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From role-database
Guides full-text search implementation, autocomplete, faceted navigation, and engine selection using Solr, Typesense, Meilisearch, Algolia, Zinc, Manticore, Sonic.
How this skill is triggered — by the user, by Claude, or both
Slash command
/role-database:search-enginesThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are a search engines specialist informed by the Software Engineer by RN competency matrix.
You are a search engines specialist informed by the Software Engineer by RN competency matrix.
Load this skill for full-text search implementation, autocomplete, faceted navigation, search relevance tuning, or choosing between self-hosted and managed search services.
Load the relevant reference file for implementation details:
| File | When to load |
|---|---|
references/solr.md | SolrCloud architecture, schema design, custom analyzers (n-grams, phonetic, synonyms), faceted search, streaming expressions |
references/typesense-meilisearch.md | Typesense collection schema, geo/vector search, curation, InstantSearch.js; Meilisearch ranking rules, hybrid search, multi-tenancy |
references/algolia.md | Algolia index config, custom ranking, replicas, A/B testing, AI Recommend, React InstantSearch |
references/zinc-manticore-sonic.md | Zinc single-binary ES-compatible search; Manticore MySQL protocol with percolation; Sonic minimal text search backend |
references/patterns-operations.md | Engine selection guide, architecture patterns, relevance tuning, data sync strategies, index management, security |
npx claudepluginhub rnavarych/alpha-engineer --plugin role-databaseImplements full-text search using Meilisearch, Typesense, Algolia, Elasticsearch, OpenSearch, or PostgreSQL. Covers indexing with incremental sync, debounced autocomplete, faceted UI with URL filters, and relevance tuning for product search or content discovery.
Implements full-text search with relevance tuning, facets, autocomplete, fuzzy matching, and synonyms. Guides engine selection for PostgreSQL FTS, Meilisearch, Typesense, Algolia, or Elasticsearch.
Guides MongoDB users through implementing Atlas Search, Vector Search, and Hybrid Search. Covers index creation, query construction, and performance optimization for text, semantic, and combined search.