staging-layer

Convert raw source tables into standardized dbt staging models with 1:1 mapping.

1|1|Updated Feb 27, 2026
One-click install
npx skills add https://github.com/nrakow/ae-skills-dev --skill staging-layer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: staging-layer
Source: https://github.com/nrakow/ae-skills-dev/tree/main/skills/staging-layer
Command: npx skills add https://github.com/nrakow/ae-skills-dev --skill staging-layer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build dbt staging models that convert raw source data into a clean, consistent staging layer with a 1:1 mapping.

Core Features & Use Cases

  • One staging model per source table with the naming convention stg_<source_name>__<table_name>.
  • Enforce 1:1 source-to-staging mapping and forbid joins or business logic in staging.
  • Read existing sources to avoid duplicates and use schema introspection for column stability.

Quick Start

Create a new staging model by inspecting the raw source with schema-introspect.js and naming it using stg_<source_name>__<table_name>, then run dbt compile and dbt test --select staging to validate.

Frequently Asked Questions about staging-layer

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

FAQPage Schema
How do I standardize raw data into dbt staging models?▼

To standardize raw data into dbt staging models, use schema introspection to inspect source tables and apply strict renaming and casting rules to generate stg_<source_name>__<table_name> SQL files with 1:1 source mapping.

What is the correct dbt staging model naming convention for raw source tables?▼

The correct dbt staging model naming convention is stg_<source_name>__<table_name>, ensuring a strict 1:1 mapping from each raw source table to its corresponding staging model without joins or business logic.

Can I use schema introspection to generate sources.yml and schema.yml for dbt?▼

Yes, schema introspection reads existing raw source columns to generate sources.yml and schema.yml outputs. This avoids duplicate source definitions and ensures column stability during dbt staging layer creation.

How do I validate dbt staging models after onboarding new data sources?▼

Validate dbt staging models after onboarding new data sources by running dbt compile to check SQL generation and dbt test --select staging to enforce data quality and transformation rules on the staging layer.

Should I add joins or business logic in dbt staging models?▼

No, you should not add joins or business logic in dbt staging models. The staging layer enforces a strict 1:1 source-to-staging mapping to reduce downstream transformation errors by only applying renaming and casting.

Does the staging layer approach work for auditing existing dbt transformations?▼

Yes, the staging layer approach works for auditing existing transformations by using schema introspection to verify column stability and strict renaming rules against current stg_<source_name>__<table_name> models and sources.yml definitions.