Viewing & Editing Data

Once your schema is ready, you'll spend most of your time looking at actual rows — debugging, fixing typos, exploring what your app is producing. HeroMate gives you two ways to do that: a spreadsheet-style view for normal edits, and a full SQL editor for anything more.

Browsing rows

Click any table in the Database tab to see its rows.

The row view works like a spreadsheet:

• Click a cell to edit. Press Enter to save, Esc to cancel.
• Click a column header to sort.
• Right-click a row for delete, duplicate, and copy options.
• Page through rows with the pager — rows are paginated (default page size 10, with a 10 / 25 / 50 / 100 selector), not an infinite scroll.

Changes save immediately. There's no "unsaved changes" state to worry about.

Filtering and searching

Use the filter panel above the grid to narrow things down:

• Stack multiple filters — they're combined with AND
• Pick from common operators per column type (=, !=, >, <, contains, in)
• Filters are URL-encoded so you can share a filtered view with a teammate

For full-text search, use the SQL editor — the filter panel is for exact matches and ranges.

The SQL editor

For queries the visual editor can't express, there's a full SQL console. Open it from the SQL button above any table or at the top of the Database tab.

Things you can do here:

• Run any SELECT, INSERT, UPDATE, DELETE on public
• Run CREATE TABLE, ALTER TABLE, CREATE INDEX for schema changes
• Inspect system schemas (read-only) — useful for checking users, roles, endpoint metadata

Recent queries are saved per project so you can re-run them later.

Exporting data

From the row view, click Export in the toolbar. You can download the data as:

• CSV — one row per record, headers included. Good for spreadsheets.
• JSON — array of objects. Good for feeding into scripts or other apps.
• SQL — INSERT statements you can replay into another database.

You can also Copy as CSV / JSON / SQL straight to your clipboard for quick paste. Exports respect the current filter — so you can filter to "tasks done this week" and export just those.

Bulk-loading data

There's no built-in CSV import yet (it's coming). To load data in bulk today:

• SQL — run INSERT statements (or paste the SQL you exported elsewhere) in the SQL editor.
• Ask your AI — your AI client can read and edit rows over MCP with execute_sql, and the local @dypai-ai/mcp package adds bulk_upsert to load many rows from a file at once.

What NOT to edit manually

Some schemas are read-only for good reasons. Don't try to modify them directly:

You can read from them freely (SELECT * FROM system.users), just don't write.

Next steps