Bulk product descriptions without duplication
Use when you need to write descriptions for many near-identical variants and each one must read differently.
Fill in before running
Replace each placeholder with your own detail. The more specific you are, the less the model invents.
- {{BRAND_NAME}}
- {{PRODUCT_CATEGORY}}
- {{PRODUCT_LIST_WITH_ATTRIBUTES}}
Getting a better result
- Feed 10 to 20 products per run. Past that the model starts recycling sentence shapes even with the rule in place.
- Paste back any two descriptions that read too alike and ask for one to be rewritten from a different lead attribute.
- Keep the MISSING column - it is usually faster to fill gaps in the feed than to rewrite the copy later.
Questions about this prompt
When should I batch descriptions rather than write them one at a time?
When you have a run of products whose attributes barely differ and a template would give you the same paragraph with one word swapped. Writing singly is fine for ten distinct products. Reach for this when the risk is not bad copy but identical copy, because the anti-duplication rules only bite when the model sees the whole set at once.
What should the product list contain, and how many rows per run?
A clean attribute line per product in {{PRODUCT_LIST_WITH_ATTRIBUTES}}, plus the brand and category. Keep the batch to ten or twenty rows, as the tips say, because the rule against repeating any sentence of eight or more words degrades once the set is longer than the model can hold in view.
What does the output table give me?
A table of SKU, description, bullet specs and a MISSING column. The copy is the deliverable, but MISSING is the column to read first: it lists the claims the model refused to invent from the attributes you gave it, and filling those gaps in the feed is faster than rewriting the copy later.
What goes wrong most often on a batch like this?
Reading the descriptions one at a time. Near duplication only shows when two rows sit side by side, which is what the tips mean about pasting back a pair that reads alike and asking for one to lead on a different attribute. The other costly habit is filling a MISSING gap with a plausible material instead of checking supplier data.