Should I use this skill to create new metrics or attributes?

No, this skill is specifically for exploration and querying. For creation tasks, you should use the specialized metric-creation or attribute-creation skills.

What is the primary purpose of the Honeydew Model Exploration skill?

It is designed to help users navigate the Honeydew semantic layer, discover available data entities and metrics, manage workspace contexts, and execute data queries.

Does this skill support natural language data requests?

Yes, it includes tools like ask_question_get_data and ask_deep_analysis_question which allow you to query your data using plain English.

Which data warehouses can I explore with this skill?

The skill supports discovery and querying for Snowflake, Databricks, and Google BigQuery environments via the Honeydew semantic layer.

How do I ensure I'm working in the correct development environment?

You can use the session management tools to list workspaces, select a specific branch, or create a new branch to isolate your changes from production.

Honeydew Semantic Model Exploration

Name: Honeydew Semantic Model Exploration
Author: honeydew-ai

byhoneydew-ai

0•

Database Management

Explores semantic layers, discovers data entities, and executes complex data queries within Honeydew workspaces.

The Honeydew Model Exploration skill enables developers to navigate and interact with the Honeydew Semantic Layer directly within Claude Code. It provides a robust set of tools for discovering entities, metrics, and attributes across Snowflake, Databricks, and BigQuery warehouses. Users can manage their development environment through workspace and branch controls, inspect raw warehouse schemas, and perform data analysis ranging from structured SQL generation to AI-powered natural language queries. It serves as the foundational discovery tool for any data-centric workflow involving Honeydew's source of truth.

Key Features

01Comprehensive discovery of semantic entities, metrics, and fields

02Direct inspection of Snowflake, Databricks, and BigQuery schemas

03Workspace and branch management for isolated development environments

04AI-powered natural language querying and multi-step deep analysis

05Deterministic SQL generation and data execution from field parameters

060 GitHub stars

Use Cases

01Investigating data trends and root causes using agentic natural language analysis

02Mapping out data relationships and entity fields before implementing new business logic

03Switching between production and development branches to test semantic model changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add honeydew-ai/honeydew-ai-coding-agents-plugins model-exploration

For use in Claude.ai and ChatGPT

Key Features

01Comprehensive discovery of semantic entities, metrics, and fields

02Direct inspection of Snowflake, Databricks, and BigQuery schemas

03Workspace and branch management for isolated development environments

04AI-powered natural language querying and multi-step deep analysis

05Deterministic SQL generation and data execution from field parameters

060 GitHub stars

Use Cases

01Investigating data trends and root causes using agentic natural language analysis

02Mapping out data relationships and entity fields before implementing new business logic

03Switching between production and development branches to test semantic model changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add honeydew-ai/honeydew-ai-coding-agents-plugins model-exploration

For use in Claude.ai and ChatGPT