amvcp-tables

To choose the right interactive table UI, use a routing matrix that matches your table shape and capabilities—like sorting, virtualization, or matrix comparisons—against the appropriate specialized table renderer for your specific workflow.

Handling large datasets in a virtualized table requires routing your request to a sibling skill specialized in virtualization, ensuring the matched renderer owns initialization and outputs for optimal performance.

Yes, you can combine sortable tables with per-cell decision pills by using composition support, which loads multiple table siblings simultaneously when a single workflow spans multiple capability categories.

Adding status decision pills to a matrix comparison table involves routing your request through a routing matrix that identifies the need for both matrix layouts and per-cell decision pill UX, then loading the matched siblings.

Yes, this table routing approach supports special layouts like kanban and two-column before-after comparisons by matching those specific structural requirements within the routing matrix to select the correct sibling renderer.

You should avoid using a single table component for multiple tasks when progressive discovery is better, as routing to five focused sibling skills keeps each implementation's embedded TOC natural and readable instead of forcing a one-size-fits-all solution.