Model Requirements Gatherer FAQs

Question 1

What does the Model Requirements Gatherer skill do?

Accepted Answer

This skill guides you through a structured interview process to define the business logic, grain, and technical dependencies for BigQuery data models. It automates the discovery of source tables and assesses potential downstream impacts before any code is written.

Question 2

What specific outputs does the skill provide?

Accepted Answer

The skill generates two primary artifacts: a detailed Requirements Document for stakeholders and condensed Working Notes tailored for developers. These include grain definitions, source table mappings, transformation logic, and scheduling patterns.

Question 3

How does this skill improve BigQuery data management?

Accepted Answer

It reduces breaking changes by performing automated downstream impact analysis and validates source table dependencies across local files, Glean Dictionary, and DataHub. This ensures high-quality ETL pipelines and clearer documentation for data teams.

Question 4

When should I use this skill in my workflow?

Accepted Answer

You should use this skill as a pre-planning step before writing SQL for new data models or whenever you need to modify existing queries in a bqetl environment. It ensures that all stakeholders' needs are captured and that architectural decisions are sound.

Question 5

Does this skill help with SQL generation?

Accepted Answer

While it doesn't write the SQL itself, it is designed to work composably with the query-writer skill. It provides the structured requirements and column suggestions needed for Claude to generate accurate, performant BigQuery SQL code.

Model Requirements Gatherer

Model Requirements Gatherer

소개

주요 기능

사용 사례

소개

주요 기능

사용 사례