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Build Dashboard

OrganizationPopular
anthropics
build-dashboard

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.

Overview

Publisheranthropics
Repositoryknowledge-work-plugins
Skill namebuild-dashboard
Stars
24.9K
Forks
3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by anthropics on GitHub. Read the source before you install it.

Installation

Install the Build Dashboard AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anthropics/knowledge-work-plugins.git /tmp/knowledge-work-plugins
mkdir -p .claude/skills
cp -r /tmp/knowledge-work-plugins/data/skills/build-dashboard .claude/skills/build-dashboard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Build Dashboard in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Build Dashboard on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Build Dashboard is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/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:

  1. Query the necessary data
  2. Embed the results as JSON within the HTML file

If data is pasted or uploaded:

  1. Parse and clean the data
  2. Embed as JSON in the dashboard

If working from a description without data:

  1. Create a realistic sample dataset matching the described schema
  2. Note in the dashboard that it uses sample data
  3. 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

  1. Save the dashboard as an HTML file with a descriptive name (e.g., sales_dashboard.html)
  2. Open it in the user's default browser
  3. Confirm it renders correctly
  4. Provide instructions for updating data or customizing

Base Template

Every dashboard follows this structure:

html
<!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

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>
javascript
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

html
<div class="chart-container">
    <h3 class="chart-title">Monthly Revenue Trend</h3>
    <canvas id="revenue-chart"></canvas>
</div>

Line Chart

javascript
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

javascript
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

javascript
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

javascript
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

html
<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>
javascript
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

html
<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>
javascript
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

javascript
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

javascript
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

css
: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

css
* {
    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

css
.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

css
.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

css
.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

css
.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

css
@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 SizeApproach
<1,000 rowsEmbed directly in HTML. Full interactivity.
1,000 - 10,000 rowsEmbed in HTML. May need to pre-aggregate for charts.
10,000 - 100,000 rowsPre-aggregate server-side. Embed only aggregated data.
>100,000 rowsNot suitable for client-side dashboard. Use a BI tool or paginate.

Pre-Aggregation Pattern

Instead of embedding raw data and aggregating in the browser:

javascript
// 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
javascript
// 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

Frequently asked questions

What does the Build Dashboard AI skill do?

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.

Why use Build Dashboard on TypingMind?

Because you install it once and use it with any model. Build Dashboard is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Build Dashboard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anthropics/knowledge-work-plugins/tree/main/data/skills/build-dashboard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Build Dashboard?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Build Dashboard?

As many as you like. As long as a model supports skills, you can use Build Dashboard with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Build Dashboard AI skill free?

Yes. It is published on GitHub by anthropics under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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