Metadata Manager FAQs

Question 1

What does the Metadata Manager skill do?

Accepted Answer

The Metadata Manager skill automates the creation and maintenance of BigQuery table schemas (schema.yaml), metadata configurations (metadata.yaml), and Airflow DAG schedules. It ensures all data definitions follow standard ETL conventions while proactively filling in missing documentation and field descriptions.

Question 2

When should I use this skill?

Accepted Answer

Use this skill whenever you are creating new derived datasets, updating existing BigQuery table structures, or scheduling tasks via Airflow. It is also the go-to tool for coordinating test updates when SQL queries are modified to maintain data integrity across your pipeline.

Question 3

How does it improve my ETL workflow?

Accepted Answer

It eliminates manual boilerplate by auto-populating schemas from source tables and intelligently sourcing descriptions from the Glean Dictionary or DataHub. By automating DAG discovery and creation, it reduces configuration errors and ensures your data pipelines are scheduled correctly from day one.

Question 4

Can it handle missing field descriptions automatically?

Accepted Answer

Yes. The skill proactively detects missing descriptions and can auto-generate them using context from your queries. It also cross-references global base schemas to ensure standard fields like 'client_id' or 'submission_date' have consistent documentation across all tables.

Question 5

Is this skill compatible with other Claude Code capabilities?

Accepted Answer

Absolutely. It is designed to be composable, working seamlessly with 'bigquery-etl-core' for naming conventions, 'query-writer' for SQL development, and 'sql-test-generator' for maintaining robust test suites during schema changes.

Metadata Manager

Metadata Manager

Key Features

Use Cases

Key Features

Use Cases