Data Visualization Executor Skill

When to Use

Primary triggers:

• "generate a chart", "create a visualization", "build this chart"
• "execute this dataviz plan", "generate from this viz spec"
• "make a bar chart of this data", "plot this CSV"
• User has a dataviz-planner spec and wants an HTML visualization generated
• User has a CSV/JSON file and wants a chart produced

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Use When

• You have a completed dataviz-planner spec and want a self-contained HTML chart generated
• You have a CSV or JSON data file and a clear chart request (simple cases)
• You need a Plotly.js visualization with accessibility features (colorblind-safe, alt text, responsive)
• You want a chart that opens directly in the browser — no server or build step needed
• You need to produce a chart that dataviz-critic can then review

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Do Not Use When

• You need to design a visualization — use dataviz-planner first
• You need to review an existing visualization — use dataviz-critic
• You need a dashboard with multiple charts and KPI hierarchy — use dashboard-planner first
• You need statistical analysis of the data — analyze first, then visualize
• You need a print-ready static image — this produces interactive HTML, not PNG/PDF

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Resolution Paths

Situation	Route
Have a dataviz-planner spec, need a chart	This skill — generates self-contained HTML
Need to design the visualization first	Use dataviz-planner, then come back
Have a chart, need quality review	Use dataviz-critic
Need multiple charts in a dashboard	Use dashboard-planner for architecture first
Have raw data, need quick exploratory chart	This skill — direct request mode (simple cases)

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What You Get

• Self-contained HTML file with Plotly.js CDN, inline data, responsive layout
• Accessibility features: colorblind-safe palette, alt text, ARIA labels, keyboard navigation
• Deviation log documenting any places the output differs from the planner spec
• Critic handoff command — ready to run /dataviz-critic on the output

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Input Modes

Mode 1: Planner Spec (Preferred)

Provide the output from dataviz-planner. The executor parses the structured plan (Question & Audience, Chart Type Selection, Design Specifications, Equity Review) and generates an HTML visualization matching the spec.

Mode 2: Direct Request (Simple Cases)

Provide a data file path (CSV/JSON) and describe the chart: "Create a bar chart of sales by region from sales.csv." The executor generates the chart using sensible defaults. For complex multi-variable visualizations or equity-sensitive data, redirects to dataviz-planner.

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Supported Chart Types

Chart Type	Use Case	Plotly.js Trace
Bar (vertical/horizontal)	Category comparison	bar
Grouped/Stacked bar	Multi-series comparison	bar with barmode
Line	Trends over time	scatter mode lines
Multi-series line	Group trends	scatter mode lines (multiple traces)
Scatter	Relationship between variables	scatter
Scatter with regression	Correlation analysis	scatter + trendline
Histogram	Distribution	histogram
Box plot	Distribution comparison	box
Heatmap	Matrix relationships	heatmap
Treemap	Hierarchical composition	treemap
Choropleth	Geographic data	choropleth / choroplethmapbox
Pie/Donut	Part-to-whole (≤5 categories)	pie

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Companion Skills

• dataviz-planner (upstream): Designs the visualization plan this executor implements
• dataviz-critic (downstream): Reviews the generated visualization for encoding honesty, accessibility, audience fit
• dashboard-planner (upstream, multi-chart): Designs dashboard architecture when multiple charts are needed

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meta-router Registry Note

Listed under the Executors table. Trigger signals: generate chart, create visualization, build chart, plot data, generate dataviz, create plotly chart, visualize this data