Honeydew AI Coding Agents Plugins

Use when the user wants to query, analyze, or explore data through the Honeydew semantic layer. Covers structured queries and multi-step deep analysis.

Use after creating or modifying ANY Honeydew object (metric, attribute, entity, domain). Provides type-specific validation logic to ensure objects work correctly and return sensible results.

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 analysis.

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 the MCP tools.

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 exploring Honeydew semantic layer, discovering entities/fields, setting up workspace and branch context, or querying data. For creating metrics use metric-creation skill. For creating attributes use attribute-creation skill.

Guides you through defining a relationship between two Honeydew entities — covering join type, direction, cross-filtering, and connection method — then pushes the updated entity YAML to Honeydew via the MCP tools.

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. Covers when to create each type, naming conventions, folder organization, and the hard boundary between context (rules and procedures) and the semantic layer (logic and calculations).