This covers the essentials of working with Elasticsearch, from index management and mapping design to complex boolean queries and aggregations. You get Python examples for bulk indexing, multi-match searches with field boosting, and common aggregation patterns like histograms and term buckets. The best practices section is solid, calling out things like using search_after instead of deep pagination and applying filters for exact matches. It's aimed at someone building search functionality or working with the ELK stack who needs quick reference material for queries and cluster operations. The anti-patterns list alone will save you from common performance mistakes.
npx skills add https://github.com/personamanagmentlayer/pcl --skill elasticsearch-expert