
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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| Installs | 3 |
|---|---|
| repo stars | ★ 6 |
| Last updated | January 30, 2026 |
| Repository | claude-office-skills/skills-hub ↗ |
What it does
Helps with design & ui/ux tasks.
Files
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, #9a60b4Cool
#1f77b4, #aec7e8, #17becf, #9edae5, #6baed6, #c6dbef, #08519c, #3182bdWarm
#ff7f0e, #ffbb78, #d62728, #ff9896, #e377c2, #f7b6d2, #bcbd22, #dbdb8dAccessible (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!