| name | dataviz |
| description | Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator. |
| when_to_use | When creating or revising charts, graphs, dashboards, maps, plots, inline SVG, D3, Plotly, Recharts, matplotlib, or any Artifact page that visualizes data. |
| allowedTools | ["read_file"] |
Dataviz
Use this skill before producing a chart, dashboard, map, or data visualization.
Workflow
- Identify the analytic task: comparison, trend, distribution, relationship,
ranking, part-to-whole, geography, or status monitoring.
- Choose the simplest chart form that answers that task. Read
references/choosing-a-form.md when the form is not obvious.
- Write the finding into the title, subtitle, axis label, or direct annotation.
A viewer should know what changed, what is high or low, or what decision the
chart supports.
- Pick colors from
references/palette.md, or validate any custom palette with
the script below.
- Check
references/anti-patterns.md before finalizing the design.
Palette Validation
Resolve paths relative to the skill base directory shown above this skill body.
Do not assume $QWEN_SKILL_ROOT is set for normal shell commands.
Run:
node <skill-base-directory>/scripts/validate_palette.js '#1d4ed8,#b45309,#166534' --mode light
Treat FAIL as a required palette change. Treat WARN as acceptable only when
the chart also uses labels, shape, texture, ordering, or another secondary
encoding.
Mark Rules
- Use categorical palettes for unordered groups; use sequential or diverging
ramps only for ordered values.
- Prefer direct labels over legends when the chart has a small number of series.
- Keep gridlines subtle and fewer than the data marks.
- Avoid dual axes unless both series share a clearly explained transformation.
- Do not rely on color alone for critical distinctions.
- Keep dashboards scan-friendly: align cards, use consistent number formats,
and reserve saturated color for important state changes.
