A scalable, distributed, collaborative, document-graph database, for the realtime web
SurrealDB's skills help AI agents work with its database across SurrealQL query writing, schema design, graph relationships, live queries, and vector search with HNSW indexes for semantic search and RAG pipelines. They also cover performance tuning through record ID design and index selection, and SDK usage from Python and JavaScript/TypeScript, including embedded mode. A notable feature of the set is the operational side, with skills for running the surreal CLI server, importing and exporting data, and looking up current function signatures and official documentation.
Agent Skills
10 skills · 28 stars · MIT
Surrealdb Agent Memory Docs Look up official SurrealDB Agent Memory (formerly Spectron) documentation from surrealdb.com as m…
Surrealdb Cli Use the `surreal` command-line binary to run a SurrealDB server (in-memory, RocksDB, SurrealKV, o…
Surrealdb Docs Look up official SurrealDB documentation (SurrealQL, SDKs, CLI, deployment) from surrealdb.com as…
Surrealdb Js Using SurrealDB from JavaScript and TypeScript with the official surrealdb SDK, covering connecti…
Surrealdb Python Using SurrealDB with the Python SDK, covering both client/server mode (WebSocket) and embedded mo…
Surrealdb Vector Vector search with SurrealDB using HNSW indexes, KNN queries, and similarity scoring.
Surrealkit Use SurrealKit, SurrealDB's schema-management and migration CLI, to scaffold projects from templa…
Surrealql Generate and modify SurrealQL queries to interact with SurrealDB databases.
Surrealql Functions Discover and use SurrealDB's built-in SurrealQL functions with accurate, version-current signatur…
Surrealql Performance Optimize SurrealDB performance through record ID and key design, indexing strategy, and computed/…