What is the difference between structured and natural language queries?

Structured queries use specific field names for deterministic results and full control, while natural language queries allow you to ask questions in plain English for quick answers.

Do I need to know the database schema to use this skill?

No, you can use discovery tools like list_entities to explore the model or simply ask questions in natural language, and the Honeydew semantic layer handles the mapping.

Does it support data pagination?

Yes, the structured query methods include limit and offset parameters to help you manage and navigate large result sets efficiently.

Can I see the SQL before it executes?

Yes, tools like get_sql_from_fields and ask_question_get_sql return the generated SQL for review or debugging without running it against your data source.

How does the Deep Analysis feature work?

It uses agentic reasoning to perform multi-step investigations, looking at data from multiple angles to answer complex 'why' questions, detect anomalies, or find hidden trends.

Honeydew Data Query & Analysis

Name: Honeydew Data Query & Analysis
Author: honeydew-ai

byhoneydew-ai

0•

Data Science & ML

Queries, analyzes, and explores complex data through the Honeydew semantic layer using natural language or structured fields.

This skill empowers Claude to interact with Honeydew's semantic layer, enabling sophisticated data exploration ranging from simple natural language questions to deep agentic analysis. It provides multiple entry points: precise structured queries for deterministic results, natural language to SQL translation for quick answers, and multi-step deep analysis for investigative reasoning and root cause investigation. By abstracting complex SQL and joins through a semantic model, it allows developers and analysts to perform high-level data reasoning and trend analysis directly within their terminal workflow.

Key Features

01Structured query execution with precise control over metrics, attributes, and filters

02SQL previewing and debugging capabilities to review logic before execution

03Agentic deep analysis for multi-step reasoning and root cause investigation

040 GitHub stars

05Cross-entity data retrieval powered by Honeydew's semantic relations

06Natural language to SQL translation for intuitive, plain-English data exploration

Use Cases

01Investigating business metric trends such as revenue drops or user growth anomalies

02Exploring new datasets using plain English to discover patterns without knowing the underlying schema

03Generating precise reports by combining specific attributes and metrics across multiple data entities

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add honeydew-ai/honeydew-ai-coding-agents-plugins query

For use in Claude.ai and ChatGPT

Key Features

01Structured query execution with precise control over metrics, attributes, and filters

02SQL previewing and debugging capabilities to review logic before execution

03Agentic deep analysis for multi-step reasoning and root cause investigation

040 GitHub stars

05Cross-entity data retrieval powered by Honeydew's semantic relations

06Natural language to SQL translation for intuitive, plain-English data exploration

Use Cases

01Investigating business metric trends such as revenue drops or user growth anomalies

02Exploring new datasets using plain English to discover patterns without knowing the underlying schema

03Generating precise reports by combining specific attributes and metrics across multiple data entities