Agent Skills
› aiming-lab/MetaClaw
› visualization-selection
visualization-selection
GitHub提供图表选择指南，帮助用户根据数据关系（如比较、分布、趋势等）选择最合适的可视化类型，并遵循标注、配色及避免误导等最佳实践原则。
Trigger Scenarios
创建图表或绘图时
设计仪表盘时
Install
npx skills add aiming-lab/MetaClaw --skill visualization-selection -g -y
SKILL.md
Frontmatter
{
"name": "visualization-selection",
"category": "data_analysis",
"description": "Use this skill when creating charts, plots, or dashboards. Choose the visualization type that best communicates the data relationship before writing any plotting code."
}
Visualization Selection Guide
| Goal | Chart Type |
|---|---|
| Compare categories | Bar chart (horizontal if many labels) |
| Show distribution | Histogram, box plot, violin plot |
| Show trend over time | Line chart |
| Show correlation | Scatter plot, heatmap |
| Show part-to-whole | Pie (<=5 slices), stacked bar |
Principles:
- Label axes and include units.
- Use color purposefully — not just for decoration.
- Avoid 3D charts; they distort perception.
- Start y-axis at 0 for bar charts (truncated bars mislead).
- Use a colorblind-safe palette (e.g.,
viridis,colorbrewer).
Version History
- 922caf3 Current 2026-07-25 11:09
