Adds the mongodb-search-and-ai skill — an agent skill for implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search in MongoDB.
Reference Files
- lexical-search-indexing.md — Atlas Search index configuration: field types, analyzers, dynamic/explicit/typeSet mappings, storedSource, synonyms, and creating Search indexes on Views
- lexical-search-querying.md — Atlas Search query patterns: $search vs $searchMeta, count, pagination with searchSequenceToken, returnScope, compound queries, autocomplete, facet, geo operators, sort optimization, and compound.filter vs $match guidance
- vector-search.md — Vector Search index configuration, $vectorSearch query construction, filter fields, numCandidates tuning, ANN vs ENN, and Vector Search on Views
- hybrid-search.md — $rankFusion (MongoDB 8.0+), $scoreFusion (MongoDB 8.2+), lexical prefilters using the vectorSearch operator inside $search, and choosing between approaches
Key Design Decisions
- Skill scope explicitly excludes Voyage API integration, auto-embedding, and reranking
- Skill description includes text containment signals (contains, includes, appears in) to correctly route text search use cases away from the NLQ skill
Testing
- 15 evals covering lexical, vector, hybrid, and edge cases
- Skills-boundary tests (natural-language-querying-vs-search-ai.json) with 25 test cases validating correct skill invocation vs mongodb-natural-language-querying
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