Build Dashboard Skill for Claude

Build an interactive HTML dashboard with charts, filters, and tables. Use when creating an executive overview with KPI cards, turning query results into a shareable self-contained report, building a team monitoring snapshot, or needing multiple charts with filters in one browser-openable file.

6k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

23273

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/anthropics/knowledge-work-plugins --skill build-dashboard

The instruction itself

38 sections, as written by the author

/build-dashboard - Build Interactive Dashboards

> 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/[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>

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

<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: false in Chart.js options
Use Chart.update('none') instead of Chart.update() for filter-triggered updates

DOM Performance

Limit data tables to 100-200 visible rows. Add pagination for more.
Use requestAnimationFrame for coordinated chart updates
Avoid rebuilding the entire DOM on filter change -- update only changed elements

// 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"
}

Examples

/build-dashboard Monthly sales dashboard with revenue trend, top products, and regional breakdown. Data is in the orders table.

/build-dashboard Here's our support ticket data [pastes CSV]. Build a dashboard showing volume by priority, response time trends, and resolution rates.

/build-dashboard Create a template executive dashboard for a SaaS company showing MRR, churn, new customers, and NPS. Use sample data.

Tips

Dashboards are fully self-contained HTML files -- share them with anyone by sending the file
For real-time dashboards, consider connecting to a BI tool instead. These dashboards are point-in-time snapshots
Request "dark mode" or "presentation mode" for different styling
You can request a specific color scheme to match your brand

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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.

16k tokens

How to use it

Copy the folder

Take anthropics/build-dashboard from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.

Build Dashboard Skill for Claude

Install

The instruction itself

/build-dashboard - Build Interactive Dashboards

Usage

Workflow

1. Understand the Dashboard Requirements

2. Gather the Data

3. Design the Dashboard Layout

4. Build the HTML Dashboard

5. Implement Chart Types

6. Add Interactivity

7. Save and Open

Base Template

KPI Card Pattern

Chart.js Integration

Chart Container Pattern

Line Chart

Bar Chart

Doughnut Chart

Updating Charts on Filter Change

Filter and Interactivity Implementation

Dropdown Filter

Date Range Filter

Combined Filter Logic

Sortable Table

CSS Styling for Dashboards

Color System

Layout

KPI Cards

Chart Containers

Filters

Data Table

Responsive Design

Performance Considerations for Large Datasets

Data Size Guidelines

Pre-Aggregation Pattern

Chart Performance

DOM Performance

Examples

Tips

Other skills for the same job

How to use it