What problem does it solve? Choosing the wrong chart type, truncating axes, or relying on color alone makes quantitative evidence misleading or unreadable. This Skill guides the selection, design, and auditing of data visualizations so charts stay truthful, perceptually accurate, and tied to a specific audience decision. ## Core Features & Use Cases - Chart selection by analytical task: Maps tasks like ranking, change over time, distribution, composition, and uncertainty to appropriate forms such as sorted bars, line charts, histograms, and scatterplots. - Integrity and accessibility auditing: Runs an eight-step audit covering evidence integrity, perceptual accuracy, axis baselines, colorblind-safe palettes, alt text, and keyboard access. - Implementation guidance: Provides technology recommendations for web charts, from static HTML/SVG to SvelteKit with LayerChart or D3, with data validation and fallback tables. - Use Case: Ask it to audit an executive KPI dashboard, and it flags truncated bar baselines, unexplained dual axes, and missing uncertainty intervals, then recommends a redesigned bullet chart with direct labels. ## Quick Start Ask the assistant to recommend and design an accessible chart comparing quarterly revenue across regions, including axis, scale, and alt text choices.
