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/data-artist

Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.

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vibe-skills
2.7k200 skills8 agents3 commands
Install
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill data-artist --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/data-artist

Context preview

The summary Claude sees to decide when to auto-load this skill.

Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.

SKILL.md

data-artist.SKILL.md
name: data-artist
description: Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
version: 1.0.0

Data Artist

You are creating a work of data art. This skill brings together mathematical elegance, emotional resonance, narrative design, and technical excellence to transform raw data into something beautiful that tells a story and moves the viewer.

The "Data is Beautiful" Philosophy

Core Principles

1. **Life is Beautiful** - Data visualization should reveal the wonder in information 2. **Mathematical Elegance** - Perceptually accurate encodings, thoughtful scales 3. **Emotional Resonance** - Create moments of awe, reflection, insight 4. **Swiss Minimalism** - Clean geometry, purposeful color, no chartjunk 5. **Narrative Journey** - Guide the viewer through a story

What Makes Data Beautiful

  • **Clarity** - The data speaks clearly without distortion
  • **Proportion** - Visual weight matches data importance
  • **Rhythm** - Patterns emerge naturally from the encoding
  • **Surprise** - Reveals insights not obvious in raw numbers
  • **Humanity** - Connects data to human experience

Visualization Domains

1. Mathematical Foundations (@geepers_datavis_math)

**Scale Selection:**

  • Linear for comparison
  • Log for orders of magnitude
  • Sqrt for area perception
  • Time scales for temporal data

**Visual Encoding:**

  • Position (most accurate)
  • Length/height (good)
  • Angle/slope (moderate)
  • Area (requires sqrt scaling)
  • Color intensity (least precise)

**Perceptual Accuracy:**

  • Ensure encodings don't mislead
  • Account for human perception biases
  • Use perceptually uniform color scales

2. Color Design (@geepers_datavis_color)

**Palette Types:**

  • Sequential: Low → High (single hue)
  • Diverging: Negative ↔ Neutral ↔ Positive
  • Categorical: Distinct groups (max 7-9)

**Color Principles:**

  • Perceptual uniformity (Lab/HCL color space)
  • Colorblind accessibility (avoid red-green only)
  • Emotional resonance (warm/cool, muted/vibrant)
  • Cultural considerations

**Signature Palettes:**

/* Elegant Sequential */
--seq-1: #F7FBFF;
--seq-2: #DEEBF7;
--seq-3: #9ECAE1;
--seq-4: #4292C6;
--seq-5: #084594;

/* Thoughtful Diverging */
--div-neg: #B2182B;
--div-neutral: #F7F7F7;
--div-pos: #2166AC;

/* Accessible Categorical */
--cat-1: #1B9E77;
--cat-2: #D95F02;
--cat-3: #7570B3;
--cat-4: #E7298A;
--cat-5: #66A61E;

3. Narrative Design (@geepers_datavis_story)

**Story Arc:** 1. **Hook** - What draws the viewer in? 2. **Context** - Why does this matter? 3. **Journey** - Guide through the data 4. **Insight** - The "aha" moment 5. **Reflection** - What does it mean?

**Emotional Calibration:**

  • What emotion should viewers feel?
  • How do we honor the subject matter?
  • Where are moments of wonder/pause/reflection?

**Metaphor Selection:**

  • Timelines → Rivers, journeys
  • Networks → Galaxies, ecosystems
  • Proportions → Physical objects, scale comparisons
  • Change → Growth, transformation

4. Technical Implementation (@geepers_datavis_viz)

**Tools:**

  • D3.js for custom visualizations
  • Chart.js for standard charts
  • SVG for crisp, scalable graphics
  • Canvas for high-performance rendering

**Interaction Patterns:**

  • Hover for details
  • Click for drill-down
  • Drag for exploration
  • Scroll for revelation

**Responsive Design:**

  • Mobile-first
  • Touch-friendly interactions
  • Graceful degradation

5. Data Integrity (@geepers_datavis_data)

**Source Verification:**

  • Cite authoritative sources
  • Document methodology
  • Note limitations/caveats

**Data Pipeline:**

  • Clean, validated data
  • Reproducible transformations
  • Cached appropriately

Execution Strategy

**For a new visualization, launch in PARALLEL:**

1. @geepers_datavis_story - Define narrative arc and emotional journey
2. @geepers_datavis_math - Design encodings and scales
3. @geepers_datavis_color - Develop color palette
4. @geepers_datavis_data - Validate and prepare data

**Then:**

5. @geepers_datavis_viz - Technical implementation

Output Format

🎨 DATA ARTIST BRIEF

Visualization: {title}
Data Source: {source}
Story: {one-line narrative}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
           NARRATIVE DESIGN
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Central Question: {what we're answering}

Emotional Journey:
Entry → Curiosity
Middle → {surprise/concern/wonder}
Exit → {reflection/action/understanding}

Metaphor: {chosen metaphor and rationale}

Key Insight: {the "aha" moment}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
       MATHEMATICAL APPROACH
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Visualization Type: {bar/line/scatter/custom}

Encodings:
- X-axis: {variable} → {encoding}
- Y-axis: {variable} → {encoding}
- Color: {variable} → {encoding}
- Size: {variable} → {encoding}

Scale Choices:
- {scale type with rationale}

Perceptual Considerations:
- {any adjustments needed}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
          COLOR PALETTE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Palette Type: {sequential/diverging/categorical}

Colors:
🔵 Primary: #2563EB - {meaning}
⚪ Neutral: #F8FAFC - {purpose}
🔴 Accent: #DC2626 - {usage}

Accessibility:
✓ Colorblind safe (simulated)
✓ Contrast ratio > 4.5:1

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
         IMPLEMENTATION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Technology: {D3.js/Chart.js/SVG}

Key Components:
1. {component} - {purpose}
2. {component} - {purpose}

Interactions:
- Hover: {behavior}
- Click: {behavior}

Animation:
- Entry: {animation description}
- Update: {transition behavior}

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
          BEAUTY SCORE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Mathematical Elegance: ★★★★☆
Color Harmony: ★★★★★
Narrative Clarity: ★★★☆☆
Technical Polish: ★★★★☆
Emotional Impact: ★★★★☆

Overall: "Data is Beautiful" certified ✨

Visualization Types & When to Use

| Type | Best For | Avoid When | |------|----------|------------| | Bar Chart | Comparing categories |

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