The Scenario
You are a platform engineer. A new backend engineer is joining on Monday. Today is Thursday.
Your Supabase project has forty-three tables across three schemas. The new engineer needs a data dictionary before day one — every table name, column name, data type, and nullable flag. Your team has never written this down.
The slow version of Friday:
- You open the Supabase dashboard and navigate to the table editor
- You screenshot twenty tables, paste them into a doc
- You realize screenshots do not capture data types cleanly
- You switch to the SQL editor and write a query against
information_schema.columns - You run it, copy the output, paste it into a sheet
- The column names are
column_name,data_type,is_nullable— cryptic to a junior engineer - You spend an hour reformatting and adding friendly column headers
- You send it Saturday morning and it is still not quite right.
The fast version is one prompt.
The Easy Way: One Prompt in SheetXAI
SheetXAI reads your Supabase schema directly and writes the data dictionary into the sheet, so you do not have to write information_schema queries or reformat output by hand.
Open the SheetXAI sidebar and type:
List all tables in my Supabase project abc123. For each table, write the table name, schema, column name, data type, and nullable flag into this sheet — one row per column. Use readable headers: Table, Schema, Column, Type, Required. Sort by table name then column name.
SheetXAI calls Supabase's schema API, walks every table and column, and writes the full data dictionary with the headers you asked for.
What You Get
A complete data dictionary in the sheet:
- One row per column — not one row per table
- Readable headers — Table, Schema, Column, Type, Required
- Sorted — by table name, then column name within each table
- All forty-three tables — nothing skipped
The new engineer does not need database credentials to read a Google Sheet. She can explore the full schema structure before her first commit.
Want a second tab with just the table names and row counts? Ask SheetXAI to add it in the same session.
What If the Schema Is Not Quite Ready to Document
Supabase schemas accumulate technical debt. SheetXAI handles cleanup and documentation in the same prompt.
When table names use inconsistent naming conventions
Some tables use snake_case, some use camelCase, some have numeric suffixes from migrations.
List all tables in Supabase project abc123 and write the data dictionary into this sheet. Add a column called "Naming Issue" and flag any table or column names that are not lowercase snake_case.
When you only want the public schema
The project has three schemas and you only want to document public.
List all tables in the public schema of Supabase project abc123 and write the full column-level data dictionary into this sheet. Exclude the auth and storage schemas.
When you want foreign keys documented too
The new engineer needs to understand relationships, not just columns.
List all tables in Supabase project abc123 and write the data dictionary into this sheet. Add a Foreign Key column showing which column references which table, if any, and leave it blank for non-FK columns.
When you need schema documentation plus a summary per table
Table-level column counts, an estimate of purpose, and a full column list — in one shot.
List all tables in Supabase project abc123. Write the full column-level data dictionary into the Columns tab. Then in the Tables tab, write one row per table showing table name, schema, column count, and a one-sentence plain-English description of what the table likely stores based on its column names.
The pattern: ask for the documentation shape you actually want, not just the raw data dump.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet, then ask it to document your Supabase schema. The Supabase integration is included in every SheetXAI plan. For related workflows, see how to run a cohort SQL query and pull results into a sheet or the Supabase in Google Sheets overview.