surrealdb
GitHub2 skills
surrealdb-vectorsurrealdbVector search with SurrealDB using HNSW indexes, KNN queries, and similarity scoring. Use when creating vector indexes, querying vectors with KNN distance operators, building semantic search or RAG pipelines, tuning HNSW parameters (EFC, M, M0, distance function, type), or implementing recommendation systems with SurrealDB. Triggers: HNSW, vector, embedding, KNN, cosine, euclidean, semantic search, RAG, vector::distance.surrealqlsurrealdbGenerate and modify SurrealQL queries to interact with SurrealDB databases. This includes creating and retrieving records, designing and managing schemas, establishing and querying graph relationships, performing live (real-time) queries, and leveraging all unique SurrealQL features for advanced database workflows. Use this skill whenever users need to write, adapt, or troubleshoot SurrealQL statements.