dataviz

Data Visualization

A chart is read by people and executed by you. This skill turns "make it look good" into a procedure with checks, so the result is right by construction rather than by taste.

The method here is design-system-agnostic. Nothing in the procedure, the form heuristic, the six checks, or the mark specs is specific to one product. A design system supplies a small set of parameters (its ramps, a categorical order, a diverging pair, a status palette, a texture, its surfaces, its filter components); the method consumes them unchanged. A validated default palette is the reference instance, fully specified in references/palette.md. To target your brand, read that file's structure and substitute its values - touch nothing else.

The single most important habit: the color part is computable, so compute it. Never eyeball whether a palette is colorblind-safe - run scripts/validate_palette.js.

The procedure - do these in order

Color comes LAST. Most bad charts pick colors first.

1. Pick the form. What is the data's job - magnitude, identity, polarity, a single headline, change-over-time? The job picks the chart type, and sometimes the answer is not a chart (a stat tile or hero number). -> references/choosing-a-form.md
2. Assign color by the job it does. Categorical (identity), sequential (magnitude), diverging (polarity), or status (state) - each has one rule. Assign categorical hues in fixed order, never cycled. -> references/color-formula.md
3. VALIDATE the palette - run the script, don't reason about Delta E. node scripts/validate_palette.js "<hex,hex,...>" --mode light (relative to this skill's base directory - or load it as <script type="module"> in the chart's own page, where it reads data-palette off <body> and logs a console.table report). It returns pass/fail on the lightness band, chroma floor, adjacent-pair CVD separation, the normal-vision floor, and contrast. Fix anything that FAILs before continuing. Re-run for --mode dark with that mode's surface.
4. Apply mark specs & spacers. Thin marks, 4px rounded data-ends anchored to the baseline, 2px lines, >=8px markers, a 2px surface gap between fills (stacked segments and adjacent bars alike) and a 2px surface ring on overlapping marks, selective direct labels. -> references/marks-and-anatomy.md
5. Add the hover layer - by default. An HTML/SVG chart is interactive; ship a crosshair+tooltip on line/area and a per-mark hover tooltip on bar/dot/cell. The only form that skips it is a bare stat tile with no plot. Hit targets bigger than the mark; filters in one row above the charts. -> references/interaction.md
6. Final accessibility pass. For >= 2 series a legend is always present and <= 4 are also direct-labeled (a single series needs no legend box - the title names it), so identity is never color-alone; a table view exists; dark mode is selected - its own steps from the same ramps, validated against the dark surface, not an automatic flip; texture is available for the CVD/print/forced-colors case.
7. Render it and look at it. The validator checks color, not layout - open or screenshot the output and eyeball it for label collisions, geometry, and overflow before calling it done.