Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add besoeasy/open-skills --skill d3js-data-visualizationgit clone --depth 1 https://github.com/besoeasy/open-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/besoeasy/open-skills/d3js-data-visualization)<a href="https://agentmods.dev/skills/besoeasy/open-skills/d3js-data-visualization"><img src="https://agentmods.dev/badge/skills/besoeasy/open-skills/d3js-data-visualization.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.02542 |
| Opus 5 | $0.00037 | $0.01271 |
| Sonnet 5 | $0.00015 | $0.00508 |
| Haiku 4.5 | $0.00007 | $0.00254 |
Grade A, and why
d3js-data-visualization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
D3.js Data Visualization
Build sophisticated, interactive data visualizations using d3.js (Data-Driven Documents). D3 binds data to DOM elements and applies data-driven transformations to produce publication-quality, fully customizable visuals.
When to Use This Skill
- Custom charts requiring unique visual encodings or layouts
- Interactive visualizations with pan, zoom, or brush behaviors
- Network/graph visualizations (force-directed, tree, hierarchy, chord diagrams)
- Geographic visualizations with custom projections
- Smooth, choreographed transitions and animations
- Novel chart types not available in standard libraries (Recharts, Chart.js, etc.)
- Fine-grained SVG styling and accessibility control
Consider alternatives for:
- 3D visualizations → use Three.js
- Simple standard charts with minimal customization → use Chart.js or Recharts
Required Tools / Libraries
No backend required. Runs entirely in the browser or Node.js (with jsdom/canvas).
# Install via npm
npm install d3
# Or use CDN in HTML
<script src="https://d3js.org/d3.v7.min.js"></script>
Core Workflow
1. Set Up D3
import * as d3 from 'd3';
2. Standard Chart Structure
Every d3 visualization follows this pattern:
function drawChart(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart');
svg.selectAll("*").remove(); // clear previous render
const width = 800, height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
const innerWidth = width - margin.left - margin.right;
const innerHeight = height - margin.top - margin.bottom;
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
// Define scales
const xScale = d3.scaleLinear().domain([0, d3.max(data, d => d.x)]).range([0, innerWidth]);
const yScale = d3.scaleLinear().domain([0, d3.max(data, d => d.y)]).range([innerHeight, 0]);
// Axes
g.append("g").attr("transform", `translate(0,${innerHeight})`).call(d3.axisBottom(xScale));
g.append("g").call(d3.axisLeft(yScale));
// Data elements
g.selectAll("circle")
.data(data)
.join("circle")
.attr("cx", d => xScale(d.x))
.attr("cy", d => yScale(d.y))
.attr("r", 5)
.attr("fill", "steelblue");
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 289 lines · 75 tokens per session scan A a1af10d60abf
d3js-data-visualization is a skill published in the GitHub repository besoeasy/open-skills (132 stars, last pushed 2d ago), licensed MIT. It adds 75 tokens to every session and 2,542 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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