Build self-contained interactive HTML dashboards with Chart.js, dropdown filters, and professional styling. Use when creating dashboards, building interactive reports, or generating shareable HTML files with charts and filters that work without a server.
npx skills add https://github.com/w95/awesome-claude-corporate-skills --skill interactive-dashboard-builder
Patterns and techniques for building self-contained HTML/JS dashboards with Chart.js, filters, interactivity, and professional styling.
Every dashboard follows this structure:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Dashboard Title</title>
<script src="https://cdn.jsdelivr.net/npm/[email protected]" integrity="sha384-jb8JQMbMoBUzgWatfe6COACi2ljcDdZQ2OxczGA3bGNeWe+6DChMTBJemed7ZnvJ" crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/[email protected]" integrity="sha384-cVMg8E3QFwTvGCDuK+ET4PD341jF3W8nO1auiXfuZNQkzbUUiBGLsIQUE+b1mxws" crossorigin="anonymous"></script>
<style>
/* Dashboard styles go here */
</style>
</head>
<body>
<div class="dashboard-container">
<header class="dashboard-header">
<h1>Dashboard Title</h1>
<div class="filters">
<!-- Filter controls -->
</div>
</header>
<section class="kpi-row">
<!-- KPI cards -->
</section>
<section class="chart-row">
<!-- Chart containers -->
</section>
<section class="table-section">
<!-- Data table -->
</section>
<footer class="dashboard-footer">
<span>Data as of: <span id="data-date"></span></span>
</footer>
</div>
<script>
// Embedded data
const DATA = [];
// Dashboard logic
class Dashboard {
constructor(data) {
this.rawData = data;
this.filteredData = data;
this.charts = {};
this.init();
}
init() {
this.setupFilters();
this.renderKPIs();
this.renderCharts();
this.renderTable();
}
applyFilters() {
// Filter logic
this.filteredData = this.rawData.filter(row => {
// Apply each active filter
return true; // placeholder
});
this.renderKPIs();
this.updateCharts();
this.renderTable();
}
// ... methods for each section
}
const dashboard = new Dashboard(DATA);
</script>
</body>
</html>
<div class="kpi-card">
<div class="kpi-label">Total Revenue</div>
<div class="kpi-value" id="kpi-revenue">$0</div>
<div class="kpi-change positive" id="kpi-revenue-change">+0%</div>
</div>
function renderKPI(elementId, value, previousValue, format = 'number') {
const el = document.getElementById(elementId);
const changeEl = document.getElementById(elementId + '-change');
// Format the value
el.textContent = formatValue(value, format);
// Calculate and display change
if (previousValue && previousValue !== 0) {
const pctChange = ((value - previousValue) / previousValue) * 100;
const sign = pctChange >= 0 ? '+' : '';
changeEl.textContent = `${sign}${pctChange.toFixed(1)}% vs prior period`;
changeEl.className = `kpi-change ${pctChange >= 0 ? 'positive' : 'negative'}`;
}
}
function formatValue(value, format) {
switch (format) {
case 'currency':
if (value >= 1e6) return `$${(value / 1e6).toFixed(1)}M`;
if (value >= 1e3) return `$${(value / 1e3).toFixed(1)}K`;
return `$${value.toFixed(0)}`;
case 'percent':
return `${value.toFixed(1)}%`;
case 'number':
if (value >= 1e6) return `${(value / 1e6).toFixed(1)}M`;
if (value >= 1e3) return `${(value / 1e3).toFixed(1)}K`;
return value.toLocaleString();
default:
return value.toString();
}
}
<div class="chart-container">
<h3 class="chart-title">Monthly Revenue Trend</h3>
<canvas id="revenue-chart"></canvas>
</div>
function createLineChart(canvasId, labels, datasets) {
const ctx = document.getElementById(canvasId).getContext('2d');
return new Chart(ctx, {
type: 'line',
data: {
labels: labels,
datasets: datasets.map((ds, i) => ({
label: ds.label,
data: ds.data,
borderColor: COLORS[i % COLORS.length],
backgroundColor: COLORS[i % COLORS.length] + '20',
borderWidth: 2,
fill: ds.fill || false,
tension: 0.3,
pointRadius: 3,
pointHoverRadius: 6,
}))
},
options: {
responsive: true,
maintainAspectRatio: false,
interaction: {
mode: 'index',
intersect: false,
},
plugins: {
legend: {
position: 'top',
labels: { usePointStyle: true, padding: 20 }
},
tooltip: {
callbacks: {
label: function(context) {
return `${context.dataset.label}: ${formatValue(context.parsed.y, 'currency')}`;
}
}
}
},
scales: {
x: {
grid: { display: false }
},
y: {
beginAtZero: true,
ticks: {
callback: function(value) {
return formatValue(value, 'currency');
}
}
}
}
}
});
}
function createBarChart(canvasId, labels, data, options = {}) {
const ctx = document.getElementById(canvasId).getContext('2d');
const isHorizontal = options.horizontal || labels.length > 8;
return new Chart(ctx, {
type: 'bar',
data: {
labels: labels,
datasets: [{
label: options.label || 'Value',
data: data,
backgroundColor: options.colors || COLORS.map(c => c + 'CC'),
borderColor: options.colors || COLORS,
borderWidth: 1,
borderRadius: 4,
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
indexAxis: isHorizontal ? 'y' : 'x',
plugins: {
legend: { display: false },
tooltip: {
callbacks: {
label: function(context) {
return formatValue(context.parsed[isHorizontal ? 'x' : 'y'], options.format || 'number');
}
}
}
},
scales: {
x: {
beginAtZero: true,
grid: { display: isHorizontal },
ticks: isHorizontal ? {
callback: function(value) {
return formatValue(value, options.format || 'number');
}
} : {}
},
y: {
beginAtZero: !isHorizontal,
grid: { display: !isHorizontal },
ticks: !isHorizontal ? {
callback: function(value) {
return formatValue(value, options.format || 'number');
}
} : {}
}
}
}
});
}
function createDoughnutChart(canvasId, labels, data) {
const ctx = document.getElementById(canvasId).getContext('2d');
return new Chart(ctx, {
type: 'doughnut',
data: {
labels: labels,
datasets: [{
data: data,
backgroundColor: COLORS.map(c => c + 'CC'),
borderColor: '#ffffff',
borderWidth: 2,
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
cutout: '60%',
plugins: {
legend: {
position: 'right',
labels: { usePointStyle: true, padding: 15 }
},
tooltip: {
callbacks: {
label: function(context) {
const total = context.dataset.data.reduce((a, b) => a + b, 0);
const pct = ((context.parsed / total) * 100).toFixed(1);
return `${context.label}: ${formatValue(context.parsed, 'number')} (${pct}%)`;
}
}
}
}
}
});
}
function updateChart(chart, newLabels, newData) {
chart.data.labels = newLabels;
if (Array.isArray(newData[0])) {
// Multiple datasets
newData.forEach((data, i) => {
chart.data.datasets[i].data = data;
});
} else {
chart.data.datasets[0].data = newData;
}
chart.update('none'); // 'none' disables animation for instant update
}
<div class="filter-group">
<label for="filter-region">Region</label>
<select id="filter-region" onchange="dashboard.applyFilters()">
<option value="all">All Regions</option>
</select>
</div>
function populateFilter(selectId, data, field) {
const select = document.getElementById(selectId);
const values = [...new Set(data.map(d => d[field]))].sort();
// Keep the "All" option, add unique values
values.forEach(val => {
const option = document.createElement('option');
option.value = val;
option.textContent = val;
select.appendChild(option);
});
}
function getFilterValue(selectId) {
const val = document.getElementById(selectId).value;
return val === 'all' ? null : val;
}
<div class="filter-group">
<label>Date Range</label>
<input type="date" id="filter-date-start" onchange="dashboard.applyFilters()">
<span>to</span>
<input type="date" id="filter-date-end" onchange="dashboard.applyFilters()">
</div>
function filterByDateRange(data, dateField, startDate, endDate) {
return data.filter(row => {
const rowDate = new Date(row[dateField]);
if (startDate && rowDate < new Date(startDate)) return false;
if (endDate && rowDate > new Date(endDate)) return false;
return true;
});
}
applyFilters() {
const region = getFilterValue('filter-region');
const category = getFilterValue('filter-category');
const startDate = document.getElementById('filter-date-start').value;
const endDate = document.getElementById('filter-date-end').value;
this.filteredData = this.rawData.filter(row => {
if (region && row.region !== region) return false;
if (category && row.category !== category) return false;
if (startDate && row.date < startDate) return false;
if (endDate && row.date > endDate) return false;
return true;
});
this.renderKPIs();
this.updateCharts();
this.renderTable();
}
function renderTable(containerId, data, columns) {
const container = document.getElementById(containerId);
let sortCol = null;
let sortDir = 'desc';
function render(sortedData) {
let html = '<table class="data-table">';
// Header
html += '<thead><tr>';
columns.forEach(col => {
const arrow = sortCol === col.field
? (sortDir === 'asc' ? ' ▲' : ' ▼')
: '';
html += `<th onclick="sortTable('${col.field}')" style="cursor:pointer">${col.label}${arrow}</th>`;
});
html += '</tr></thead>';
// Body
html += '<tbody>';
sortedData.forEach(row => {
html += '<tr>';
columns.forEach(col => {
const value = col.format ? formatValue(row[col.field], col.format) : row[col.field];
html += `<td>${value}</td>`;
});
html += '</tr>';
});
html += '</tbody></table>';
container.innerHTML = html;
}
window.sortTable = function(field) {
if (sortCol === field) {
sortDir = sortDir === 'asc' ? 'desc' : 'asc';
} else {
sortCol = field;
sortDir = 'desc';
}
const sorted = [...data].sort((a, b) => {
const aVal = a[field], bVal = b[field];
const cmp = aVal < bVal ? -1 : aVal > bVal ? 1 : 0;
return sortDir === 'asc' ? cmp : -cmp;
});
render(sorted);
};
render(data);
}
:root {
/* Background layers */
--bg-primary: #f8f9fa;
--bg-card: #ffffff;
--bg-header: #1a1a2e;
/* Text */
--text-primary: #212529;
--text-secondary: #6c757d;
--text-on-dark: #ffffff;
/* Accent colors for data */
--color-1: #4C72B0;
--color-2: #DD8452;
--color-3: #55A868;
--color-4: #C44E52;
--color-5: #8172B3;
--color-6: #937860;
/* Status colors */
--positive: #28a745;
--negative: #dc3545;
--neutral: #6c757d;
/* Spacing */
--gap: 16px;
--radius: 8px;
}
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
background: var(--bg-primary);
color: var(--text-primary);
line-height: 1.5;
}
.dashboard-container {
max-width: 1400px;
margin: 0 auto;
padding: var(--gap);
}
.dashboard-header {
background: var(--bg-header);
color: var(--text-on-dark);
padding: 20px 24px;
border-radius: var(--radius);
margin-bottom: var(--gap);
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
gap: 12px;
}
.dashboard-header h1 {
font-size: 20px;
font-weight: 600;
}
.kpi-row {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
gap: var(--gap);
margin-bottom: var(--gap);
}
.kpi-card {
background: var(--bg-card);
border-radius: var(--radius);
padding: 20px 24px;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.08);
}
.kpi-label {
font-size: 13px;
color: var(--text-secondary);
text-transform: uppercase;
letter-spacing: 0.5px;
margin-bottom: 4px;
}
.kpi-value {
font-size: 28px;
font-weight: 700;
color: var(--text-primary);
margin-bottom: 4px;
}
.kpi-change {
font-size: 13px;
font-weight: 500;
}
.kpi-change.positive { color: var(--positive); }
.kpi-change.negative { color: var(--negative); }
.chart-row {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(400px, 1fr));
gap: var(--gap);
margin-bottom: var(--gap);
}
.chart-container {
background: var(--bg-card);
border-radius: var(--radius);
padding: 20px 24px;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.08);
}
.chart-container h3 {
font-size: 14px;
font-weight: 600;
color: var(--text-primary);
margin-bottom: 16px;
}
.chart-container canvas {
max-height: 300px;
}
.filters {
display: flex;
gap: 12px;
align-items: center;
flex-wrap: wrap;
}
.filter-group {
display: flex;
align-items: center;
gap: 6px;
}
.filter-group label {
font-size: 12px;
color: rgba(255, 255, 255, 0.7);
}
.filter-group select,
.filter-group input[type="date"] {
padding: 6px 10px;
border: 1px solid rgba(255, 255, 255, 0.2);
border-radius: 4px;
background: rgba(255, 255, 255, 0.1);
color: var(--text-on-dark);
font-size: 13px;
}
.filter-group select option {
background: var(--bg-header);
color: var(--text-on-dark);
}
.table-section {
background: var(--bg-card);
border-radius: var(--radius);
padding: 20px 24px;
box-shadow: 0 1px 3px rgba(0, 0, 0, 0.08);
overflow-x: auto;
}
.data-table {
width: 100%;
border-collapse: collapse;
font-size: 13px;
}
.data-table thead th {
text-align: left;
padding: 10px 12px;
border-bottom: 2px solid #dee2e6;
color: var(--text-secondary);
font-weight: 600;
font-size: 12px;
text-transform: uppercase;
letter-spacing: 0.5px;
white-space: nowrap;
user-select: none;
}
.data-table thead th:hover {
color: var(--text-primary);
background: #f8f9fa;
}
.data-table tbody td {
padding: 10px 12px;
border-bottom: 1px solid #f0f0f0;
}
.data-table tbody tr:hover {
background: #f8f9fa;
}
.data-table tbody tr:last-child td {
border-bottom: none;
}
@media (max-width: 768px) {
.dashboard-header {
flex-direction: column;
align-items: flex-start;
}
.kpi-row {
grid-template-columns: repeat(2, 1fr);
}
.chart-row {
grid-template-columns: 1fr;
}
.filters {
flex-direction: column;
align-items: flex-start;
}
}
@media print {
body { background: white; }
.dashboard-container { max-width: none; }
.filters { display: none; }
.chart-container { break-inside: avoid; }
.kpi-card { border: 1px solid #dee2e6; box-shadow: none; }
}
| Data Size | Approach |
|---|---|
| <1,000 rows | Embed directly in HTML. Full interactivity. |
| 1,000 - 10,000 rows | Embed in HTML. May need to pre-aggregate for charts. |
| 10,000 - 100,000 rows | Pre-aggregate server-side. Embed only aggregated data. |
| >100,000 rows | Not suitable for client-side dashboard. Use a BI tool or paginate. |
Instead of embedding raw data and aggregating in the browser:
// DON'T: embed 50,000 raw rows
const RAW_DATA = [/* 50,000 rows */];
// DO: pre-aggregate before embedding
const CHART_DATA = {
monthly_revenue: [
{ month: '2024-01', revenue: 150000, orders: 1200 },
{ month: '2024-02', revenue: 165000, orders: 1350 },
// ... 12 rows instead of 50,000
],
top_products: [
{ product: 'Widget A', revenue: 45000 },
// ... 10 rows
],
kpis: {
total_revenue: 1980000,
total_orders: 15600,
avg_order_value: 127,
}
};
animation: false in Chart.js optionsChart.update('none') instead of Chart.update() for filter-triggered updatesrequestAnimationFrame for coordinated chart updates// Efficient table pagination
function renderTablePage(data, page, pageSize = 50) {
const start = page * pageSize;
const end = Math.min(start + pageSize, data.length);
const pageData = data.slice(start, end);
// Render only pageData
// Show pagination controls: "Showing 1-50 of 2,340"
}
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Take w95/interactive-dashboard-builder from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.