Virtualize long lists and tables

SkillSearch

list-virtualization is a skill that guides an AI agent through speeding up interfaces with many repeated items, such as dashboards, admin tables, search results, and feeds, by rendering only the visible rows. It first confirms the bottleneck is DOM or rendering cost, since small lists usually do not need the added complexity.

Use Virtualize long lists and tables in Claude, ChatGPT or Ahel Desktop

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Then ask your AI: use the Virtualize long lists and tables skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Have an AI agent that can load skills.

Virtualize long lists and tablesStart free

What your AI can do with it

  • Guides rendering only visible rows in long dashboard tables and feeds
  • Applies to admin tables, search results, and feeds with many repeated items
  • Confirms the bottleneck is DOM or rendering cost before introducing virtualization
  • Avoids added complexity when lists are small and do not need virtualization

Getting started

  1. Have an AI agent that can load skills.
  2. Add the list-virtualization skill to the agent's available skills.
  3. Ask the agent to review a dashboard, admin table, search result list, or feed with many repeated items.
  4. Let the agent confirm the bottleneck is DOM or rendering cost before applying virtualization.

What this skill tells your AI

The instructions your AI receives, as published by thedaviddias/front-end-checklist in skills/list-virtualization/SKILL.md and read by ahel’s review.

Rendering hundreds or thousands of rows at once wastes memory and makes style calculation, layout, and painting more expensive. Virtualization keeps large collections responsive by limiting the number of mounted nodes.

Quick Reference

  • Render only what is visible plus a small overscan buffer instead of the entire list
  • Use virtualization when repeated rows or cards push DOM size and layout cost too high
  • Preserve item sizing, keyboard access, and screen-reader semantics when windowing content
  • Measure scroll smoothness, memory use, and DOM node count before and after the change

Check

Inspect long lists, tables, grids, and feeds for places where the UI renders every item at once. Flag views where the number of mounted rows or cards is large enough to create DOM, memory, or scroll-performance issues.

Fix

Introduce list or table virtualization so only the visible rows plus overscan render, while preserving sizing, keyboard navigation, and any required sticky headers or selection behavior.

Explain

Explain list virtualization, why it improves performance for large collections, and the tradeoffs engineers need to watch for around measurement and accessibility.

Code Review

Inspect collection components, data tables, infinite feeds, and dashboards. Flag places where rendering the full dataset creates excessive DOM nodes or scroll jank, and verify the virtualization strategy still preserves item identity, semantics, and expected interactions.


For full implementation details, code examples, and framework-specific guidance, see references/rule.md.

Rule page: https://frontendchecklist.io/en/rules/performance/list-virtualization

Signals

GitHub stars
74k
Forks
7k
Last commit
Oct 2026

Questions

When should this skill be used?
Use it when reviewing dashboards, admin tables, search results, or feeds with many repeated items.
Why check the bottleneck first?
Virtualization should only be introduced after confirming the bottleneck is DOM or rendering cost, because small lists usually do not need the added complexity.
What does virtualization do?
It speeds up long dashboard tables and feeds by only rendering the rows that are visible.
Advanced
Item type
skill
Key
list-virtualization
Source
github.com/thedaviddias/front-end-checklist