loom-search

# Search ## Overview Full-text search on Lucene-based engines (Elasticsearch/OpenSearch) plus the leaner alternatives (Meilisearch/Typesense). The engine is easy to stand up and easy to get subtly wrong: **analyzer mismatches**, **facet counts that fight their own filters**, **deep pagination that falls over at 10k**, and **relevance that looks fine on your three test queries and terrible in production.** This skill targets those. `text` (analyzed, full-text, scored) vs `keyword` (exact, aggregatable, sortable, filterable) is the decision under most of these. Get the mapping right first. ## Analysis: the root of most bugs An **analyzer** = optional char filters → one tokenizer → token filters. It runs at **index time** (on the stored field) and at **query time** (on the search string). The inverted index only ever contains *analyzed* tokens. ⚠ **Index-time / query-time analyzer mismatch is the #1 silent search bug.** If you index with an `edge_ngram` analyzer and *also* analyze the query with it, searching "cat" expands to `c, ca, cat` and matches "category", "catalog", "cathedral" — garbage relevance. The fix is almost always: aggressive analyzer at index time, plain analyzer at search time. ```json "name": { "type": "text", "analyzer": "autocomplete", // edge_ngram — index time only "search_analyzer": "autocomplete_search" // just lowercase — query time } ``` - **Reindex required to change the index-time analyzer** (existing tokens are already commit...