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scylladb-data-modeling
Cursor Skill
ScyllaDB CQL data modeling patterns and anti-patterns. Use when designing tables, reviewing schemas, migrating from SQL or MongoDB, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "ScyllaDB data model", "partition key", "clustering column", "primary key", "CQL table design", "ALLOW FILTERING", "large partitions", "hot partitions", "query-first design", "secondary index", "materialized view", "schema review", "wide partition", "tombstones", "time series".
Official ScyllaDB agent skills. Bundles guided skills for ScyllaDB Cloud setup, CQL data modeling, and Vector Search; each is invoked independently by the agent when relevant.
Created by ScyllaDBView Source
Skills3
scylladb-cloud-setupGuide users through connecting to a ScyllaDB Cloud cluster. Use this skill when a user needs to connect to ScyllaDB Cloud, configure driver credentials, or troubleshoot connection issues. Triggers on "connect to ScyllaDB Cloud", "ScyllaDB connection", "ScyllaDB driver setup", "CQL connection", "DC-aware load balancing", "ScyllaDB credentials", "connection bundle".
scylladb-data-modelingScyllaDB CQL data modeling patterns and anti-patterns. Use when designing tables, reviewing schemas, migrating from SQL or MongoDB, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "ScyllaDB data model", "partition key", "clustering column", "primary key", "CQL table design", "ALLOW FILTERING", "large partitions", "hot partitions", "query-first design", "secondary index", "materialized view", "schema review", "wide partition", "tombstones", "time series".
scylladb-vector-searchGuides ScyllaDB Cloud users through implementing and optimizing Vector Search for semantic similarity, RAG, and similar use cases. Use this skill when users need to store and query embeddings, build vector indexes (HNSW), run approximate nearest neighbour (ANN) queries, apply filtering (global/local secondary indexes), configure quantization, or integrate with LLM frameworks (e.g. LangChain). Also use when users mention "vector", "embeddings", "similarity search", "ANN", "nearest neighbor", "RAG", "semantic search", or "recommendation system" in the context of ScyllaDB.