/build-dashboard - Build Interactive Dashboards
SkillWeb & browsingBuild an interactive dashboard with charts, filters, and tables as a single file that opens in a browser. Once added, your AI can turn query results into a shareable, self-contained report, an executive overview with KPI cards, or a team monitoring snapshot.
Available today. Use it from your connected AI after setup.
No other account needed.
Add the skill, then ask your AI to build a dashboard from your data or query results. Open the HTML file it produces in your browser to view and share it.
Then ask your AI: use the /build-dashboard - Build Interactive Dashboards skill
What your AI can do with it
- Build an executive overview with KPI cards
- Turn query results into a shareable, self-contained report
- Create a team monitoring snapshot
- Combine multiple charts with filters in one file
- Produce tables and charts that open directly in a browser
What this skill tells your AI
The instructions your AI receives, as published by charlieviettq/awesome-agent-skill in .claude/skills/build-dashboard/SKILL.md and read by ahel’s review.
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Build a self-contained interactive HTML dashboard with charts, filters, tables, and professional styling. Opens directly in a browser -- no server or dependencies required.
Usage
/build-dashboard <description of dashboard> [data source]
Workflow
1. Understand the Dashboard Requirements
Determine:
- Purpose: Executive overview, operational monitoring, deep-dive analysis, team reporting
- Audience: Who will use this dashboard?
- Key metrics: What numbers matter most?
- Dimensions: What should users be able to filter or slice by?
- Data source: Live query, pasted data, CSV file, or sample data
2. Gather the Data
If data warehouse is connected:
- Query the necessary data
- Embed the results as JSON within the HTML file
If data is pasted or uploaded:
- Parse and clean the data
- Embed as JSON in the dashboard
If working from a description without data:
- Create a realistic sample dataset matching the described schema
- Note in the dashboard that it uses sample data
- Provide instructions for swapping in real data
3. Design the Dashboard Layout
Follow a standard dashboard layout pattern:
┌──────────────────────────────────────────────────┐
│ Dashboard Title [Filters ▼] │
├────────────┬────────────┬────────────┬───────────┤
│ KPI Card │ KPI Card │ KPI Card │ KPI Card │
├────────────┴────────────┼────────────┴───────────┤
│ │ │
│ Primary Chart │ Secondary Chart │
│ (largest area) │ │
│ │ │
├─────────────────────────┴────────────────────────┤
│ │
│ Detail Table (sortable, scrollable) │
│ │
└──────────────────────────────────────────────────┘
Adapt the layout to the content:
- 2-4 KPI cards at the top for headline numbers
- 1-3 charts in the middle section for trends and breakdowns
- Optional detail table at the bottom for drill-down data
- Filters in the header or sidebar depending on complexity
4. Build the HTML Dashboard
Generate a single self-contained HTML file using the base template below. The file includes:
Structure (HTML):
- Semantic HTML5 layout
- Responsive grid using CSS Grid or Flexbox
- Filter controls (dropdowns, date pickers, toggles)
- KPI cards with values and labels
- Chart containers
- Data table with sortable headers
Styling (CSS):
- Professional color scheme (clean whites, grays, with accent colors for data)
- Card-based layout with subtle shadows
- Consistent typography (system fonts for fast loading)
- Responsive design that works on different screen sizes
- Print-friendly styles
Interactivity (JavaScript):
- Chart.js for interactive charts (included via CDN)
- Filter dropdowns that update all charts and tables simultaneously
- Sortable table columns
- Hover tooltips on charts
- Number formatting (commas, currency, percentages)
Data (embedded JSON):
- All data embedded directly in the HTML as JavaScript variables
- No external data fetches required
- Dashboard works completely offline
5. Implement Chart Types
Use Chart.js for all charts. Common dashboard chart patterns:
- Line chart: Time series trends
- Bar chart: Category comparisons
- Doughnut chart: Composition (when <6 categories)
- Stacked bar: Composition over time
- Mixed (bar + line): Volume with rate overlay
Use the Chart.js integration patterns below for each chart type.
6. Add Interactivity
Use the filter and interactivity implementation patterns below for dropdown filters, date range filters, combined filter logic, sortable tables, and chart updates.
7. Save and Open
- Save the dashboard as an HTML file with a descriptive name (e.g.,
sales_dashboard.html) - Open it in the user's default browser
- Confirm it renders correctly
- Provide instructions for updating data or customizing
Base Template
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/chart.js@4.5.1" integrity="sha384-jb8JQMbMoBUzgWatfe6COACi2ljcDdZQ2OxczGA3bGNeWe+6DChMTBJemed7ZnvJ" crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns@3.0.0" 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>
KPI Card Pattern
<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 `${(value / 1e3).toFixed(1)}K`;
return value.toLocaleString();
default:
return value.toString();
}
}
Chart.js Integration
Chart Container Pattern
<div class="chart-container">
<h3 class="chart-title">Monthly Revenue Trend</h3>
<canvas id="revenue-chart"></canvas>
</div>
Line Chart
function createLineChart(canvasId, labels, datasets) {
const ctx = document.getElementById(canvasId).getContext('2d');
return new Chart(ctx, {
type: 'line',
data: {
labels: labels,
datasets: datasets.map((ds, i) => ({
label: ds.label,
data: ds.data,
borderColor: COLORS[i % COLORS.length],
backgroundColor: COLORS[i % COLORS.length] + '20',
borderWidth: 2,
fill: ds.fill || false,
tension: 0.3,
pointRadius: 3,
pointHoverRadius: 6,
}))
},
options: {
responsive: true,
maintainAspectRatio: false,
interaction: {
mode: 'index',
intersect: false,
},
plugins: {
legend: {
position: 'top',
labels: { usePointStyle: true, padding: 20 }
},
tooltip: {
callbacks: {
label: function(context) {
return `${context.dataset.label}: ${formatValue(context.parsed.y, 'currency')}`;
}
}
}
},
scales: {
x: {
grid: { display: false }
},
y: {
beginAtZero: true,
ticks: {
callback: function(value) {
return formatValue(value, 'currency');
}
}
}
}
}
});
}
Bar Chart
function createBarChart(canvasId, labels, data, options = {}) {
const ctx = document.getElementById(canvasId).getContext('2d');
const isHorizontal = options.horizontal || labels.length > 8;
return new Chart(ctx, {
type: 'bar',
data: {
labels: labels,
datasets: [{
label: options.label || 'Value',
data: data,
backgroundColor: options.colors || COLORS.map(c => c + 'CC'),
borderColor: options.colors || COLORS,
borderWidth: 1,
borderRadius: 4,
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
indexAxis: isHorizontal ? 'y' : 'x',
plugins: {
legend: { display: false },
tooltip: {
callbacks: {
label: function(context) {
return formatValue(context.parsed[isHorizontal ? 'x' : 'y'], options.format || 'number');
}
}
}
},
scales: {
x: {
beginAtZero: true,
grid: { display: isHorizontal },
ticks: isHorizontal ? {
callback: function(value) {
return formatValue(value, options.format || 'number');
}
} : {}
},
y: {
beginAtZero: !isHorizontal,
grid: { display: !isHorizontal },
ticks: !isHorizontal ? {
callback: function(value) {
return formatValue(value, options.format || 'number');
}
} : {}
}
}
}
});
}
Doughnut Chart
function createDoughnutChart(canvasId, labels, data) {
const ctx = document.getElementById(canvasId).getContext('2d');
return new Chart(ctx, {
type: 'doughnut',
data: {
labels: labels,
datasets: [{
data: data,
backgroundColor: COLORS.map(c => c + 'CC'),
borderColor: '#ffffff',
borderWidth: 2,
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
cutout: '60%',
plugins: {
legend: {
position: 'right',
labels: { usePointStyle: true, padding: 15 }
},
tooltip: {
callbacks: {
label: function(context) {
const total = context.dataset.data.reduce((a, b) => a + b, 0);
const pct = ((context.parsed / total) * 100).toFixed(1);
return `${context.label}: ${formatValue(context.parsed, 'number')} (${pct}%)`;
}
}
}
}
}
});
}
Updating Charts on Filter Change
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
}
Filter and Interactivity Implementation
Dropdown Filter
<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;
}
Date Range Filter
<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;
});
}
Combined Filter Logic
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();
}
Sortable Table
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);
}
CSS Styling for Dashboards
Color System
: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;
}
Layout
* {
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 Cards
.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 Containers
.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
.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);
}
Data Table
.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;
}
Responsive Design
@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; }
}
Performance Considerations for Large Datasets
Data Size Guidelines
| 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. |
Pre-Aggregation Pattern
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,
}
};
Chart Performance
- Limit line charts to <500 data points per series (downsample if needed)
- Limit bar charts to <50 categories
- For scatter plots, cap at 1,000 points (use sampling for larger datasets)
- Disable animations for dashboards with many charts:
animation: falsein Chart.js options - Use
Chart.update('none')instead ofChart.update()for filter-triggered updates
DOM Performance
- Limit data tables to 100-200 visible rows. Add pagination for more.
- Use
requestAnimationFramefor coordinated chart updates - Avoid rebuilding the entire DOM on filter change -- update only changed elements
Shortened here. Read the whole file on GitHub.
Signals
- GitHub stars
- 26
- Forks
- 9
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
build-dashboard- Source
- github.com/charlieviettq/awesome-agent-skill