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building-tables skill

/skills/building-tables

This skill helps you design and optimize tables and data grids across simple HTML to enterprise scales, with accessibility, performance, and responsive

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SKILL.md
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---
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 mobile

Overview

This 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.

How this skill works

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.

When to use it

  • Displaying structured or tabular data in a UI
  • Implementing sorting, filtering, pagination, or inline editing
  • Handling datasets from a few rows up to millions of rows
  • Building spreadsheet-like interfaces or bulk-selection workflows
  • Ensuring accessibility, responsive layouts, or large-export support

Best practices

  • Choose implementation tier by data volume: <100 rows (HTML) → 100–1k (client features) → 1k–10k (server ops) → 10k+ (virtualization/streaming)
  • Prefer semantic HTML and ARIA grid patterns for accessibility and keyboard support
  • Keep client-side operations under ~1k rows; offload filtering/sorting to server beyond that
  • Benchmark rendering and API latency; aim for <50ms client ops and <200ms API responses
  • Use virtualization and windowing for 10k+ rows and streaming/workers for 100k+
  • Integrate design tokens for consistent theming (colors, spacing, typography)

Example use cases

  • Simple responsive HTML table for admin dashboards (<100 rows)
  • Sortable, filterable table with client pagination for mid-size datasets (100–1k rows)
  • Server-paginated API table for 1k–10k rows with fast server-side filtering
  • Virtual-scrolling grid for analytics dashboards handling 10k–100k+ rows
  • Enterprise grid using AG Grid for millions of rows with grouping and Excel-like UX

FAQ

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.