Build dynamic faceted search UIs on RushDB with schema-driven filters.
npx skills add https://github.com/rush-db/rushdb --skill rushdb-faceted-search
Please help me install this Agent Skill. Skill: rushdb-faceted-search Source: https://github.com/rush-db/rushdb/tree/main/packages/skills/rushdb-faceted-search Command: npx skills add https://github.com/rush-db/rushdb --skill rushdb-faceted-search
Build dynamic, schema-driven faceted search UIs on RushDB that let users filter records by properties, ranges, and values without hardcoding widgets.
Generate a ready-to-use faceted search panel by loading the RushDB schema, pulling property values, selecting widgets by type, and wiring user filters into a live where clause for record queries.
High-intent search queries and answers about installing and using this skill.
To build a faceted search UI, discover property types from the live schema via ontology discovery, enumerate distinct values, map types to UI widgets, and wire user filters into a live where clause for record queries.
Yes, dynamic search filters can be generated without hardcoding by using RushDB's ontology discovery to detect property types and automatically mapping them to appropriate UI widgets like multi-select facets and range sliders.
Lazy loading for large string sets fetches distinct property values on demand during search filtering, while booleans and numbers are eager loaded, ensuring the faceted search UI remains responsive across large datasets.
Yes, this approach supports range sliders and multi-select facets for product catalogs by mapping discovered schema types to reactive UI widgets and assembling a live where clause pipeline for interactive filtering.
The best way to create a reactive where clause pipeline is using RushDB's findRecords query construction, reacting to filter changes and updating record queries live for admin panel dashboards without hardcoded widgets.
A limitation of using ontology discovery to map schema types is that complex or nested relationships may require custom handling beyond standard property-based filtering, multi-select facets, and range sliders.
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ancolemanImplements search and filter interfaces in React/TypeScript and Python with debouncing and database integration.
