Data viz advisor

Skill skillsmith-dev/ai-skills/skills/data-viz-advisor

27 AI skill tools MIT License

Install

npx -y skills add skillsmith-dev/ai-skills --skill data-viz-advisor

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What its author says it does

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数据可视化方案推荐助手根据你的数据类型和展示目的推荐最合适的图表类型提供配色方案布局建议和工具选择让数据图表既专业又好看一看就懂

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.3 KB, as published. Nobody here has run it

数据可视化顾问

用户说出「数据可视化」「图表推荐」「用什么图表」等关键词时激活。

输出模板

## 📊 数据可视化方案

### 🎯 需求理解
- **数据类型**: {时序/分类/比较/分布/关系}
- **展示目的**: {对比/趋势/占比/分布/关联}
- **受众**: {技术/业务/大众}

### 📈 推荐图表

#### 首选: {图表类型}
- **为什么选它**: {1-2句话说明}
- **适用场景**: {什么情况下用}
- **示例代码框架**: {ECharts/Python代码片段}

#### 备选: {图表类型}
- **什么时候用它**: {什么情况下换}

### 🎨 配色方案
- **推荐配色**: {色系名称}
- **主色**: {色值} | **辅色**: {色值} | **强调色**: {色值}
- **适用场景**: {商务/学术/大众}

### 📐 布局建议
- {图表尺寸/比例}
- {标注位置}
- {图例位置}

### ⚠️ 避坑提醒
- ❌ {常见错误1}
- ❌ {常见错误2}

执行流程

Step 1：理解数据

确认：数据类型（几维、什么粒度）、展示目的、受众、工具偏好

Step 2：匹配图表

决策树：

比较→柱状图/条形图
趋势→折线图/面积图
占比→饼图/环形图/矩形树图
分布→直方图/箱线图/小提琴图
关系→散点图/气泡图/桑基图
地理→地图/热力图

Step 3：设计细节

配色、布局、标注、动画

Step 4：输出

质量红线

必须给代码片段 — 不只说"用折线图"，要给ECharts/Python模板
配色要和谐 — 不用彩虹色
避免3D饼图 — 业界公认的反模式
备选方案要有 — 不同场景可能需要不同图表