data-viz-best-practiceslisted

# Data Visualization Best Practices A format-agnostic skill for reviewing or building charts, infographics, and dashboards. Works the same whether the input is code, a design file, a screenshot, or a plain description — the principles don't change with the tool. ## Step 0: Which mode? Figure this out from context before doing anything else. If it's not obvious, ask. - **Review mode** — user has an existing chart/dashboard (image, code, file, or description) and wants feedback - **Build mode** — user wants a new chart/dashboard created or wants help picking the right chart type ## The Core Checklist (applies in both modes) Run every visualization against these seven checks. Reference files have the depth; this is the fast pass. 1. **Chart type fits the question.** Does the chart type match what the data is actually trying to answer (comparison, trend, part-to-whole, distribution, relationship)? See `references/chart-type-guide.md` for the decision tree. 2. **Data-ink ratio.** Every visual element should carry information. Flag: 3D effects, heavy gridlines, redundant legends, decorative gradients, unnecessary borders. 3. **Accessibility (WCAG AA).** Non-negotiable, not a nice-to-have. See `references/accessibility-checklist.md` for full detail: - Text contrast ≥ 4.5:1, large text/graphical objects ≥ 3:1 - Never encode meaning in color alone — pair with pattern, shape, position, or direct labels - Colorblind-safe palette (check for red-green and blue-yellow confu