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D3 Fundamentals

Organization
cxcscmu
d3-fundamentals

Essential D3.js v6 concepts including selections, scales, SVG basics, and data binding for building interactive visualizations

Overview

Publishercxcscmu
RepositorySkillLearnBench
Skill named3-fundamentals
Stars
91
Forks
7
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cxcscmu on GitHub. Read the source before you install it.

Installation

Install the D3 Fundamentals AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cxcscmu/SkillLearnBench/tree/main/skills/b1-one-shot-claude-haiku-4-5/stock-data-visualization/d3-fundamentals
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cxcscmu/SkillLearnBench.git /tmp/SkillLearnBench
mkdir -p .claude/skills
cp -r /tmp/SkillLearnBench/skills/b1-one-shot-claude-haiku-4-5/stock-data-visualization/d3-fundamentals .claude/skills/d3-fundamentals
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable D3 Fundamentals in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads D3 Fundamentals on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so D3 Fundamentals is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

D3.js v6 Fundamentals

Overview

D3.js v6 (Data-Driven Documents) is a JavaScript library for manipulating documents based on data. Essential for creating scalable vector graphics (SVG) visualizations.

Core Concepts

1. Selections

Select DOM elements and bind data to them:

javascript
// Select elements
d3.select("body")                    // single element
d3.selectAll(".dots")                // multiple elements

// Data binding
d3.selectAll("circle")
  .data(dataArray, d => d.id)       // bind data with key function
  .join(                             // handle enter/update/exit
    enter => enter.append("circle"),
    update => update,
    exit => exit.remove()
  )

2. Scales

Map data values to visual dimensions:

javascript
// Linear scale (continuous input → continuous output)
const xScale = d3.scaleLinear()
  .domain([0, 100])           // input range
  .range([0, width]);         // output range

// Other common scales:
const colorScale = d3.scaleOrdinal()
  .domain(["A", "B", "C"])
  .range(["red", "blue", "green"]);

const sizeScale = d3.scaleSqrt()   // square root scale (better for areas)
  .domain([0, max])
  .range([0, 100]);

3. SVG Elements

Common SVG elements for visualization:

javascript
// Circle (bubble chart)
g.append("circle")
  .attr("cx", d => xScale(d.x))
  .attr("cy", d => yScale(d.y))
  .attr("r", d => rScale(d.value))
  .attr("fill", d => colorScale(d.category));

// Text (labels)
g.append("text")
  .text(d => d.label)
  .attr("text-anchor", "middle")
  .attr("dominant-baseline", "central");

// Rect (table cells, bars)
g.append("rect")
  .attr("width", width)
  .attr("height", height);

4. Margins Convention

Standard pattern for creating SVG containers:

javascript
const margin = {top: 20, right: 20, bottom: 20, left: 20};
const width = 800 - margin.left - margin.right;
const height = 600 - margin.top - margin.bottom;

const svg = d3.select("body")
  .append("svg")
  .attr("width", width + margin.left + margin.right)
  .attr("height", height + margin.top + margin.bottom)
  .append("g")
  .attr("transform", `translate(${margin.left},${margin.top})`);

5. Transitions

Smooth animations:

javascript
d3.selectAll("circle")
  .transition()
  .duration(750)
  .attr("cx", d => xScale(d.newX))
  .attr("r", d => rScale(d.newValue));

Loading Data

CSV with D3

javascript
d3.csv("data.csv").then(data => {
  // Data is array of objects
  // Numeric strings are parsed as strings by default
  data.forEach(d => {
    d.value = +d.value;  // convert to number
    d.date = new Date(d.date);  // convert to date
  });
});

Module Imports

D3.js v6 uses ES6 modules. For standalone HTML, use the bundled version:

html
<script src="https://d3js.org/d3.v6.min.js"></script>

Or import specific modules:

javascript
import * as d3 from "https://cdn.jsdelivr.net/npm/d3@6/+esm";

Frequently asked questions

What does the D3 Fundamentals AI skill do?

Essential D3.js v6 concepts including selections, scales, SVG basics, and data binding for building interactive visualizations

Why use D3 Fundamentals on TypingMind?

Because you install it once and use it with any model. D3 Fundamentals is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install D3 Fundamentals in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cxcscmu/SkillLearnBench/tree/main/skills/b1-one-shot-claude-haiku-4-5/stock-data-visualization/d3-fundamentals. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use D3 Fundamentals?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with D3 Fundamentals?

As many as you like. As long as a model supports skills, you can use D3 Fundamentals with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the D3 Fundamentals AI skill free?

Yes. It is published on GitHub by cxcscmu under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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