When this tool helps
Use this before a ColorMe bulk product registration or update upload to review column count, encoding, required values, numeric fields, image settings, and listing status. Registration and update CSVs use different column counts, so first make sure you are validating the workflow you actually intend to run.
A 59-column and a 60-column CSV can look almost identical in a spreadsheet. If Excel drops trailing empty fields, the visible data can look fine while the importer still rejects the row count.
Auto mode is based on column count
Auto mode inspects early rows: 59 columns are treated as registration and 60 as update. If that cannot be inferred, selecting the intended mode manually is faster. You can also choose whether extra app columns are strict errors or allowed as additional columns.
So “Auto could not detect the mode” does not automatically mean the CSV is corrupt. Extra extension columns, missing trailing commas, and broken quoting are different causes that need different fixes.
The result goes beyond column count
The checker also validates standard-position fields it can interpret, including product name, numeric fields, image URLs, and listing status. For update CSVs, duplicate product IDs are worth reviewing because later rows can overwrite earlier data.
It does not claim that category names exist in your live store or that extension-specific columns are semantically valid. Those checks belong to the ColorMe management screen and the relevant app documentation.
A practical workflow
If you are reusing an older product CSV, first align it with the current official layout and column count. Then update only a few representative products and verify price, stock, images, and listing status before applying the same process to the full catalog.
A “wrong number of fields” error can come from trailing fields or quoting, not just bad cell values, so structure is the first place to look.