Skip to content
Agentmart
Submit a tool

d3-visualization

Build deterministic, verifiable data visualizations with D3.js (v6).

Skill by benchflow-ai

IndexedApache-2.0★ 1,870
Write a review

Chalk Labs

Need help deploying d3-visualization?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/benchflow-ai-d3-visualization

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

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.

Use cases: design, frontend, data

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Node.js package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/d3-visualization

What's inside

Skill 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.
License
Apache-2.0
Instructions
185 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (5)

  • SKILL.md
  • bubble_chart_example.js · scripts/
  • check_tooltip.js · scripts/
  • interactive_table_example.js · scripts/
  • tooltip_handler.js · scripts/

SKILL.md (first lines)

# 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:
```html
<div id="tooltip" class="tooltip"></div>
```

2. **Style with CSS** using `.visible` class for show/hide:
```css
.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;

From benchflow-ai/skillsbench, Apache-2.0.

More from benchflow-ai/skillsbench

Signals

Stars
1,870
Forks
372
Open issues
50
Last commit (this folder)
Jun 5, 2026 (4 months ago)
Last release
Jun 14, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from benchflow-ai

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get d3-visualization running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying d3-visualization?

CallGet help
Cite this page

d3-visualization skill. Agent Mart. https://agentmart.dev/skills/benchflow-ai-d3-visualization (last updated 2026-10-24)