answering-natural-language-questions-with-dbt

Answer business questions by querying the semantic layer and dbt models.

653|60|Updated Jan 8, 2026

Search Tags:#dbt #sql #nlp #data-analytics #model-discovery #semantic-layer #business-questions

Ready to run

npx skills add https://github.com/dbt-labs/dbt-agent-skills --skill answering-natural-language-questions-with-dbt-dbt-labs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: answering-natural-language-questions-with-dbt
Source: https://github.com/dbt-labs/dbt-agent-skills/tree/main/skills/answering-natural-language-questions-with-dbt
Command: npx skills add https://github.com/dbt-labs/dbt-agent-skills --skill answering-natural-language-questions-with-dbt-dbt-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Answering business questions requires translating natural language into data queries across semantic models, metrics, and dbt artifacts.

Core Features & Use Cases

Semantic-layer driven answers: query metrics and dimensions using the semantic layer.
Fallbacks: if SL can't answer, switch to compiled SQL, then model discovery, then manifest analysis.
Real-world use cases: revenue by region, top products, trend analysis.

Quick Start

Ask a business question in natural language and the system will use the semantic layer to generate an answer.

Frequently Asked Questions about answering-natural-language-questions-with-dbt

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

FAQPage Schema

How do I answer business questions using the dbt semantic layer?▼

To answer business questions using the dbt semantic layer, query metrics and dimensions directly to retrieve data-driven insights like revenue by region or top products without writing manual SQL.

What is the fallback mechanism when the semantic layer cannot answer my data query?▼

When the semantic layer cannot answer your data query, the system sequentially falls back to modifying compiled SQL, discovering dbt marts, and analyzing manifest or catalog artifacts to retrieve the required insights.

How do I retrieve revenue by region and perform trend analysis in dbt?▼

Retrieve revenue by region and perform trend analysis in dbt by asking a natural language question, which triggers a semantic layer query to automatically calculate metrics and dimensions across your models.

Can I discover dbt marts and analyze artifacts without validating models during development?▼

Yes, you can discover dbt marts and analyze manifest or catalog artifacts to answer business questions without validating or building models during development, ensuring quick and accurate data retrieval.

What dbt tools do I need to access semantic layer queries and model discovery?▼

You need access to semantic layer tooling, dbt model discovery workflows, and manifest or catalog analysis capabilities to successfully execute semantic-layer queries and retrieve business insights.