How does it identify dimensions?

It scans your model's column types and names to suggest appropriate categorical or time-based dimensions for your confirmation.

Can it help migrate old metrics?

Yes, it includes guidance for migrating older metrics specifications to the current dbt Semantic Layer format.

Which dbt versions are supported?

This skill is optimized for dbt 1.12.0 and above, following the latest semantic layer YAML specification.

Can it handle cross-model metrics?

Absolutely, it supports top-level metrics like ratios and derived metrics that span multiple semantic models.

Does it validate the generated YAML files?

Yes, it performs both dbt parse validation and semantic layer validation using the dbt Cloud CLI or MetricFlow CLI.

dbt Semantic Layer Architect

Name: dbt Semantic Layer Architect
Author: dbt-labs

bydbt-labs

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データベース管理

Simplifies the creation and management of dbt Semantic Layer components including semantic models, metrics, and dimensions.

概要

This skill empowers Claude to act as a domain expert for the dbt Semantic Layer, guiding users through the end-to-end process of defining semantic models, entities, dimensions, and metrics. It leverages MetricFlow to translate complex business logic into standardized YAML configurations, ensuring consistent data definitions across your organization. Whether you are starting from a raw business question or an existing dbt model, this skill provides structured workflows for implementation, validation, and maintenance of the dbt 1.12.0+ metrics specification.

主な機能

Identification of primary/foreign entities and categorical/time dimensions
Support for simple, derived, cumulative, ratio, and conversion metrics
Guidance on migrating older metric specs to the current dbt standard
Automated generation of semantic model YAML configurations
Two-stage validation using dbt parse and MetricFlow/dbt SL commands
13 GitHub stars

ユースケース

Validating and refining complex cross-model metrics and aggregations
Exposing existing dbt models to the semantic layer for BI consumption
Transforming business requirements into tracked metrics like LTV or churn

概要

主な機能

Identification of primary/foreign entities and categorical/time dimensions
Support for simple, derived, cumulative, ratio, and conversion metrics
Guidance on migrating older metric specs to the current dbt standard
Automated generation of semantic model YAML configurations
Two-stage validation using dbt parse and MetricFlow/dbt SL commands
13 GitHub stars

ユースケース

Validating and refining complex cross-model metrics and aggregations
Exposing existing dbt models to the semantic layer for BI consumption
Transforming business requirements into tracked metrics like LTV or churn