data-visualization
Design and generate accurate statistical visualizations with readable scales, labels, annotations, and source context.
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tessl review fix ./resources/bundled-skills/data-visualization/SKILL.mdData Visualization
Copyright (c) 2026 KunAgent. Licensed under the MIT License.
Purpose
Design and generate accurate statistical visualizations with readable scales, labels, annotations, and source context.
Tool routing
| Tool or skill | Use |
|---|---|
render_chart | Render governed charts directly from structured data. |
bash | Run Python visualization code for file-based figures. |
design_create_diagram | Create chart-like explanatory diagrams on canvas. |
Workflow
- Identify the analytical question and comparison structure.
- Validate data types, units, missing values, and aggregation.
- Select the simplest chart that preserves the relationship.
- Use direct labels, honest scales, accessible color, and source notes.
- Export at the requested dimensions and inspect the result.
Completion gates
- Check totals, ordering, axes, units, legends, and annotations against source data.
- Use zero baselines where magnitude comparison requires them.
- Avoid dual axes unless the relationship and scale are unambiguous.
Boundaries
- Do not smooth, truncate, or aggregate in ways that change the conclusion without disclosure.
- Do not use decorative charts when a table or metric is clearer.
Delivery
Lead with the outcome, name the evidence used for verification, and disclose any real limitation that remains.
- Repository
- KunAgent/Kun
- Commit
ebce7f6
- Last updated
- First committed
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