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data-visualization · dylantarre — Claude Code skill: what it does, how to install

Applies Disney's 12 animation principles to charts, dashboards, and data transitions. Helps Claude Code configure motion timing and easing in D3.js and Chart.js.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add dylantarre/animation-principles --skill data-visualization -a claude-code
Open on GitHub

What data-visualization does

This skill brings classic Disney motion principles into charts and information dashboards. It instructs the assistant on staged element reveals, value transitions, and counter interpolations. Motion must never distort actual metrics. Visual scales, data points, and coordinate axes remain strictly accurate while elements settle.

Specific timing guidelines are provided for common visualizations. Line charts draw over 600ms, pie charts sweep clockwise in 500ms, and data updates run between 200ms and 300ms. The prompt contains reference snippets for D3.js easing using d3.easeCubicInOut alongside transition settings for Chart.js.

Accessibility is a strict requirement. Every animated display must honor the prefers-reduced-motion media query by rendering immediate state changes when motion is turned off.

What it helps with

  • stagger bar and label arrivals in chart components
  • apply precise transition timing for D3.js and Chart.js
  • animate pie charts and Sankey diagrams along circular paths
  • create immediate fallback states for prefers-reduced-motion

Example prompts for the agent

  • Add staggered entry transitions to this D3.js bar chart
  • Configure smooth value updates in Chart.js with proper easing
  • Animate this clockwise pie chart reveal and handle prefers-reduced-motion

How to install data-visualization

1Skills CLI (Vercel)

npx skills add dylantarre/animation-principles --skill data-visualization -a claude-code

2Manually: put the files in place

~/.claude/skills/data-visualization/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/data-visualization/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about data-visualization

How to install data-visualization in Claude Code?

Run npx skills add dylantarre/animation-principles --skill data-visualization -a claude-code. The file is saved directly to ~/.claude/skills/data-visualization/SKILL.md.

What does the data-visualization skill do?

It guides the agent on applying classic animation concepts to charts, scatter plots, and dashboard cards. It sets duration standards for entries and updates so movement improves legibility instead of cluttering the screen.

Which charting libraries does this skill cover?

It provides ready-to-use code patterns for D3.js and Chart.js. You can also apply the underlying timing and easing tables to other charting tools.

Source text

SKILL.md · MIT
---
name: data-visualization
description: Use when animating charts, graphs, dashboards, data transitions, or any information visualization work.
---

# Data Visualization Animation

Apply Disney's 12 animation principles to charts, graphs, dashboards, and information displays.

## Quick Reference

| Principle | Data Viz Implementation |
|-----------|------------------------|
| Squash & Stretch | Bar overshoot, elastic settling |
| Anticipation | Brief pause before data loads |
| Staging | Sequential reveal, focus hierarchy |
| Straight Ahead / Pose to Pose | Streaming vs snapshot data |
| Follow Through / Overlapping | Staggered element entry |
| Slow In / Slow Out | Smooth value interpolation |
| Arc | Pie chart sweeps, flow diagrams |
| Secondary Action | Labels following data points |
| Timing | Entry 300-500ms, updates 200-300ms |
| Exaggeration | Emphasize significant changes |
| Solid Drawing | Consistent scales, clear relationships |
| Appeal | Satisfying reveals, professional polish |

## Principle Applications

**Squash & Stretch**: Bars can overshoot target height then settle. Pie slices expand slightly on hover. Bubbles compress on collision. Keep total values accurate—animation is transitional.

**Anticipation**: Brief loading state before data appears. Slight shrink before expansion. Counter briefly pauses before rapid counting. Prepares user for incoming information.

**Staging**: Reveal data in meaningful sequence—most important first. Highlight active data series. Dim unrelated elements during focus. Guide the data story with motion.

**Straight Ahead vs Pose to Pose**: Real-time streaming data animates continuously (straight ahead). Dashboard snapshots transition between states (pose to pose). Match approach to data nature.

**Follow Through & Overlapping**: Data points enter with staggered timing. Labels settle after their data elements. Grid lines appear before data. Legends animate with slight delay.

**Slow In / Slow Out**: Value changes ease smoothly—no jarring jumps. Use `d3.easeCubicInOut` or equivalent. Counter animations accelerate then decelerate. Progress bars ease to completion.

**Arc**: Pie charts sweep clockwise from 12 o'clock. Sankey diagram flows follow curved paths. Network graphs use force-directed arcs. Radial charts expand from center.

**Secondary Action**: Tooltips follow data point movement. Value labels count up as bars grow. Axis tick marks respond to scale changes. Shadows indicate data depth.

**Timing**: Initial entry: 300-500ms staggered. Data updates: 200-300ms. Hover states: 100-150ms. Filter transitions: 400-600ms. Slower timing aids comprehension.

**Exaggeration**: Significant changes deserve attention—pulse or glow outliers. Threshold crossings trigger emphasis. Anomalies animate more dramatically. Don't exaggerate the data itself.

**Solid Drawing**: Maintain consistent scales during animation. Transitions shouldn't distort data relationships. Preserve axis alignment. Visual hierarchy must remain clear throughout motion.

**Appeal**: Data entry should feel satisfying. Professional, purposeful motion builds trust. Avoid gratuitous animation—every motion should aid understanding.

## Code Patterns

### D3.js
```javascript
// Staggered bar entry with easing
bars.transition()
    .duration(500)
    .delay((d, i) => i * 50)
    .ease(d3.easeCubicOut)
    .attr("height", d => yScale(d.value))
    .attr("y", d => height - yScale(d.value));

// Smooth data updates
bars.transition()
    .duration(300)
    .ease(d3.easeCubicInOut)
    .attr("height", d => yScale(d.value));
```

### Chart.js
```javascript
// Animation configuration
options: {
    animation: {
        duration: 500,
        easing: 'easeOutQuart',
        delay: (context) => context.dataIndex * 50
    }
}
```

## Data Type Timing

| Visualization | Entry | Update | Hover |
|--------------|-------|--------|-------|
| Bar chart | 400ms stagger | 300ms | 100ms |
| Line chart | 600ms draw | 400ms | 150ms |
| Pie chart | 500ms sweep | 300ms | 100ms |
| Scatter plot | 300ms stagger | 200ms | 100ms |
| Dashboard | 500-800ms cascade | 300ms | 150ms |

## Accessibility Note

Always respect `prefers-reduced-motion`. Data visualization animation should aid comprehension, not hinder it. Provide instant-state fallback for users who disable motion.

© dylantarre · MIT · dylantarre/animation-principles

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