/data-artist
Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill data-artist --agent claude-codeHow 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.mdname: 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 |
Read more
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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