home / skills / ancoleman / ai-design-components / building-tables
This skill helps you design and optimize tables and data grids across simple HTML to enterprise scales, with accessibility, performance, and responsive
npx playbooks add skill ancoleman/ai-design-components --skill building-tablesReview the files below or copy the command above to add this skill to your agents.
---
name: building-tables
description: Builds tables and data grids for displaying tabular information, from simple HTML tables to complex enterprise data grids. Use when creating tables, implementing sorting/filtering/pagination, handling large datasets (10-1M+ rows), building spreadsheet-like interfaces, or designing data-heavy components. Provides performance optimization strategies, accessibility patterns (WCAG/ARIA), responsive designs, and library recommendations (TanStack Table, AG Grid).
---
# Building Tables & Data Grids
## Purpose
This skill enables systematic creation of tables and data grids from simple HTML tables to enterprise-scale virtualized grids handling millions of rows. It provides clear decision frameworks based on data volume and required features, ensuring optimal performance, accessibility, and responsive design across all implementations.
## When to Use
Activate this skill when:
- Creating tables, data grids, or spreadsheet-like interfaces
- Displaying tabular or structured data
- Implementing sorting, filtering, or pagination features
- Handling large datasets or addressing performance concerns
- Building inline editing or data entry interfaces
- Requiring row selection or bulk operations
- Implementing data export (CSV, Excel, PDF)
- Ensuring table accessibility or responsive behavior
## Quick Decision Framework
Select implementation tier based on data volume:
```
<100 rows → Simple HTML table with progressive enhancement
100-1,000 rows → Client-side features (sort, filter, paginate)
1,000-10,000 → Server-side operations with API pagination
10,000-100,000 → Virtual scrolling with windowing
>100,000 rows → Enterprise grid with streaming and workers
```
For detailed selection criteria, reference `references/selection-framework.md`.
## Core Implementation Patterns
### Tier 1: Basic Tables (<100 rows)
For simple, read-only data display:
- Use semantic HTML `<table>` structure
- Add responsive behavior via CSS
- Implement client-side sorting if needed
- Reference `references/basic-tables.md` for patterns
Example: `examples/simple-responsive-table.tsx`
### Tier 2: Interactive Tables (100-10K rows)
For feature-rich interactions:
- Add filtering, pagination, and selection
- Implement inline or modal editing
- Use client-side operations up to 1K rows
- Switch to server-side beyond 1K rows
- Reference `references/interactive-tables.md`
Example: `examples/sortable-filtered-table.tsx`
### Tier 3: Advanced Grids (10K+ rows)
For massive datasets:
- Implement virtual scrolling
- Use server-side aggregation
- Add grouping and hierarchies
- Consider enterprise solutions
- Reference `references/advanced-grids.md`
Example: `examples/virtual-scrolling-grid.tsx`
## Performance Optimization
Critical performance thresholds:
- Client-side operations: <1,000 rows (instant, <50ms)
- Server-side operations: 1,000-10,000 rows (<200ms API)
- Virtual scrolling: 10,000+ rows (60fps, constant memory)
- Streaming: 100,000+ rows (progressive rendering)
To benchmark performance:
```bash
# Generate test data
python scripts/generate_mock_data.py --rows 10000
# Analyze rendering performance
node scripts/analyze_performance.js
```
For optimization strategies, reference `references/performance-optimization.md`.
## Feature Implementation
### Sorting
- Single or multi-column sorting
- Custom sort logic (numeric, date, natural)
- Visual indicators and keyboard support
- Reference `references/sorting-filtering.md`
### Filtering & Search
- Column-specific filters (text, range, select)
- Global search across all columns
- Advanced filter logic (AND/OR)
- Reference `references/sorting-filtering.md`
### Pagination
- Client-side for small datasets
- Server-side for large datasets
- Infinite scroll alternative
- Reference `references/pagination-strategies.md`
### Selection & Bulk Actions
- Single or multi-row selection
- Range selection (Shift+click)
- Bulk operations toolbar
- Reference `references/selection-patterns.md`
### Inline Editing
- Cell-level or row-level editing
- Validation and error handling
- Optimistic updates
- Reference `references/editing-patterns.md`
### Export
- CSV, Excel, PDF formats
- Preserve formatting and encoding
- Stream large exports
- Run `scripts/export_table_data.py`
## Accessibility Requirements
Essential WCAG compliance:
- Semantic HTML with proper structure
- ARIA grid pattern for interactive tables
- Full keyboard navigation
- Screen reader announcements
To validate accessibility:
```bash
node scripts/validate_accessibility.js
```
For complete requirements, reference `references/accessibility-patterns.md`.
## Responsive Design
Four proven strategies:
1. **Horizontal scroll** - Simple, preserves structure
2. **Card stack** - Transform rows to cards on mobile
3. **Priority columns** - Hide less important columns
4. **Truncate & expand** - Compact with details on demand
See `examples/responsive-patterns.tsx` for implementations.
Reference `references/responsive-strategies.md` for details.
## Library Recommendations
### Primary: TanStack Table (Headless)
Best for custom designs and complete control:
- TypeScript-first with excellent DX
- Small bundle size (~15KB)
- Framework agnostic
- Virtual scrolling support
```bash
npm install @tanstack/react-table
```
See `examples/tanstack-basic.tsx` for setup.
### Enterprise: AG Grid
Best for feature-complete solutions:
- Handles millions of rows
- Built-in advanced features
- Community (free) + Enterprise (paid)
- Excel-like user experience
```bash
npm install ag-grid-react
```
See `examples/ag-grid-enterprise.tsx` for setup.
For detailed comparison, reference `references/library-comparison.md`.
## Design Token Integration
Tables use the design-tokens skill for consistent theming:
- Color tokens for backgrounds, borders, and states
- Spacing tokens for cell padding
- Typography tokens for text styling
- Shadow tokens for elevation
Supports light, dark, high-contrast, and custom themes.
Reference the design-tokens skill for theme switching.
## Working Examples
Start with the example matching the requirements:
```
simple-responsive-table.tsx # Basic HTML table
sortable-filtered-table.tsx # With sorting and filtering
paginated-server-table.tsx # Server-side pagination
virtual-scrolling-grid.tsx # High-performance for 100K+ rows
editable-data-grid.tsx # Inline editing with validation
grouped-aggregated-table.tsx # Hierarchical with aggregations
```
## Testing Tools
Generate test data:
```bash
python scripts/generate_mock_data.py --rows 100000 --columns 20
```
Benchmark performance:
```bash
node scripts/analyze_performance.js --rows 10000
```
Validate accessibility:
```bash
node scripts/validate_accessibility.js
```
## Next Steps
1. Determine the data volume and feature requirements
2. Select the appropriate implementation tier
3. Choose between TanStack Table (flexibility) or AG Grid (features)
4. Start with the matching example file
5. Implement core features progressively
6. Test performance and accessibility
7. Apply responsive strategy for mobileThis skill builds tables and data grids for UIs, from simple HTML tables to enterprise-scale virtualized grids handling millions of rows. It provides a decision framework, performance strategies, accessibility patterns, responsive options, and library recommendations to deliver robust, performant tabular interfaces. Use it to design, implement, and optimize tables across web applications.
The skill inspects data volume and feature requirements to select an implementation tier (basic HTML, interactive client-side, server-backed, virtualized, or enterprise). It prescribes patterns for sorting, filtering, pagination, selection, inline editing, exports, and responsive behavior. It also recommends performance thresholds, accessibility (WCAG/ARIA) practices, and libraries such as TanStack Table and AG Grid for appropriate use cases.
Which library should I pick for full control and small bundle size?
Use TanStack Table for a headless, TypeScript-first approach that keeps bundle size small and maximizes design flexibility.
When is AG Grid the right choice?
Choose AG Grid for feature-complete, enterprise scenarios where built-in grouping, aggregation, and extreme-scale performance are required.