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Chart Designer

  • 3 installs
  • 6 repo stars
  • Updated January 30, 2026
  • claude-office-skills/skills-hub

This is a copy of chart-designer by claude-office-skills - installs and ranking accrue to the original listing.

Helps with design & ui/ux tasks.

About

chart-designer is a Claude Code skill for design & ui/ux. It helps solo builders move faster with AI-assisted development.

  • chart-designer
  • Design & UI/UX
  • AI-coding skill

Chart Designer by the numbers

  • 3 all-time installs (skills.sh)
  • Data as of Jul 31, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs3
repo stars6
Last updatedJanuary 30, 2026
Repositoryclaude-office-skills/skills-hub

What it does

Helps with design & ui/ux tasks.

Files

SKILL.mdMarkdownGitHub ↗

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

# 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

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!

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