creating-dashboards▌
ancoleman/ai-design-components · updated Apr 8, 2026
This skill enables the creation of sophisticated dashboard interfaces that aggregate and present data through coordinated widgets including KPI cards, charts, tables, and filters. Dashboards serve as centralized command centers for data-driven decision making, combining multiple component types from other skills (data-viz, tables, design-tokens) into unified analytics experiences with real-time updates, responsive layouts, and interactive filtering.
Creating Dashboards
Purpose
This skill enables the creation of sophisticated dashboard interfaces that aggregate and present data through coordinated widgets including KPI cards, charts, tables, and filters. Dashboards serve as centralized command centers for data-driven decision making, combining multiple component types from other skills (data-viz, tables, design-tokens) into unified analytics experiences with real-time updates, responsive layouts, and interactive filtering.
When to Use
Activate this skill when:
- Building business intelligence or analytics dashboards
- Creating executive reporting interfaces
- Implementing real-time monitoring systems
- Designing KPI displays with metrics and trends
- Developing customizable widget-based layouts
- Coordinating filters across multiple data displays
- Building responsive data-heavy interfaces
- Implementing drag-and-drop dashboard editors
- Creating template-based analytics systems
- Designing multi-tenant SaaS dashboards
Core Dashboard Elements
KPI Card Anatomy
┌────────────────────────────┐
│ Revenue (This Month) │ ← Label with time period
│ │
│ $1,245,832 │ ← Big number (primary metric)
│ ↑ 15.3% vs last month │ ← Trend indicator with comparison
│ ▂▃▅▆▇█ (sparkline) │ ← Mini visualization
└────────────────────────────┘
Widget Container Structure
- Title bar with widget name and actions
- Loading state (skeleton or spinner)
- Error boundary with retry option
- Resize handles for adjustable layouts
- Settings menu (export, configure, refresh)
Dashboard Layout Types
Fixed Layout: Designer-defined placement, consistent across users Customizable Grid: User drag-and-drop, resizable widgets, saved layouts Template-Based: Pre-built patterns, industry-specific starting points
Global Dashboard Controls
- Date range picker (affects all widgets)
- Filter panel (coordinated across widgets)
- Refresh controls (manual/auto-refresh)
- Export actions (PDF, image, data)
- Theme switcher (light/dark/custom)
Implementation Approach
1. Choose Dashboard Architecture
For Quick Analytics Dashboard → Use Tremor Pre-built KPI cards, charts, and tables with minimal code:
npm install @tremor/react
For Customizable Dashboard → Use react-grid-layout Drag-and-drop, resizable widgets, user-defined layouts:
npm install react-grid-layout
2. Set Up Global State Management
Implement filter context for cross-widget coordination:
// Dashboard context for shared filters
const DashboardContext = createContext({
filters: { dateRange: null, categories: [] },
setFilters: () => {},
refreshInterval: 30000
});
// Wrap dashboard with provider
<DashboardContext.Provider value={dashboardState}>
<FilterPanel />
<WidgetGrid />
</DashboardContext.Provider>
3. Implement Data Fetching Strategy
Parallel Loading: Fetch all widget data simultaneously Lazy Loading: Load visible widgets first, others on scroll Cached Updates: Serve from cache while fetching fresh data
4. Configure Real-Time Updates
Server-Sent Events (Recommended for Dashboards):
const eventSource = new EventSource('/api/dashboard/stream');
eventSource.onmessage = (event) => {
const update = JSON.parse(event.data);
updateWidget(update.widgetId, update.data);
};
5. Apply Responsive Design
Define breakpoints for different screen sizes:
- Desktop (>1200px): Multi-column grid
- Tablet (768-1200px): 2-column layout
- Mobile (<768px): Single column stack
Quick Start with Tremor
Basic KPI Dashboard
import { Card, Grid, Metric, Text, BadgeDelta, AreaChart } from '@tremor/react';
function QuickDashboard({ data }) {
return (
<Grid numItems={1} numItemsSm={2} numItemsLg={4} className="gap-4">
{/* KPI Cards */}
<Card>
<Text>Total Revenue</Text>
<Metric>$45,231.89</Metric>
<BadgeDelta deltaType="increase">+12.5%</BadgeDelta>
</Card>
<Card>
<Text>Active Users</Text>
<Metric>1,234</Metric>
<BadgeDelta deltaType="decrease">-2.3%</BadgeDelta>
</Card>
{/* Chart Widget */}
<Card className="lg:col-span-2">
<Text>Revenue Trend</Text>
<AreaChart
data={data.revenue}
index="date"
categories={["revenue"]}
valueFormatter={(value) => `$${value.toLocaleString()}`}
/>
</Card>
</Grid>
);
}
For complete implementation, see examples/tremor-dashboard.tsx.
Customizable Dashboard Implementation
Drag-and-Drop Grid Layout
import { Responsive, WidthProvider } from 'react-grid-layout';
import 'react-grid-layout/css/styles.css';
const ResponsiveGridLayout = WidthProvider(Responsive);
function CustomizableDashboard() {
const [layouts, setLayouts] = useState(getStoredLayouts());
return (
<ResponsiveGridLayout
layouts={layouts}
breakpoints={{ lg: 1200, md: 996, sm: 768 }}
cols={{ lg: 12, md: 10, sm: 6 }}
rowHeight={60}
onLayoutChange={(layout, layouts) => {
setLayouts(layouts);
localStorage.setItem('dashboardLayout', JSON.stringify(layouts));
}}
draggableHandle=".widget-header"
>
<div key="kpi1">
<KPIWidget data={kpiData} />
</div>
<div key="chart1">
<ChartWidget data={chartData} />
</div>
<div key="table1">
<TableWidget data={tableData} />
</div>
</ResponsiveGridLayout>
);
}
For full example with widget catalog, see examples/customizable-dashboard.tsx.
Real-Time Data Patterns
Server-Sent Events (Recommended)
Best for unidirectional updates from server to dashboard:
function useSSEUpdates(endpoint) {
useEffect(() => {
const eventSource = new EventSource(endpoint);
eventSource.onmessage = (event) => {
const update = JSON.parse(event.data);
// Update specific widget or all widgets
dispatch({ type: 'UPDATE_WIDGET', payload: update });
};
return () => eventSource.close();
}, [endpoint]);
}
WebSocket (For Bidirectional)
Use when dashboard needs to send commands back to server:
const ws = new WebSocket('ws://localhost:3000/dashboard');
ws.onmessage = (event) => {
const data = JSON.parse(event.data);
updateDashboard(data);
};
// Send filter changes to server
ws.send(JSON.stringify({ type: 'FILTER_CHANGE', filters }));
Smart Polling Fallback
For environments without WebSocket/SSE support:
function useSmartPolling(fetchData, interval = 30000) {
const [isPaused, setIsPaused] = useState(false);
useEffect(() => {
if (isPaused || document.hidden) return;
const timer = setInterval(fetchData, interval);
return () => clearInterval(timer);
}, [isPaused, interval]);
// Pause when tab inactive
useEffect(() => {
const handleVisibilityChange = () => {
setIsPaused(document.hidden);
};
document.addEventListener('visibilitychange', handleVisibilityChange);
return () => document.removeEventListener('visibilitychange', handleVisibilityChange);
}, []);
}
For detailed patterns including error handling and reconnection, see references/real-time-updates.md.
Performance Optimization
Lazy Loading Strategy
function DashboardGrid({ widgets }) {
const [visibleWidgets, setVisibleWidgets] = useState(new Set());
return widgets.map(widget => (
<LazyLoad
key={widget.id}
height={widget.height}
offset={100}
once
placeholder={<WidgetSkeleton />}
>
<Widget {...widget} />
</LazyLoad>
));
}
Parallel Data Fetching
// Fetch all widget data simultaneously
const loadDashboard = async () => {
const [kpis, charts, tables] = await Promise.all([
fetchKPIs(),
fetchChartData(),
fetchTableData()
]);
return { kpis, charts, tables };
};
Widget-Level Caching
function CachedWidget({ id, fetcher, ttl = 60000 }) {
const cache = useRef({ data: null, timestamp: 0 });
const getData = async () => {
const now = Date.now();
if (cache.current.data && now - cache.current.timestamp < ttl) {
return cache.current.data;
}
const fresh = await fetcher();
cache.current = { data: fresh, timestamp: now };
return fresh;
};
// Use cached data while fetching fresh
return <Widget data={cache.current.data} onRefresh={getData} />;
}
To analyze and optimize dashboard performance, run:
python scripts/optimize-dashboard-performance.py --analyze dashboard-config.json
Cross-Skill Integration
Using Data Visualization Components
Reference the data-viz skill for chart widgets:
// Use charts from data-viz skill
import { createChart } from '../data-viz/chart-factory';
const revenueChart = createChart('area', {
data: revenueData,
xAxis: 'date',
yAxis: 'revenue',
theme: dashboardTheme
});
Integrating Data Tables
Reference the tables skill for data grids:
// Use advanced tables from tables skill
import { DataGrid } from '../tables/data-grid';
<DataGrid
data={transactions}
columns={columnDefs}
pagination={true}
sorting={true}
filtering={true}
/>
Applying Design Tokens
Use the design-tokens skill for consistent theming:
// Dashboard-specific tokens from design-tokens skill
const dashboardTokens = {
'--dashboard-bg': 'var(--color-bg-secondary)',
'--widget-bg': 'var(--color-white)',
'--widget-shadow': 'var(--shadow-lg)',
'--kpi-value-size': 'var(--font-size-4xl)',
'--kpi-trend-positive': 'var(--color-success)',
'--kpi-trend-negative': 'var(--color-error)'
};
Filter Input Components
Optionally use the forms skill for filter controls:
// Advanced filter inputs from forms skill
import { DateRangePicker, MultiSelect } from '../forms/inputs';
<FilterPanel>
<DateRangePicker onChange={handleDateChange} />
<MultiSelect options={categories} onChange={handleCategoryFilter} />
</FilterPanel>
Library Selection Guide
Choose Tremor When:
- Need to build dashboards quickly
- Want pre-styled, professional components
- Using Tailwind CSS in your project
- Building standard analytics interfaces
- Limited customization requirements
Choose react-grid-layout When:
- Users need to customize layouts
- Drag-and-drop is required
- Different users need different views
- Building a dashboard builder tool
- Maximum flexibility is priority
Combine Both When:
- Use Tremor for widget contents (KPIs, charts)
- Use react-grid-layout for layout management
- Get best of both worlds
Bundled Resources
Scripts (Token-Free Execution)
scripts/generate-dashboard-layout.py- Generate responsive grid configurationsscripts/calculate-kpi-metrics.py- Calculate trends, comparisons, sparklinesscripts/validate-widget-config.py- Validate widget and filter configurationsscripts/optimize-dashboard-performance.py- Analyze and optimize performancescripts/export-dashboard.py- Export dashboards to various formats
Run scripts directly without loading into context:
python scripts/calculate-kpi-metrics.py --data metrics.json --period monthly
References (Detailed Patterns)
references/kpi-card-patterns.md- KPI card design patterns and variationsreferences/layout-strategies.md- Grid systems and responsive approachesreferences/real-time-updates.md- WebSocket, SSE, and polling implementationsreferences/filter-coordination.md- Cross-widget filter synchronizationreferences/performance-optimization.md- Advanced optimization techniquesreferences/library-guide.md- Detailed Tremor and react-grid-layout guides
Examples (Complete Implementations)
examples/sales-dashboard.tsx- Full sales analytics dashboardexamples/monitoring-dashboard.tsx- Real-time monitoring with alertsexamples/executive-dashboard.tsx- Polished executive reportingexamples/customizable-dashboard.tsx- Drag-and-drop with persistenceexamples/tremor-dashboard.tsx- Quick Tremor implementationexamples/filter-context.tsx- Global filter coordination
Assets (Templates & Configurations)
assets/dashboard-templates.json- Pre-built dashboard layoutsassets/widget-library.json- Widget catalog and configurationsassets/grid-layouts.json- Responsive grid configurationsassets/kpi-formats.json- Number formatting rulesassets/theme-tokens.json- Dashboard-specific design tokens
Dashboard Creation Workflow
- Define Requirements: Fixed or customizable? Real-time or static?
- Choose Libraries: Tremor for quick, react-grid-layout for flexible
- Set Up Structure: Global state, filter context, layout system
- Build Widgets: KPI cards, charts (data-viz), tables (tables skill)
- Implement Data Flow: Fetching strategy, caching, updates
- Add Interactivity: Filters, drill-downs, exports
- Optimize Performance: Lazy loading, parallel fetching, caching
- Apply Theming: Use design-tokens for consistent styling
- Test Responsiveness: Desktop, tablet, mobile breakpoints
- Deploy & Monitor: Track performance, user engagement
For specific patterns and detailed implementations, explore the bundled resources referenced above.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★53 reviews- ★★★★★Chaitanya Patil· Dec 16, 2024
creating-dashboards fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Soo Taylor· Dec 16, 2024
I recommend creating-dashboards for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Soo Anderson· Dec 8, 2024
creating-dashboards fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Diya Brown· Dec 4, 2024
creating-dashboards has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Carlos Reddy· Nov 27, 2024
creating-dashboards is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Hana Johnson· Nov 11, 2024
Solid pick for teams standardizing on skills: creating-dashboards is focused, and the summary matches what you get after install.
- ★★★★★Piyush G· Nov 7, 2024
creating-dashboards is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Charlotte Agarwal· Nov 7, 2024
creating-dashboards reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Charlotte Malhotra· Nov 3, 2024
creating-dashboards has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Shikha Mishra· Oct 26, 2024
Keeps context tight: creating-dashboards is the kind of skill you can hand to a new teammate without a long onboarding doc.
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