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Chart Designer Skill for Claude

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

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
353
stars on the repo
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!*

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How to use it

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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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