Chart Tufte

---
name: chart-tufte
description: "Post-build grader for a rendered quantitative chart, grounded in Edward Tufte's The Visual Display of Quantitative Information: strips chartjunk, checks the lie factor, picks the right genre, and names failures from the VDQI catalogue. Not a chart builder. Runs as the last step of /visual-explainer when the page has a chart, or on demand (\"grade this chart\", \"is this chart honest\")."
---

# Chart Tufte

A chart is good when it shows the data, helps the viewer reason about it, and does not lie. Tufte spent a career formalising this. This skill collapses his principles into a self-grade pass that runs on any chart the assistant is about to emit.

**Read [references/vdqi-catalogue.md](references/vdqi-catalogue.md) first** when grading. It holds the named-failures library (NYT MPG 14.8, TIME barrel 59.4, etc.) and the named-exemplars library (Minard, Marey, Playfair, Snow). The catalogue is what makes assessment diagnostic instead of generic.

## When to invoke

- **After building**: as the last step of `/visual-explainer` whenever the page holds a *quantitative* chart (bar, line, scatter, area, dot, range-frame); that skill's steps call for it. Skip for diagrams (architecture, sequence, flow); those are different beasts.
- **Explicitly**: `/chart-tufte <chart-spec>` to score a chart produced elsewhere.

## The rubric (run before emitting)

Score each on 0-10. Stop and revise if any score drops below 5.

1. **Data-ink ratio**: does every pixel of ink represent data? Borders, gridlines, redundant legends are non-data ink. Target: tend toward 1.0; typical for default-styled charts is 0.1-0.2 (VDQI p.136).
2. **Lie factor**: `(visual change %) / (data change %)`. Acceptable range 0.95-1.05. Cite a VDQI named failure if it is worse: TIME's barrel chart hit 59.4, NYT's MPG hit 14.8.
3. **Data density**: numbers per square inch. Below 0.15 is overwrought (a single bar showing one number is the canonical sin). High-density alternatives: small multiples, range-frame scatters, tables.
4. **Chartjunk count**: does the chart contain any of the four named species?
   - **Moiré**: vibrating cross-hatch patterns.
   - **The dreaded grid**: gridlines drawn darker than the data.
   - **The duck**: visual gimmick that overwhelms the data (3D pies, gradient-shaded bars).
   - **Decoration**: clip art, icons, mascots in the chart frame.
   Each chartjunk species costs points.
5. **Genre fit**: is this the right *shape* for this data?
   - ≤20 numbers → table, not chart
   - Many series → small multiples (one panel per series)
   - 2 quantitative variables → range-frame scatter (axis only spans data min-max)
   - Distribution → quartile plot, not bar of mean
   - Time series → thin line + direct endpoint labels, no legend
6. **Dimensionality discipline**: does the chart use more dimensions than the data has? A 3D pie chart on 1D data is dishonest by construction. Penalise.
7. **Direct labelling**: are series labelled at their endpoint or inline, not via a separate legend? Legends force the reader's eye to bounce.
8. **Range-frame discipline**: does the axis span only the data range, not 0 to some arbitrary max?
9. **Comparability**: if multiple panels: same y-scale where comparison matters; different scales only when local shape is the question.

## Remedies (when the rubric flags problems)

- **B1: fix lie factor**: redraw with proportional scaling. State the new lie factor in the chart caption.
- **B2: erase non-data ink**: remove borders, drop gridlines, kill the legend if direct labelling fits.
- **B3: increase data density**: switch to small multiples if you have ≥3 panels of comparable data.
- **B4: pick the right genre** (see C1-C10 below).
- **B5: name the failure**: if the chart resembles a VDQI named failure (NYT MPG 14.8, TIME barrel 59.4, LA Times shrinking-doctor 2.8, USA Today 3D bar chart, Playfair's wheat decline), say so before showing.
- **B6: fix dimensionality**: 1D data → 1D chart; never 3D unless the third dimension is *in* the data.
- **B7: deflate currency over time**: if plotting dollars across years, deflate to a common year (state which) before plotting. Failing to do this is a silent lie factor.

## Genre playbook (C1-C10)

- **C1: quartile plot** for distributions (5-number summary, no whiskers gimmick).
- **C2: range-frame scatter** for two quantitative variables (axes span data range only).
- **C3: dot-dash marginals** on a range frame to show density on each axis.
- **C4: paired bars** for two-group comparison on one categorical axis.
- **C5: small multiples** for many series (1 panel per series, same x-axis, often same y-axis).
- **C6: sparkline** for inline time series at word-scale.
- **C7: slopegraph** for before/after comparison across many categories.
- **C8: stem-and-leaf table** when the goal is the actual numbers, not the shape.
- **C9: table** when ≤20 numbers and structure matters.
- **C10: thin line chart** for time series, direct endpoint label, no legend, no gridlines.

## Exemplars to emulate

- Minard's *Napoleon's March* (1869): six variables, one image, time + space + temperature + casualties.
- Playfair's wheat-vs-wages (1822): currency deflated, dual y-axis used honestly.
- Modern NYT inflation charts: direct labels, no gridlines, deflated currency.
- Tufte's own sparkline-in-prose pattern: chart as part of the sentence.

## Output

A six-line block:

```
Tufte self-grade
  Data-ink ratio: 7/10
  Lie factor: 1.02 (acceptable; not in catalogue)
  Chartjunk: 0 species
  Genre fit: C10 (thin line), correct for the data
  Verdict: ship
  Notes: (any remedies applied during pass)
```

If the verdict is not `ship`, revise the chart and re-grade before emitting.

## Integration with `visual-explainer`

`/visual-explainer` calls this skill after it builds the page (its "Grade any chart" step). Two things to do there:

1. **Check the genre**: name the Tufte genre (C1-C10) the chart should be, and whether the built chart matches it. The visual palette is a separate choice; never let styling pick the genre.
2. **Grade the rendered chart**: run this rubric over the rendered HTML/SVG before the page is saved. If any score is below 5, revise. Do not save on `verdict != ship`.

## VDQI page references (for citations)

- Data-ink ratio definition + targets: p.93, 136
- Lie factor formula + named failures: pp.55-80
- Chartjunk taxonomy (moiré / grid / duck / decoration): pp.107-121
- Small multiples: pp.170-175
- Range frame: pp.130-133
- Sparklines (later book *Beautiful Evidence*, but cited in the canon)

Edward Tufte, *The Visual Display of Quantitative Information*, 2nd ed., Graphics Press, 2001.