Guides you step-by-step through defining a business metric (aggregation) on a Honeydew entity. Covers SQL expression building and pushes to Honeydew via the MCP tools.
Use when the user needs to filter data — whether in a structured query, a metric aggregation, or an attribute expression. Covers filter syntax, date handling, and best practices.
Guides you through defining a relationship between two Honeydew entities — covering join type, direction, cross-filtering, and connection method — then pushes the updated entity…
Guides you through creating a Honeydew domain — a governance object that scopes entity/field visibility and applies mandatory filters — ideal for setting up contexts for deep…
Guides you through defining a new Honeydew entity from a data warehouse source — covering source type, granularity key, and initial attribute mapping — then pushes to Honeydew via…
Guides you step-by-step through defining a calculated attribute (dimension) on a Honeydew entity. Covers SQL expression building and pushes to Honeydew via the MCP tools.
Guides you through creating context items — instructions, skills, knowledge pointers, and memory events — that give the AI analyst persistent knowledge about your organization.
Use when exploring Honeydew semantic layer, discovering entities/fields, setting up workspace and branch context, or running simple structured queries to inspect data.
Use when setting up workspace and branch context, switching workspaces or branches, creating or deleting branches, reviewing branch history, or creating a pull request for a…