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d3-visualization

Build deterministic, verifiable data visualizations with D3.js (v6). Generate standalone HTML/SVG (and optional PNG) from local data files without external network dependencies

Install / Use

npx skills add benchflow-ai/skillsbench --skill d3-visualization

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Supported Platforms

Universal

Tags

Our assessment of d3-visualization

d3-visualization scores 92/100 on our quality scale, 127th of 491 Data & Analytics skills we index (top 26%).

Its SKILL.md is 6.0 KB long, well organised into 14 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.

With 1,813 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so d3-visualization is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-02. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

d3-visualization compared with similar skills

All 4 of these similar skills score higher than d3-visualization; compare them before choosing.

SkillScoreStarsUpdatedFormat
d3-visualization (this skill)by benchflow-ai921.8k2mo agoSKILL.md
algorithmic-artby anthropics100177.9k9d agoSKILL.md
pptxby anthropics100177.9k9d agoSKILL.md
designby nextlevelbuilder100130.2k11d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k11d agoSKILL.md

Frequently asked questions

How do I install d3-visualization?
Run npx skills add benchflow-ai/skillsbench --skill d3-visualization. The install tabs above show the steps for each supported agent.
Which AI agents does d3-visualization work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is d3-visualization safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is d3-visualization still maintained?
The repository was last updated about 2 months ago, so d3-visualization is actively maintained.

name: d3-visualization description: Build deterministic, verifiable data visualizations with D3.js (v6). Generate standalone HTML/SVG (and optional PNG) from local data files without external network dependencies. Use when tasks require charts, plots, axes/scales, legends, tooltips, or data-driven SVG output.

D3.js Visualization Skill

Use this skill to turn structured data (CSV/TSV/JSON) into clean, reproducible visualizations using D3.js. The goal is to produce stable outputs that can be verified by diffing files or hashing.

When to use

Activate this skill when the user asks for any of the following:

  • “Make a chart/plot/graph/visualization”
  • bar/line/scatter/area/histogram/box/violin/heatmap
  • timelines, small multiples, faceting
  • axis ticks, scales, legends, tooltips
  • data-driven SVG output for a report or web page
  • converting data to a static SVG or HTML visualization

If the user only needs a quick table or summary, don’t use D3—use a spreadsheet or plain markdown instead.


Inputs you should expect

  • One or more local data files: *.csv, *.tsv, *.json
  • A chart intent:
    • chart type (or you infer the best type)
    • x/y fields and aggregation rules
    • sorting/filtering rules
    • dimensions (width/height) and margins
    • color rules (categorical / sequential)
    • any labeling requirements (title, axis labels, units)
  • Output constraints:
    • “static only”, “no animation”, “must be deterministic”, “offline”, etc.

If details are missing, make reasonable defaults and document them in comments near the top of the output file.


Outputs you should produce

Prefer producing all of the following when feasible:

  1. dist/chart.html — standalone HTML that renders the visualization
  2. dist/chart.svg — exported SVG (stable and diff-friendly)
  3. (Optional) dist/chart.png — if the task explicitly needs a raster image

Always keep outputs in a predictable folder (default: dist/), unless the task specifies paths.


Determinism rules (non-negotiable)

To keep results stable across runs and machines:

Data determinism

  • Sort input rows deterministically before binding to marks (e.g., by x then by category).
  • Use stable grouping order (explicit Array.from(grouped.keys()).sort()).
  • Avoid locale-dependent formatting unless fixed (use d3.format, d3.timeFormat with explicit formats).

Rendering determinism

  • No randomness: do not use Math.random() or d3-random.
  • No transitions/animations by default (transitions can introduce timing variance).
  • Fixed width, height, margin, viewBox.
  • Use explicit tick counts only when needed; otherwise rely on D3 defaults but keep domains fixed.
  • Avoid layout algorithms with non-deterministic iteration unless you control seeds/iterations (e.g., force simulation). If a force layout is required:
    • fix the tick count,
    • fix initial positions deterministically (e.g., sorted nodes placed on a grid),
    • run exactly N ticks and stop.

Offline + dependency determinism

  • Do not load D3 from a CDN.
  • Pin D3 to a specific version (default: d3@7.9.0).
  • Prefer vendoring a minified D3 bundle (e.g., vendor/d3.v7.9.0.min.js) or bundling with a lockfile.

File determinism

  • Stable SVG output:
    • Avoid auto-generated IDs that may change.
    • If you must use IDs (clipPath, gradients), derive them from stable strings (e.g., "clip-plot").
  • Use LF line endings.
  • Keep numeric precision consistent (e.g., round to 2–4 decimals if needed).

Recommended project layout

If the task doesn't specify an existing structure, use:

dist/
  chart.html        # standalone HTML with inline or linked JS/CSS
  chart.svg         # exported SVG (optional but nice)
  chart.png         # rasterized (optional)
vendor/
  d3.v7.9.0.min.js  # pinned D3 library

Interactive features (tooltips, click handlers, hover effects)

When the task requires interactivity (e.g., tooltips on hover, click to highlight):

Tooltip pattern (recommended)

  1. Create a tooltip element in HTML:
<div id="tooltip" class="tooltip"></div>
  1. Style with CSS using .visible class for show/hide:
.tooltip {
    position: absolute;
    padding: 10px;
    background: rgba(0, 0, 0, 0.8);
    color: white;
    border-radius: 4px;
    pointer-events: none;  /* Prevent mouse interference */
    opacity: 0;
    transition: opacity 0.2s;
    z-index: 1000;
}

.tooltip.visible {
    opacity: 1;  /* Show when .visible class is added */
}
  1. Add event handlers to SVG elements:
svg.selectAll('circle')
    .on('mouseover', function(event, d) {
        d3.select('#tooltip')
            .classed('visible', true)  // Add .visible class
            .html(`<strong>${d.name}</strong><br/>${d.value}`)
            .style('left', (event.pageX + 10) + 'px')
            .style('top', (event.pageY - 10) + 'px');
    })
    .on('mouseout', function() {
        d3.select('#tooltip').classed('visible', false);  // Remove .visible class
    });

Key points:

  • Use opacity: 0 by default (not display: none) for smooth transitions
  • Use .classed('visible', true/false) to toggle visibility
  • pointer-events: none prevents tooltip from blocking mouse events
  • Position tooltip relative to mouse with event.pageX/pageY

Click handlers for selection/highlighting

// Add 'selected' class on click
svg.selectAll('.bar')
    .on('click', function(event, d) {
        // Remove previous selection
        d3.selectAll('.bar').classed('selected', false);
        // Add to clicked element
        d3.select(this).classed('selected', true);
    });

CSS for highlighting:

.bar.selected {
    stroke: #000;
    stroke-width: 3px;
}

Conditional interactivity

Sometimes only certain elements should be interactive:

.on('mouseover', function(event, d) {
    // Example: Don't show tooltip for certain categories
    if (d.category === 'excluded') {
        return;  // Exit early, no tooltip
    }
    // Show tooltip for others
    showTooltip(event, d);
})

Related Skills

View on GitHub
GitHub Stars1.8k
CategoryData
Updated2mo ago
Forks368

Languages

PDDL

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions