d3-viz▌
davila7/claude-code-templates · updated Apr 8, 2026
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This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js. D3.js (Data-Driven Documents) excels at binding data to DOM elements and applying data-driven transformations to create custom, publication-quality visualisations with precise control over every visual element. The techniques work across any JavaScript environment, including vanilla JavaScript, React, Vue, Svelte, and other frameworks.
D3.js Visualisation
Overview
This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js. D3.js (Data-Driven Documents) excels at binding data to DOM elements and applying data-driven transformations to create custom, publication-quality visualisations with precise control over every visual element. The techniques work across any JavaScript environment, including vanilla JavaScript, React, Vue, Svelte, and other frameworks.
When to use d3.js
Use d3.js for:
- Custom visualisations requiring unique visual encodings or layouts
- Interactive explorations with complex pan, zoom, or brush behaviours
- Network/graph visualisations (force-directed layouts, tree diagrams, hierarchies, chord diagrams)
- Geographic visualisations with custom projections
- Visualisations requiring smooth, choreographed transitions
- Publication-quality graphics with fine-grained styling control
- Novel chart types not available in standard libraries
Consider alternatives for:
- 3D visualisations - use Three.js instead
Core workflow
1. Set up d3.js
Import d3 at the top of your script:
import * as d3 from 'd3';
Or use the CDN version (7.x):
<script src="https://d3js.org/d3.v7.min.js"></script>
All modules (scales, axes, shapes, transitions, etc.) are accessible through the d3 namespace.
2. Choose the integration pattern
Pattern A: Direct DOM manipulation (recommended for most cases) Use d3 to select DOM elements and manipulate them imperatively. This works in any JavaScript environment:
function drawChart(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart'); // Select by ID, class, or DOM element
// Clear previous content
svg.selectAll("*").remove();
// Set up dimensions
const width = 800;
const height = 400;
const margin = { top: 20, right: 30, bottom: 40, left: 50 };
// Create scales, axes, and draw visualisation
// ... d3 code here ...
}
// Call when data changes
drawChart(myData);
Pattern B: Declarative rendering (for frameworks with templating) Use d3 for data calculations (scales, layouts) but render elements via your framework:
function getChartElements(data) {
const xScale = d3.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([0, 400]);
return data.map((d, i) => ({
x: 50,
y: i * 30,
width: xScale(d.value),
height: 25
}));
}
// In React: {getChartElements(data).map((d, i) => <rect key={i} {...d} fill="steelblue" />)}
// In Vue: v-for directive over the returned array
// In vanilla JS: Create elements manually from the returned data
Use Pattern A for complex visualisations with transitions, interactions, or when leveraging d3's full capabilities. Use Pattern B for simpler visualisations or when your framework prefers declarative rendering.
3. Structure the visualisation code
Follow this standard structure in your drawing function:
function drawVisualization(data) {
if (!data || data.length === 0) return;
const svg = d3.select('#chart'); // Or pass a selector/element
svg.selectAll("*").remove(); // Clear previous render
// 1. Define dimensions
const width = 800;
const 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;
// 2. Create main group with margins
const g = svg.append("g")
.attr("transform", `translate(${margin.left},${margin.top})`);
// 3. Create 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]); // Note: inverted for SVG coordinates
// 4. Create and append axes
const xAxis = d3.axisBottom(xScale);
const yAxis = d3.axisLeft(yScale);
g.append("g")
.attr("transform", `translate(0,${innerHeight})`)
.call(xAxis);
g.append("g")
.call(yAxis);
// 5. Bind data and create visual elements
g.selectAll("circle")
.data(data)
.how to use d3-vizHow to use d3-viz on Cursor
AI-first code editor with Composer
1Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add d3-viz
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/davila7/claude-code-templates --skill d3-vizThe skills CLI fetches d3-viz from GitHub repository davila7/claude-code-templates and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/d3-vizReload or restart Cursor to activate d3-viz. Access the skill through slash commands (e.g., /d3-viz) or your agent's skill management interface.
⚠Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
List & Monetize Your Skill
Submit your Claude Code skill and start earning
GET_STARTED →Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
✓Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
✓Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
✓Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
✓Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.5★★★★★74 reviews- ★★★★★Sofia Patel· Dec 28, 2024
We added d3-viz from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Amelia White· Dec 20, 2024
Solid pick for teams standardizing on skills: d3-viz is focused, and the summary matches what you get after install.
- ★★★★★Pratham Ware· Dec 12, 2024
Useful defaults in d3-viz — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chaitanya Patil· Dec 4, 2024
d3-viz fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Amelia Jackson· Dec 4, 2024
d3-viz is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Piyush G· Nov 23, 2024
Registry listing for d3-viz matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Amelia Tandon· Nov 23, 2024
Solid pick for teams standardizing on skills: d3-viz is focused, and the summary matches what you get after install.
- ★★★★★Alexander White· Nov 23, 2024
Useful defaults in d3-viz — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ava Farah· Nov 19, 2024
d3-viz reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Arya Harris· Nov 11, 2024
d3-viz is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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