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blog-chart

agricidaniel/claude-blog

Generate dark-mode-compatible SVG charts for blog posts with automatic platform detection.

What is blog-chart?

Creates accessible inline SVG data visualizations (bar, donut, line, lollipop, area, radar) for blog content. Automatically detects HTML vs JSX/MDX output format and enforces WCAG compliance with proper ARIA labels, source attribution, and colorblind-friendly styling.

  • Generates 7 chart types: horizontal bar, grouped bar, donut, line, lollipop, area, and radar charts
  • Automatically detects platform (HTML vs JSX/MDX) and outputs correct syntax
  • Ensures dark-mode and light-mode compatibility using currentColor and CSS variables
  • Enforces accessibility with role=img, aria-labelledby, and full descriptions for screen readers
  • Applies colorblind-friendly color palette with patterns and direct labels, not color alone
  • Includes source attribution and proper chart dimensions with responsive scaling

How to install blog-chart

npx skills add https://github.com/agricidaniel/claude-blog --skill blog-chart
Prerequisites
  • Python 3 installed for the deterministic CLI script (optional; skill can be invoked programmatically)
  • Chart data in JSON format with type, title, values, and source attribution
Claude Code
Cursor
Windsurf
Cline

How to use blog-chart

  1. 1.Provide a chart request with type (horizontal bar, grouped bar, donut, line, lollipop, area, or radar), title, data values, and source attribution
  2. 2.Specify platform: 'html' for HTML output or 'mdx' for JSX/MDX syntax
  3. 3.Call the skill with the chart request; it auto-detects the best chart type if not specified
  4. 4.Review the generated SVG for proper styling, accessibility attributes, and source citation
  5. 5.Embed the SVG in your blog post within a <figure> element

Use cases

Good for
  • Visualizing quarterly product signups or performance metrics in blog posts
  • Comparing before/after data or A vs B scenarios with grouped bar charts
  • Displaying market share or parts-of-whole data with donut charts
  • Showing trends over time in product adoption or metrics with line charts
  • Ranking factors or correlations with lollipop charts for blog analysis pieces
Who it's for
  • Technical writers and bloggers creating data-driven content
  • Product managers documenting metrics and performance in blog posts
  • Data journalists and analysts publishing findings on company blogs
  • Content teams needing accessible, on-brand visualizations without external tools

blog-chart FAQ

Can I use this skill standalone or only with blog-write?

It's invoked internally by blog-write and blog-rewrite when chart-worthy data is detected, but can also be called directly via the Python CLI script (generate_chart_svg.py) with a JSON input file.

How does it handle dark mode?

All text uses fill='currentColor' and grid/axis lines use opacity values so they adapt to the host page's text color. The --chart-muted CSS variable controls muted text; it defaults to #4b5563 (light) or #d1d5db (dark) if not set.

What if I need a chart type not listed?

The skill supports 7 core types (bar, grouped bar, donut, line, lollipop, area, radar). For other visualizations, provide the data and context; the skill will recommend the closest matching type or suggest a combination.

Are the charts accessible to screen readers?

Yes. Every chart includes a <title> and <desc> with full data points and source, role='img', and aria-labelledby attributes. Labels and patterns ensure colorblind readers can distinguish series.

Can I customize colors or styling?

The skill enforces a fixed accessible color palette (orange, sky blue, purple, green) and styling rules for dark/light compatibility. Custom colors are not supported to maintain accessibility and brand consistency.

Full instructions (SKILL.md)

Source of truth, from agricidaniel/claude-blog.


name: blog-chart description: > Generate dark-mode-compatible inline SVG data visualization charts for blog posts. Supports horizontal bar, grouped bar, donut, line, lollipop, area, and radar charts with automatic platform detection (HTML vs JSX/MDX). Enforces chart type diversity, accessible markup (role=img, aria-labelledby), source attribution, and transparent backgrounds. Use when user says "blog chart", "generate chart", "data visualization", "svg chart", "blog graph", or "visualize data". user-invokable: false license: MIT

Blog Chart: Built-In SVG Data Visualization

Generates dark-mode-compatible inline SVG charts for blog posts. Invoked internally by blog-write and blog-rewrite when chart-worthy data is identified. Not a standalone user-facing command.

Styling source of truth: skills/blog/references/visual-media.md

For supported chart types, prefer the deterministic CLI:

python3 skills/blog-chart/scripts/generate_chart_svg.py --input chart.json --output chart.html --json

Input Format

The writer or researcher passes a chart request:

Chart Request:
- Type: horizontal bar
- Title: "Quarterly Signups by Product"
- Data: Product A 420, Product B 315, Product C 180
- Source: [Verified source], [publication date]
- Platform: mdx (or html)

Chart Type Selection

Select based on the data pattern. Prefer chart type diversity, but repeat a type when comparability or reader comprehension clearly benefits.

Data PatternBest Chart Type
Before/after comparisonGrouped bar chart
Ranked factors / correlationsLollipop chart
Parts of whole / market shareDonut chart
Trend over timeLine chart
Percentage improvementHorizontal bar chart
Distribution / rangeArea chart
Multi-dimensional scoringRadar chart

Styling Rules (Non-Negotiable)

All charts must work on both dark and light backgrounds:

Text elements:     fill="currentColor"
Grid lines:        stroke="currentColor" opacity="0.08"
Axis lines:        stroke="currentColor" opacity="0.3"
Background:        transparent (no fill on root SVG)
Subtitle text:     fill="var(--chart-muted, currentColor)"
Source text:        fill="var(--chart-muted, currentColor)"
Label text:        fill="currentColor" opacity="0.8"

Set --chart-muted to an accessible text token in the host theme. If no token exists, use #4b5563 on light backgrounds and #d1d5db on dark backgrounds. Do not rely on low-opacity source or subtitle text for visible attribution.

Color Palette

ColorHexUse Case
Orange#f97316Primary / highest value
Sky Blue#38bdf8Secondary / comparison
Purple#a78bfaTertiary / special category
Green#22c55eQuaternary / positive indicator

For text inside approved colored elements: use fill="#111827" with fontWeight="800". Only use white text after checking the contrast ratio is at least 4.5:1 against that specific fill color.

Do not rely on color alone. Add direct labels, patterns, line dashes, marker shapes, or legend text so colorblind readers can distinguish series.

Standard SVG Shell (HTML)

<svg
  viewBox="0 0 560 380"
  style="max-width: 100%; height: auto; font-family: 'Inter', system-ui, sans-serif"
  role="img"
  aria-labelledby="chart-title chart-desc"
>
  <title id="chart-title">Chart Title</title>
  <desc id="chart-desc">Description for screen readers with all key data points and source</desc>

  <!-- Chart content -->

  <text x="280" y="372" text-anchor="middle" font-size="10" fill="var(--chart-muted, currentColor)">
    Source: Source Name (Year)
  </text>
</svg>

JSX/MDX Shell (camelCase attributes)

<svg
  viewBox="0 0 560 380"
  style={{maxWidth: '100%', height: 'auto', fontFamily: "'Inter', system-ui, sans-serif"}}
  role="img"
  aria-labelledby="chart-title chart-desc"
>
  <title id="chart-title">Chart Title</title>
  <desc id="chart-desc">Description for screen readers</desc>

  {/* Chart content */}

  <text x="280" y="372" textAnchor="middle" fontSize="10" fill="var(--chart-muted, currentColor)">
    Source: Source Name (Year)
  </text>
</svg>

JSX Attribute Conversion (Required for MDX)

HTMLJSX
stroke-widthstrokeWidth
stroke-dasharraystrokeDasharray
stroke-linecapstrokeLinecap
text-anchortextAnchor
font-sizefontSize
font-weightfontWeight
font-familyfontFamily
classclassName
style="..."style={{...}}

Chart Type Construction

Horizontal Bar Chart

Best for: percentage improvements, single-metric comparisons.

  1. Define chart area: x=80, y=40, width=440, height=280
  2. Calculate bar height: chartHeight / dataCount - gap (gap=8)
  3. Calculate bar width: (value / maxValue) * chartWidth
  4. Position bars: y = chartY + index * (barHeight + gap)
  5. Label on left (right-aligned at x=75): category name
  6. Value label at end of bar: percentage or number
  7. Source text at bottom center

Grouped Bar Chart

Best for: before/after, A vs B comparisons.

  1. Define groups along Y axis, bars within each group
  2. Use 2 colors (primary + secondary) for the two series
  3. Add legend at top: colored square + label for each series
  4. Gap between groups > gap within groups

Donut Chart

Best for: parts of whole, market share.

  1. Center: cx=280, cy=180, outer radius=140, inner radius=80
  2. Calculate arc segments using cumulative angles
  3. Each segment: <path d="M... A... L... A... Z" fill="color" />
  4. Center text: total or key label
  5. Legend below chart with color squares + labels + values

Line Chart

Best for: trends over time.

  1. X axis: time periods, evenly spaced
  2. Y axis: value range with 4-5 grid lines
  3. Draw grid lines: stroke="currentColor" opacity="0.08"
  4. Plot data points: <circle cx=... cy=... r="4" fill="color" />
  5. Connect with: <polyline points="..." fill="none" stroke="color" strokeWidth="2" />
  6. Optional: area fill below line with opacity="0.1"

Lollipop Chart

Best for: ranked factors, correlations.

  1. Horizontal orientation (like bar chart but with circles)
  2. Thin line from axis to data point: stroke="currentColor" opacity="0.15" strokeWidth="1"
  3. Circle at data point: r="6" with fill color
  4. Value label next to circle
  5. Categories on Y axis (left-aligned)

Area Chart

Best for: distribution, cumulative data.

  1. Same as line chart but with filled area below
  2. Area fill: <path d="M... L... L... Z" fill="color" opacity="0.15" />
  3. Line on top: stroke="color" strokeWidth="2" fill="none"
  4. Grid lines behind the area

Radar Chart

Best for: multi-dimensional scoring (5-7 axes).

  1. Center: cx=280, cy=190
  2. Draw concentric polygons for grid (3-4 levels)
  3. Calculate axis endpoints at equal angles
  4. Plot data points on each axis proportional to value
  5. Connect data points with filled polygon: fill="color" opacity="0.2" stroke="color"
  6. Label each axis at the outer edge

Label Rules

  • Wrap long labels at word boundaries into <tspan> lines.
  • Truncate only when wrapping would collide with data marks, and keep the full label in <desc> or adjacent prose.
  • Use stable chart dimensions with a responsive max-width: 100%; height: auto style, or choose a justified wider viewBox for dense labels.
  • Check mobile widths so axis labels, legends, and value labels do not overlap.

Output Format

Wrap every chart in a <figure> element:

HTML:

<figure>
  <svg viewBox="0 0 560 380" style="max-width: 100%; height: auto; font-family: 'Inter', system-ui, sans-serif" role="img" aria-labelledby="chart-title chart-desc">
    <title id="chart-title">[Chart Title]</title>
    <desc id="chart-desc">[Full description with data points for screen readers]</desc>
    <!-- chart content -->
    <text x="280" y="372" text-anchor="middle" font-size="10" fill="var(--chart-muted, currentColor)">
      Source: [Source Name] ([Year])
    </text>
  </svg>
  <figcaption>Source: <a href="[Source URL]">[Source Name]</a>, [publication date].</figcaption>
</figure>

MDX:

<figure className="chart-container" style={{margin: '2.5rem 0', textAlign: 'center', padding: '1.5rem', borderRadius: '12px'}}>
  <svg viewBox="0 0 560 380" style={{maxWidth: '100%', height: 'auto', fontFamily: "'Inter', system-ui, sans-serif"}} role="img" aria-labelledby="chart-title chart-desc">
    <title id="chart-title">[Chart Title]</title>
    <desc id="chart-desc">[Full description]</desc>
    {/* chart content with camelCase attributes */}
    <text x="280" y="372" textAnchor="middle" fontSize="10" fill="var(--chart-muted, currentColor)">
      Source: [Source Name] ([Year])
    </text>
  </svg>
  <figcaption>Source: <a href="[Source URL]">[Source Name]</a>, [publication date].</figcaption>
</figure>

Quality Checklist (Verify Before Returning)

  • No hardcoded text colors except contrast-checked labels inside colored elements
  • No white/light backgrounds (transparent or none)
  • Source attribution text present at bottom and semantic <figcaption> present
  • role="img" and aria-labelledby present on <svg>
  • <title id> and <desc id> present inside <svg>
  • Chart type choice supports comprehension and comparability
  • If MDX: all attributes camelCased (no hyphens in attribute names)
  • Data values match the source data exactly
  • Color palette uses only approved colors
  • ViewBox is 0 0 560 380 (standard) or justified alternative
  • Labels, shapes, patterns, or line styles provide redundancy beyond color