Design and operate full-text and vector search infrastructure — inverted-index engines (Elasticsearch/OpenSearch, Meilisearch, Typesense), analyzers and tokenization, relevance tuning (BM25, boosting, synonyms), faceting, and semantic/vector search (embeddings, ANN indexes, hybrid retrieval). Use when adding a search box, choosing a search engine, designing an index mapping and analyzer chain, tuning relevance, building autocomplete, deciding keyword vs vector vs hybrid retrieval, or keeping a search index in sync with the source database. Boundary vs db-design — db-design owns the durable transactional source of truth (normalized PostgreSQL schema, known-key indexes, migrations, ACID); this skill owns the derived denormalized search index built FROM that source for ranked free-text/semantic retrieval, where the engine is eventually-consistent, rebuildable, and never the system of record. Defers cache concerns to redis and RAG prompt assembly to llm-patterns.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryEngineeringStars0
About this skill
Design and operate full-text and vector search infrastructure — inverted-index engines (Elasticsearch/OpenSearch, Meilisearch, Typesense), analyzers and tokenization, relevance tuning (BM25, boosting, synonyms), faceting, and semantic/vector search (embeddings, ANN indexes, hybrid retrieval). Use when adding a search box, choosing a search engine, designing an index mapping and analyzer chain, tuning relevance, building autocomplete, deciding keyword vs vector vs hybrid retrieval, or keeping a search index in sync with the source database. Boundary vs db-design — db-design owns the durable transactional source of truth (normalized PostgreSQL schema, known-key indexes, migrations, ACID); this skill owns the derived denormalized search index built FROM that source for ranked free-text/semantic retrieval, where the engine is eventually-consistent, rebuildable, and never the system of record. Defers cache concerns to redis and RAG prompt assembly to llm-patterns.
Quick start
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Design and operate full-text and vector search infrastructure — inverted-index engines (Elasticsearch/OpenSearch, Meilisearch, Typesense), analyzers and tokenization, relevance tuning (BM25, boosting, synonyms), faceting, and semantic/vector search (embeddings, ANN indexes, hybrid retrieval). Use when adding a search box, choosing a search engine, designing an index mapping and analyzer chain, tuning relevance, building autocomplete, deciding keyword vs vector vs hybrid retrieval, or keeping a search index in sync with the source database. Boundary vs db-design — db-design owns the durable transactional source of truth (normalized PostgreSQL schema, known-key indexes, migrations, ACID); this skill owns the derived denormalized search index built FROM that source for ranked free-text/semantic retrieval, where the engine is eventually-consistent, rebuildable, and never the system of record. Defers cache concerns to redis and RAG prompt assembly to llm-patterns.
About this listing
Category
Engineering
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI