Chart Designer

作者 claude-office-skills9c4c7d5cd281MIT499 个星标收录于 2026年10月8日更新于 2026年10月8日仓库8个月前更新

Design effective data visualizations and charts. Generate chart configurations for ECharts, Chart.js, and other libraries. Create dashboards and reports.

仅含说明Data & Analytics
AI 生成的概览

推荐图表类型,并生成 ECharts、Chart.js 和 Excel 图表配置及样式建议。

功能
该技能提供数据可视化设计建议:通过选择表和决策树,把所描述的数据与表达目的对应到合适的图表类型。随后输出可直接使用的 ECharts 与 Chart.js 配置片段、Excel 图表设置说明、配色方案、字体与布局建议,以及最佳实践和备选方案说明。它本身不渲染图表,也不直接访问数据。
适用场景
当你需要为某组数据选择合适的图表,或需要为仪表板、报告、演示文稿生成图表配置代码时使用。它也适用于配色方案、样式与可视化最佳实践咨询,或 Excel 图表规格说明。
运行要求
仅为说明性内容,不附带脚本。文中提到 office-mcp 服务器及其 create_chart、read_xlsx、create_xlsx 工具,但该技能本身只产出文字建议和配置片段,因此严格来说不需要运行时、软件包或凭据。

Chart Designer Skill

Overview

I help you design effective data visualizations by recommending the right chart types, generating configurations for popular charting libraries, and applying data visualization best practices.

What I can do:

  • Recommend appropriate chart types for your data
  • Generate ECharts/Chart.js configurations
  • Design dashboard layouts
  • Apply visualization best practices
  • Create Excel chart specifications
  • Suggest color schemes and styling

What I cannot do:

  • Render charts directly (use generated configs in tools)
  • Create custom chart types from scratch
  • Access your data directly

How to Use Me

Step 1: Describe Your Data

Tell me:

  • What type of data you have
  • What story you want to tell
  • Your audience (technical, executive, public)
  • Where it will be displayed (presentation, dashboard, report)

Step 2: Get Recommendations

I'll suggest:

  • Best chart type(s) for your data
  • Configuration options
  • Color schemes
  • Layout considerations

Step 3: Receive Chart Configs

I'll provide:

  • ECharts JSON configuration
  • Chart.js configuration
  • Excel chart setup instructions
  • CSS/styling recommendations

Chart Selection Guide

Comparison Charts

Chart TypeBest ForData Requirements
Bar ChartComparing categoriesCategories + values
Grouped BarMultiple series comparisonCategories + multiple series
Stacked BarPart-to-whole comparisonCategories + component values

Trend Charts

Chart TypeBest ForData Requirements
Line ChartChange over timeTime series data
Area ChartCumulative trendsTime series (stacked optional)
SparklineCompact trendsSimple time series

Distribution Charts

Chart TypeBest ForData Requirements
HistogramValue distributionNumeric values
Box PlotDistribution summaryNumeric values with quartiles
Scatter PlotCorrelationTwo numeric variables

Part-to-Whole Charts

Chart TypeBest ForData Requirements
Pie ChartSimple proportions (≤5 items)Categories + percentages
Donut ChartProportions with totalCategories + percentages
TreemapHierarchical proportionsHierarchical data + values

Specialized Charts

Chart TypeBest ForData Requirements
FunnelProcess stages/conversionStages + values
GaugeSingle KPI vs targetCurrent value + target
HeatmapMatrix comparisonsRow + Column + Value
RadarMulti-dimensional comparisonMultiple metrics per item
SankeyFlow/transitionsSource + Target + Value

Decision Tree

What do you want to show?│├─ Comparison│   ├─ Among items → Bar Chart│   ├─ Over time → Line Chart│   └─ Multiple series → Grouped/Stacked Bar│├─ Composition│   ├─ Static → Pie/Donut (≤5) or Treemap│   ├─ Over time → Stacked Area│   └─ Hierarchical → Treemap/Sunburst│├─ Distribution│   ├─ Single variable → Histogram│   ├─ Multiple datasets → Box Plot│   └─ Two variables → Scatter Plot│├─ Relationship│   ├─ Two variables → Scatter Plot│   ├─ Three variables → Bubble Chart│   └─ Correlation matrix → Heatmap│└─ Flow/Process    ├─ Sequential stages → Funnel    ├─ Transitions → Sankey    └─ Single metric → Gauge

Output Format

markdown
# Chart Design: [Title]
**Data Type**: [Description]**Purpose**: [What story to tell]**Recommended Chart**: [Chart type]
---
## Chart Configuration
### ECharts
```javascriptconst option = {  title: {    text: 'Chart Title',    left: 'center'  },  tooltip: {    trigger: 'axis'  },  legend: {    data: ['Series 1', 'Series 2'],    bottom: 10  },  xAxis: {    type: 'category',    data: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']  },  yAxis: {    type: 'value'  },  series: [    {      name: 'Series 1',      type: 'bar',      data: [120, 200, 150, 80, 70, 110]    },    {      name: 'Series 2',      type: 'line',      data: [100, 180, 160, 90, 80, 100]    }  ]};

Chart.js

javascript
const config = {  type: 'bar',  data: {    labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'],    datasets: [{      label: 'Series 1',      data: [120, 200, 150, 80, 70, 110],      backgroundColor: 'rgba(54, 162, 235, 0.8)'    }]  },  options: {    responsive: true,    plugins: {      title: {        display: true,        text: 'Chart Title'      }    }  }};

Styling Recommendations

Color Palette

  • Primary: #5470c6
  • Secondary: #91cc75
  • Accent: #fac858
  • Neutral: #73c0de

Typography

  • Title: 16px, bold
  • Labels: 12px, regular
  • Axis: 11px, light

Best Practices Applied

  1. [Practice 1]
  2. [Practice 2]
  3. [Practice 3]

Alternative Charts

If this doesn't work well, consider:

  1. [Alternative 1] - when [condition]
  2. [Alternative 2] - when [condition]

---
## ECharts Common Configurations
### Bar Chart```javascript{  xAxis: { type: 'category', data: categories },  yAxis: { type: 'value' },  series: [{    type: 'bar',    data: values,    itemStyle: { color: '#5470c6' }  }]}

Line Chart

javascript
{  xAxis: { type: 'category', data: categories },  yAxis: { type: 'value' },  series: [{    type: 'line',    data: values,    smooth: true,    areaStyle: {} // for area chart  }]}

Pie Chart

javascript
{  series: [{    type: 'pie',    radius: ['40%', '70%'], // donut    data: [      { value: 100, name: 'A' },      { value: 200, name: 'B' }    ]  }]}

Scatter Plot

javascript
{  xAxis: { type: 'value' },  yAxis: { type: 'value' },  series: [{    type: 'scatter',    data: [[x1, y1], [x2, y2]],    symbolSize: 10  }]}

Color Palettes

Professional

#5470c6, #91cc75, #fac858, #ee6666, #73c0de, #3ba272, #fc8452, #9a60b4

Cool

#1f77b4, #aec7e8, #17becf, #9edae5, #6baed6, #c6dbef, #08519c, #3182bd

Warm

#ff7f0e, #ffbb78, #d62728, #ff9896, #e377c2, #f7b6d2, #bcbd22, #dbdb8d

Accessible (colorblind-friendly)

#0077BB, #33BBEE, #009988, #EE7733, #CC3311, #EE3377, #BBBBBB

Best Practices

Data Ink Ratio

  • Remove unnecessary gridlines
  • Minimize chart junk
  • Let data be the focus

Clarity

  • Clear, descriptive titles
  • Labeled axes with units
  • Appropriate precision (not too many decimals)

Comparison

  • Start y-axis at zero for bar charts
  • Use consistent scales for comparison
  • Sort data logically

Color

  • Use color purposefully
  • Consider colorblind users
  • Don't use too many colors (≤7)

Interaction

  • Tooltips for details
  • Zoom for dense data
  • Drill-down for hierarchies

Tips for Better Charts

  1. Know your audience - technical vs. executive
  2. Start with the question - what are you trying to answer?
  3. Choose the right chart - don't force data into wrong formats
  4. Simplify - less is more
  5. Label clearly - assume viewers have no context
  6. Test with real users - is the message clear?
  7. Consider accessibility - colors, contrast, alt text

Limitations

  • Cannot render charts directly
  • Configuration may need adjustment for specific tools
  • Complex custom visualizations may require code
  • Real-time data requires additional setup

Built by the Claude Office Skills community. Contributions welcome!

来源与署名

来源:claude-office-skills/skills位于chart-designer提交9c4c7d5

许可证: MIT

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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