How does import_tables differ from create_entity?

import_tables is a fast, automated method to bootstrap entities from existing warehouse tables, while create_entity offers full manual control via YAML for custom configurations.

Why is defining a granularity key important?

Honeydew requires unique, non-null keys to ensure accurate joins and prevent incorrect aggregation results in your metrics.

What is a Honeydew entity?

A Honeydew entity is a named, governed representation of a business concept (like customers or orders) anchored to a specific granularity in your data warehouse.

Which data warehouses are supported by this skill?

This skill supports semantic modeling for Snowflake, Databricks, and BigQuery data sources.

Can I update existing entities with this skill?

Yes, you can use the update_object functionality within this skill to modify existing entity or dataset configurations while preserving your YAML structure.

Honeydew Entity Modeler

Name: Honeydew Entity Modeler
Author: honeydew-ai

byhoneydew-ai

0•

Database Management

Guides the creation and management of Honeydew semantic entities from data warehouse sources with automated mapping and validation.

The Entity Creation skill provides a structured framework for defining Honeydew entities, the foundational building blocks of a governed semantic layer. It streamlines the process of mapping data warehouse tables from Snowflake, Databricks, or BigQuery into business-ready concepts by helping developers define granularity keys, source types, and initial attribute mappings. Whether performing bulk imports or crafting complex virtual entities via YAML, this skill ensures that your semantic model remains consistent, well-documented, and properly validated through integrated MCP tools.

Key Features

010 GitHub stars

02Automated validation workflow to ensure data integrity and key uniqueness

03Bulk import capabilities for rapidly bootstrapping warehouse tables into the model

04Integrated schema discovery for Snowflake, Databricks, and BigQuery

05Support for physical tables, custom SQL sources, and virtual entity derivations

06Guided entity and dataset creation using standardized YAML patterns

Use Cases

01Defining complex semantic relationships and granularity keys for multi-source data

02Mapping raw data warehouse tables to governed business concepts for BI tools

03Enforcing data governance standards through mandatory ownership and attribute tagging

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add honeydew-ai/honeydew-ai-coding-agents-plugins entity-creation

For use in Claude.ai and ChatGPT

Key Features

010 GitHub stars

02Automated validation workflow to ensure data integrity and key uniqueness

03Bulk import capabilities for rapidly bootstrapping warehouse tables into the model

04Integrated schema discovery for Snowflake, Databricks, and BigQuery

05Support for physical tables, custom SQL sources, and virtual entity derivations

06Guided entity and dataset creation using standardized YAML patterns

Use Cases

01Defining complex semantic relationships and granularity keys for multi-source data

02Mapping raw data warehouse tables to governed business concepts for BI tools

03Enforcing data governance standards through mandatory ownership and attribute tagging

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add honeydew-ai/honeydew-ai-coding-agents-plugins entity-creation

For use in Claude.ai and ChatGPT