Mmcp.market

data-viz-renderer skill

by zebbern·zebbern/claude-code-guide·4.6k stars·MIT

Generate self-contained HTML/SVG infographics from JSON data, including stat cards, bar charts, flow diagrams, and mixed dashboards. Offers 8 color palettes and built-in icons with no external dependencies. Triggered when users request data visualization, infographics, charts, or dashboards.

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Install the data-viz-renderer skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/zebbern/claude-code-guide.git /tmp/claude-code-guide
mkdir -p ~/.claude/skills
cp -r /tmp/claude-code-guide/skills/data-viz-renderer ~/.claude/skills/data-viz-renderer
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Data Viz Renderer

Generate self-contained HTML/SVG infographics from JSON data. Four supported types:

  1. Stats Cards — KPI big numbers + trend arrows + icons
  2. Comparison Chart — Grouped bar chart with multiple series
  3. Flow Diagram — Step-by-step process with numbering, icons, and connecting arrows
  4. Dashboard — Mixed layout: stat cards + bar chart + donut chart + flow

Output is a fully self-contained HTML file (all CSS/SVG inline, no external dependencies), ready to open directly in a browser.

Usage

Basic Usage

python3 scripts/build_infographic.py config.json

Also supports reading from stdin:

cat config.json | python3 scripts/build_infographic.py

The script outputs a JSON status to stdout and writes the generated HTML to the path specified in the output field.

JSON Configuration Format

Common fields:

Color Palettes

Available values: auto (automatically chosen based on data), ocean, sunset, forest, berry, vibrant, corporate, pastel, earth

Data Format by Type

1. stats — Stat Cards

{
  "type": "stats",
  "data": [
    {
      "label": "Total Revenue",
      "value": "$1.2M",
      "icon": "money",
      "trend": "+12.5%",
      "trend_dir": "up"
    },
    {
      "label": "Users",
      "value": "45,230",
      "icon": "users",
      "trend": "+8.2%",
      "trend_dir": "up"
    }
  ]
}

icon options: users, user, money, percent, globe, clock, check, star, target, zap, chart-bar, chart-pie, database, rocket, shield, heart, light, search, mail, settings, flag, trending-up, trending-down

trenddir**: up (green upward arrow) or down (red downward arrow)

2. comparison — Bar Chart Comparison

{
  "type": "comparison",
  "data": {
    "chart_title": "Quarterly Revenue Comparison",
    "categories": ["Q1", "Q2", "Q3", "Q4"],
    "series": [
      {"name": "2024", "values": [320, 410, 380, 520]},
      {"name": "2025", "values": [380, 490, 450, 610]}
    ]
  }
}

3. flow — Flow Diagram

{
  "type": "flow",
  "data": [
    {"step": 1, "title": "Requirements", "description": "Gather user needs", "icon": "search"},
    {"step": 2, "title": "Design", "description": "Create technical plan", "icon": "light"},
    {"step": 3, "title": "Development", "description": "Code and test", "icon": "settings"},
    {"step": 4, "title": "Launch", "description": "Deploy to production", "icon": "rocket"}
  ]
}

4. dashboard — Mixed Dashboard

{
  "type": "dashboard",
  "data": {
    "stats": [
      {"label": "DAU", "value": "12.3K", "icon": "users", "trend": "+5%", "trend_dir": "up"},
      {"label": "Conversion Rate", "value": "3.8%", "icon": "target", "trend": "-0.2%", "trend_dir": "down"}
    ],
    "chart": {
      "chart_title": "Monthly Trend",
      "categories": ["Jan", "Feb", "Mar", "Apr"],
      "series": [{"name": "DAU", "values": [10200, 11500, 11800, 12300]}]
    },
    "breakdown": [
      {"label": "iOS", "value": 45},
      {"label": "Android", "value": 38},
      {"label": "Web", "value": 17}
    ],
    "flow": [
      {"step": 1, "title": "Sign Up", "description": ""},
      {"step": 2, "title": "Activate", "description": ""},
      {"step": 3, "title": "Retain", "description": ""}
    ]
  }
}

Output Format

The script outputs a JSON result to stdout:

{
  "status": "success",
  "output": "/absolute/path/to/infographic.html",
  "type": "stats",
  "title": "My Infographic",
  "palette": "auto",
  "size_bytes": 8432
}

On error:

{
  "status": "error",
  "errors": ["Missing required field: data"]
}

Design Highlights

  • Zero external dependencies: Pure Python standard library, no pip install needed
  • Self-contained output: HTML with all CSS and SVG inline, no network required
  • Responsive layout: Works on both desktop and mobile browsers
  • Professional palettes: 8 preset color schemes + automatic selection
  • 24+ built-in icons: Common SVG icons, no font files needed
  • CJK-friendly: Font stack includes Noto Sans SC, PingFang SC, Microsoft YaHei

Use Cases

  • Visualization modules in data reports
  • Product data dashboards
  • Business process illustrations
  • Quarterly/monthly data comparisons
  • Team KPI displays

Dependencies

  • Python 3.7+ (standard library only)

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