
Cursor Skill
Store and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vecto
Data lake, analytics, search, ETL, and orchestration workflows with S3 Tables, AWS Glue, Athena, Amazon Redshift, Amazon OpenSearch Service, and Amazon MWAA. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, vector storage and semantic search on Amazon S3 Vectors, Amazon OpenSearch Service and Serverless (migration from Solr/Elasticsearch, provisioning, vector/semantic/hybrid search, log analytics, trace analytics), and Amazon MWAA Provisioned and MWAA Serverless (authoring, testing, and debugging DAGs and workflows, and Airflow version upgrades for provisioned environments).