mcpbeat

Chart Designer

claude-office-skills/chart-designer

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

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on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/claude-office-skills/skills --skill chart-designer

The instruction itself

32 sections, as written by the author

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 Type | Best For | Data Requirements |

|------------|----------|-------------------|

| Bar Chart | Comparing categories | Categories + values |

| Grouped Bar | Multiple series comparison | Categories + multiple series |

| Stacked Bar | Part-to-whole comparison | Categories + component values |

Trend Charts

| Chart Type | Best For | Data Requirements |

|------------|----------|-------------------|

| Line Chart | Change over time | Time series data |

| Area Chart | Cumulative trends | Time series (stacked optional) |

| Sparkline | Compact trends | Simple time series |

Distribution Charts

| Chart Type | Best For | Data Requirements |

|------------|----------|-------------------|

| Histogram | Value distribution | Numeric values |

| Box Plot | Distribution summary | Numeric values with quartiles |

| Scatter Plot | Correlation | Two numeric variables |

Part-to-Whole Charts

| Chart Type | Best For | Data Requirements |

|------------|----------|-------------------|

| Pie Chart | Simple proportions (≤5 items) | Categories + percentages |

| Donut Chart | Proportions with total | Categories + percentages |

| Treemap | Hierarchical proportions | Hierarchical data + values |

Specialized Charts

| Chart Type | Best For | Data Requirements |

|------------|----------|-------------------|

| Funnel | Process stages/conversion | Stages + values |

| Gauge | Single KPI vs target | Current value + target |

| Heatmap | Matrix comparisons | Row + Column + Value |

| Radar | Multi-dimensional comparison | Multiple metrics per item |

| Sankey | Flow/transitions | Source + 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

# Chart Design: [Title]

**Data Type**: [Description]
**Purpose**: [What story to tell]
**Recommended Chart**: [Chart type]

---

## Chart Configuration

### ECharts

const 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

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

{
  xAxis: { type: 'category', data: categories },
  yAxis: { type: 'value' },
  series: [{
    type: 'bar',
    data: values,
    itemStyle: { color: '#5470c6' }
  }]
}

Line Chart

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

Pie Chart

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

Scatter Plot

{
  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

  • Know your audience - technical vs. executive
  • Start with the question - what are you trying to answer?
  • Choose the right chart - don't force data into wrong formats
  • Simplify - less is more
  • Label clearly - assume viewers have no context
  • Test with real users - is the message clear?
  • 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!*

How to use it

Copy the folder

Take claude-office-skills/chart-designer from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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