Data Warehouse Discovery & Schema Mapper FAQs

Question 1

How often should I run the /data:init command?

Accepted Answer

You should run it during initial project setup and whenever your database schema undergoes significant changes to ensure the local metadata remains synchronized.

Question 2

Does it support large-scale databases?

Accepted Answer

Absolutely. It includes logic to identify tables with over 100 million rows and flags them so that Claude knows to apply mandatory filters, preventing expensive or slow queries.

Question 3

How does this skill improve Claude's data analysis capabilities?

Accepted Answer

It provides Claude with a detailed map of your data warehouse, including table descriptions and column types, which allows the AI to write more accurate SQL queries without guessing schema names.

Question 4

Where does the skill store the discovered schema information?

Accepted Answer

It generates a .astro/warehouse.md file in your project root, which is designed to be committed to version control so your entire team can share the context.

Question 5

Can it read my dbt project documentation?

Accepted Answer

Yes, it automatically scans for dbt YAML models and SQL files with frontmatter to extract business descriptions and primary key information to enrich the warehouse reference.

Data Warehouse Discovery & Schema Mapper

Key Features

Use Cases

Data Warehouse Discovery & Schema Mapper

Key Features

Use Cases