Claude Dataviz Skills: The Best Skills for Charts and Data Visualization

Claude can already draw a chart if you ask. What a dataviz skill adds is judgment and consistency: choosing the chart that fits the question, labeling it properly, using a palette people can read, and producing the same quality every time. The right skill depends on where the chart is going.

Choosing the Chart: Chart & Data Visualization Designer

Most bad charts are the wrong chart. The Chart & Data Visualization Designer starts by recommending a chart type and explaining why, then generates the ECharts or Chart.js configuration and a readable color scheme. Use it when you know the question but not the best way to show the answer.

For Reports and Papers: Data Visualization Creator

The Data Visualization Creator (adapted from Anthropic's knowledge-work plugins) produces publication-quality figures in matplotlib, plotly, or Chart.js: colorblind-friendly palettes, proper labels and annotations, and the code to regenerate the figure when the data changes. It's the one to use for anything going into a report, paper, or slide deck.

From a CSV: CSV Data Visualizer

Point the CSV Data Visualizer at a file and it builds histograms, trend lines, scatter plots, and heatmaps in Plotly, exported as interactive HTML or PNG. It's the fastest way to see what's in a dataset before deciding what to present.

Dashboards You Can Email: Interactive Dashboard Builder

The Interactive Dashboard Builder creates a single self-contained HTML file with Chart.js charts, dropdown filters, and sortable tables. No server or BI license needed: it opens in any browser and can go out as an email attachment. For exploratory analysis with hover, zoom, and linked subplots, Scientific Plotly goes further.

Infographics: Infographic Layout Designer

The Infographic Layout Designer plans the infographic rather than drawing it: visual hierarchy, section flow, a chart type for each data point, icons, and a palette, written as a spec you (or a designer) can build in Figma or Canva.

What Makes a Chart Good, Whichever Skill You Use

• Say the point in the title. "Product A drove all growth in 2026" beats "Revenue by product".
• Tell Claude the one comparison that matters. The chart choice follows from it.
• Check the numbers against the source. Spot-check a few values in the chart against the data before sharing.
• Keep the code. A regenerable chart beats a screenshot when the data updates.

For the analysis that comes before the chart, see Claude Skills for Data Analysts.

Get the Dataviz Skills