A TOOLFRED WORKED EXAMPLE
Check a product CSV before an import.
Find repeated IDs, a missing SKU, a negative price and fractional stock. Use a small practice file to see what the checks can—and cannot—tell you.
SKU,Product,Category,Price,Stock
001,Linen tote,Bags,24.00,18
001,Ceramic mug,Home,-5.00,2.5
,Desk tray,Home,18.00,9
1. Keep the original and choose the real rules.
Work on a copy of an actual export. Check the destination’s current import template first: required columns, supported values and identifier rules can differ. This lesson assumes SKU is a required unique identifier, Price must be a plain decimal at least zero, and Stock must be a whole number.
Our tools keep values such as 001 as text. A spreadsheet can still change them when opening a downloaded CSV. Import identifier columns as text when you need to preserve leading zeros.
2. Inspect the IDs.
Open the CSV duplicate checker, choose the practice CSV and select SKU. Run the check. Record 1 and record 2 share 001; record 3 has a blank SKU. The checker reports affected records. It does not decide which record to delete or invent a replacement ID.
3. Apply four explicit checks.
Open the CSV rule checker and choose the same file. Review the proposed rules before running: SKU required, SKU unique, Price minimum 0, and Stock whole number. The built-in sample contains the same three records, so you can use “Try a sample” instead of downloading.
| Data record | Expected issue |
|---|---|
| 1 | SKU 001 appears twice. |
| 2 | SKU 001 appears twice; Price −5.00 is below 0; Stock 2.5 is not a whole number. |
| 3 | SKU is missing. |
Expected result: 5 issues across 3 failed records, with 0 passed records. A record can have several issues. Record numbers refer to data records after the header and skipped empty physical lines, not necessarily a spreadsheet’s visible line numbers.
To reuse this setup, expand Reuse these rules in the checker and choose Create rule file, then Download rule file. For reference, view the four practice rules as JSON →. Read a CSV first, then choose Load rule file. Column names must match exactly; a rule file never changes your spreadsheet-safety choice.
4. Review the source, then check the correction.
In this fictional lesson, the correct second SKU is 002, its price is 36.00 and stock is 2; the third SKU is 003. Those values are chosen for the example. For real data, confirm corrections against the source of truth rather than guessing IDs or rounding stock automatically.
Download the reviewed example CSV ↓
Run the reviewed file with the same four rules. Expected result: 0 issues, 3 passed records. This establishes only that these specific checks pass. It does not verify business facts, a destination’s complete schema, tax treatment or platform acceptance.
5. Prepare the next step deliberately.
Use the column mapper if the destination needs different header names or a different column order. For two later exports with valid unique IDs, the CSV comparison tool can show added, removed and changed records. It will reject the original practice file’s ambiguous IDs; fix or resolve them first.
Keep your original files and review the report before changing a live catalogue. An export report is evidence about the selected checks, not permission to overwrite production data.
Where the boundaries are
These tools handle bounded UTF-8 CSV files in your browser. They do not connect to a shop, upload the source file to Toolfred, validate every possible import rule or correct your data automatically. Read each tool’s Formats and limits before a larger job. No account or subscription is needed.