{"skill":{"slug":"voyageai-skill","displayName":"Voyage AI CLI","summary":"Voyage AI embedding and reranking CLI integrated with MongoDB Atlas Vector Search. Use for: generating text embeddings, reranking search results, storing embeddings in Atlas, performing vector similarity search, creating vector search indexes, listing available models, comparing text similarity, bulk ingestion, interactive demos, and learning about AI concepts. Triggers: embed text, generate embeddings, vector search, rerank documents, voyage ai, semantic search, similarity search, store embeddings, atlas vector search, embedding models, cosine similarity, bulk ingest, explain embeddings.","tags":{"cli":"1.4.0","database":"1.4.0","latest":"1.4.0","llm":"1.4.0","mongodb":"1.4.0","reranking":"1.4.0","stable":"1.4.0","vectorsearch":"1.4.0","voyageai":"1.4.0"},"stats":{"comments":0,"downloads":1860,"installsAllTime":1,"installsCurrent":1,"stars":0,"versions":1},"createdAt":1770124519386,"updatedAt":1777524976352},"latestVersion":{"version":"1.4.0","createdAt":1770124519386,"changelog":"- Added comprehensive SKILL.md documentation detailing all features, setup instructions, environment variables, and command references.\n- Included usage examples for embeddings, reranking, vector search, model management, batch ingestion, and more.\n- Documented common workflows for typical vector search and retrieval use cases.\n- Listed global flags and linked reference guides for models and vector search patterns.","license":null},"metadata":{"os":null,"systems":null},"owner":{"handle":"mrlynn","userId":"publishers:mrlynn","displayName":"Michael Lynn","image":"https://avatars.githubusercontent.com/u/192552?v=4"},"moderation":null}