Individual skill
dbt-model-spec
Spec a dbt model — its grain, sources, transformations, tests, and materialization. Use when asked to design a dbt model, plan a data transformation, write a staging/intermediate/mart model spec, or define dbt tests for a table. Produces a model spec — purpose & grain, lineage (sources → refs), the transformation logic, column definitions, dbt tests, materialization choice, and the skeleton SQL/YAML.
skills/dbt-model-spec/SKILL.md
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# dbt Model Spec Skill
A dbt model is only trustworthy if its **grain** is unambiguous, its **sources** are declared, and it's
**tested**. This skill specs a model the way a good analytics engineer would — naming the grain first,
mapping lineage, defining each column, choosing the right materialization, and writing the dbt tests
that keep it correct — so the model is reviewable before a line of SQL ships.
## Required Inputs
Ask for these only if they aren't already provided:
- **What the model represents** and its **grain** (one row per ___ — the single most important decision).
- **Layer** — staging, intermediate, or mart (dimension/fact). Conventions differ per layer.
- **Sources / upstream refs** — the raw tables or models it builds on.