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attribute-creation

Create and update SQL-calculated attributes on Honeydew entities via MCP tools.

39|1|Updated Feb 23, 2026
Search Tags:#data modeling#sql#attribute#semantic layer#dimension#honeydew
One-click install
npx skills add https://github.com/honeydew-ai/honeydew-ai-coding-agents-plugins --skill attribute-creation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: attribute-creation
Source: https://github.com/honeydew-ai/honeydew-ai-coding-agents-plugins/tree/main/plugins/semantic-modeling-tools/skills/attribute-creation
Command: npx skills add https://github.com/honeydew-ai/honeydew-ai-coding-agents-plugins --skill attribute-creation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) components.

What problem does it solve?

This Skill streamlines the creation of calculated attributes (dimensions) on your entities, ensuring consistent, governed data definitions across your organization.

Core Features & Use Cases

  • Guided SQL Expression Building: Assists in crafting SQL expressions for new attributes.
  • Object Creation & Update: Manages the lifecycle of attributes via the create_object and update_object MCP tools.
  • Use Case: Create a net_price attribute on the orders entity by multiplying amount and (1 - discount_rate), making this calculation reusable and standardized.

Quick Start

Create a new calculated attribute named 'order_month' on the 'orders' entity using the SQL expression 'DATE_TRUNC('month', orders.order_date)'.

Frequently Asked Questions about attribute-creation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create reusable calculated dimensions using SQL expressions?▼

You can define calculated dimensions by building SQL expressions on Honeydew entities. The Skill uses MCP tools to create and update these attributes, enforcing SQL dialect rules, naming conventions, and data types for consistent semantic layer definitions.

What is a semantic layer attribute and when do I need one?▼

A semantic layer attribute is a reusable calculated dimension defined directly on data entities. You need one when standardizing calculations across your organization, such as defining a universal order month extraction to ensure governed data definitions.

Can I use window functions or extract semi-structured data in a calculated attribute?▼

Yes, calculated attributes support advanced SQL use cases including window functions and semi-structured data extraction. This allows you to define complex analytical logic and reference multiple entities within a single attribute definition.

How do I update or delete an existing calculated attribute on an entity?▼

Existing calculated attributes are managed through the update_object and delete_object MCP tools. This lifecycle management allows you to modify SQL expressions or remove dimensions as your data modeling requirements evolve.

Does this attribute creation process enforce specific SQL dialects and naming conventions?▼

Yes, defining calculated attributes ensures adherence to core rules for SQL dialect, naming conventions, and data types. This governance prevents inconsistencies and ensures dimensions operate correctly across the semantic layer.

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