Explore tables and columns before you write SQL
Inspecting schemas across multiple databases typically requires different tools and interfaces. You can use a single command path to list connections, inspect tables and columns, and refresh metadata after upstream changes. This keeps schema information consistent and accessible across sources.
How it works
Step 1 — Pick the connection
What data sources are connected in this workspace, and what short name should I use for each when I run commands?Step 2 — Inspect tables and columns
On our finance database, list tables whose names start with “revenue.” For each one I need every column: its name, type, and whether blank values are allowed.Step 3 — After the database schema changes
Finance changed their database structure—refresh my catalog here so what I see matches what’s actually there now.connections refresh runs catalog reconciliation in the background—wait for it to settle before you rely on tables list for new DDL.
Step 4 — Page through a wide catalog
Give me a browseable snapshot: up to 50 tables from finance with full column details so I can skim what exists.Who uses this
- People writing SQL or filters after confirming names and types.
- Engineers building table-picker UIs against workspace catalog output.
- Teams validating renames before releasing dashboards.
- Agent tooling that limits generated SQL to columns present in listings.