How do I validate my semantic layer configuration?

The skill guides you through a two-step validation: first running 'dbt parse' to check YAML syntax, followed by 'mf validate-configs' to ensure semantic integrity.

What types of metrics can I build with this skill?

You can build Simple, Derived (mathematical combinations), Cumulative (running totals), Ratio (percentages), and Conversion (funnel) metrics.

What is a 'Time Spine' and do I need one?

A Time Spine is a table with a continuous series of dates. It is required for cumulative metrics and grain-to-date aggregations to ensure accurate time-based reporting.

Which versions of dbt does this skill support?

The skill supports the latest specification for dbt Core 1.12+ and Fusion, as well as the legacy specification used in dbt Core versions 1.6 through 1.11.

dbt Semantic Layer Builder

Name: dbt Semantic Layer Builder
Author: dbt-labs

bydbt-labs

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304

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데이터베이스 관리

Automates the definition and validation of dbt Semantic Layer components to create consistent, governed business metrics.

This skill empowers developers to architect and implement the dbt Semantic Layer with precision, supporting both legacy and the latest YAML specifications (v1.12+). It provides structured guidance for defining semantic models, entities, and dimensions, while enabling the creation of complex metric types such as cumulative, ratio, and conversion metrics. By integrating MetricFlow validation and best practices, the skill ensures that data logic is consistent and query-ready for downstream BI tools, transforming raw dbt models into a robust semantic graph.

주요 기능

01Intelligent filtering implementation using Jinja templates for dimensions and entities

02Dual-spec support for both Latest (v1.12+) and Legacy dbt Semantic Layer configurations

03Automated creation of complex metric types including Derived, Cumulative, Ratio, and Conversion funnels

04Guided Time Spine configuration for time-based aggregations and period-over-period analysis

05304 GitHub stars

06Multi-stage validation workflow using dbt parse and MetricFlow (mf validate-configs)

사용 사례

01Building standardized KPI definitions like Monthly Recurring Revenue (MRR) or Customer Acquisition Cost (CAC) directly in dbt

02Migrating legacy metric definitions to the modern dbt Semantic Layer specification with automated validation

03Mapping complex physical data models to business-friendly semantic concepts for self-service analytics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add dbt-labs/dbt-agent-skills building-dbt-semantic-layer

For use in Claude.ai and ChatGPT

Download Skill