] Maximum data-ink ratio
- [ ] Zero chartjunk
- [ ] Clear labeling
- [ ] Answers "compared to what?"
- [ ] Shows causality or mechanism where relevant
- [ ] Multivariate (not over-reduced)
- [ ] Words, numbers, images integrated — not segregated
- [ ] Reveals multiple levels of detail (micro + macro)
- [ ] Layering: primary data dominates, secondary recedes
- [ ] Appropriate data density


---
Source attribution: edmundmiller
Original project: https://github.com/edmundmiller/dotfiles/blob/a60ca3c122ffc91fdb3d63db156b1e30851c9872/skills/catalog/tufte-viz/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

The MIT License (MIT)

Copyright (c) 2020 Edmund Miller

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:

The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.



# Dave AI resource metadata

Creator / publisher: edmundmiller
Original project: https://github.com/edmundmiller/dotfiles/blob/a60ca3c122ffc91fdb3d63db156b1e30851c9872/skills/catalog/tufte-viz/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Design, Product Management
Roles: Data Analyst, Graphic Designer, Market Research Analyst, Product Manager, UX Designer
Specialties: Cross Platform
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 17146edd4797f0d75b6b8b8efc85ccb4fab6cbc516770983bf800e83e4339970