AI Product Description Generator: A Free Prompt Template and What to Look For

1. 01

   Any AI model can write a pleasant paragraph about a linen shirt. What matters happens before and after the writing.

2. 02

   A good ecommerce generator writes from your attributes, in your shoppers' words and your brand's voice, in every language you sell in, and flags missing facts instead of inventing them.

3. 03

   Bulk beats polish. A tool that writes one great description at a time won't fix 4,000 SKUs.

4. 04

   Publishing is part of the job. Copy stuck in a spreadsheet never reaches your store, your feed or the AI agents that read both.

5. 05

   For a handful of products, the prompt template below and any AI chat tool will get you most of the way.

Most free prompt lists ask for "a compelling, SEO-friendly description". That instruction is where invented details come from: a model told to be compelling with thin input fills the gaps. This template fences the model inside your facts and makes it report what's missing.

[ROLE]
You write product descriptions for [Brand], a [positioning, e.g. mid-price outdoor apparel brand] selling in [Market] in [Language].
[PRODUCT DATA: use only these facts]
Product type: [Product type]
Name and variant: [Product name], [Color], [Size range]
Materials or ingredients: [Composition with percentages]
Dimensions and weight: [Measurements with units]
Fit, compatibility or skin type: [Details]
Care: [Care instructions]
Certifications: [Certifications, or none]
In the box: [Contents]
Not suitable for: [Limitations]
[SHOPPER CONTEXT]
Target buyer: [Who buys it and the problem it solves]
Use cases: [3 to 5 situations]
Top customer questions: [Questions from reviews or support tickets]
Search terms: primary [Primary keyword]; secondary [2 to 4 related terms]
[BRAND RULES]
Tone: [Two or three adjectives]. Match this approved example: [Paste one approved description]
Always use: [Glossary terms, e.g. "merino wool" never "wool blend"]
Never use: [Banned words, e.g. best-in-class, premium quality]
Units: [e.g. metric first, imperial in parentheses]
[OUTPUT]
1. Title, max 150 characters: product type, brand, key attribute, variant.
2. Opening sentence, max 160 characters: product type, key attribute, main benefit.
3. Four to six bullets. Each starts with the benefit and ends with the fact that proves it.
4. Body, 60 to 150 words: attributes as full sentences, use cases, who it is not for.
5. FAQ: answer each top customer question in one or two sentences.
6. Attributes as key: value lines for material, color, size, pattern, gender, age_group.
[RULES]
Use only facts from PRODUCT DATA. If a fact you need is missing, write MISSING: [field name] and move on.
No prices, shipping, promotions or comparisons with other brands.
Plain text. No emojis, no exclamation marks, no HTML.
[END OF PROMPT]

How to fill it well

• Top customer questions is the field people skip and the one that pays off most. Pull five from reviews and support tickets. They become the FAQ, often in the exact phrasing shoppers use in AI prompts.
• Not suitable for feels wrong to marketers. Keep it. "Water-resistant, not waterproof" prevents a return and lets an agent rule you in or out honestly.
• The 160-character opening follows Google's advice to put the key details in the first 160 to 500 characters of a Merchant Center description, since shoppers must click to read the rest.
• Keep it plain text. The OpenAI product feed spec asks for a plain-text description of up to 5,000 characters and a title of up to 150.

A run that returns three MISSING lines did its job. Fix the data, not the wording. For category skeletons, use our product description templates.

We see these patterns constantly in catalogs written with a general-purpose tool. None of them shows up when you test a single product.

Common advice says every variant needs unique copy. We disagree for most catalogs. A sage and a navy version of one shirt should share a strong description, with variant facts in color, size and the title. Spend the effort on products that are actually different.

We'd also spend less time tuning prompts. A perfect prompt on three filled fields yields three facts. Completing the data is the faster gain.

What Google expects

Google's guidance on generative AI content calls it critical to manually fact-check AI content before publishing, and says AI-generated title and description attributes in Merchant Center must be labeled. For descriptions, that means structured_description with digital_source_type set to trained_algorithmic_media (Google). If both attributes are sent, Google uses description only, so a generator that fills both can undo your labeling.

We built AndromedAI for the catalog version of this problem. It has optimized more than 500 catalogs.

The Brand Kit holds your tone of voice, rules, examples, glossary and banned words. AI checks score every output; uncertain pages go to your team through approval workflows, and pages above 4.0 on the AI Checker can be approved automatically. Each language is generated for its market, which avoids the unit and sizing errors above (see ecommerce localization).

A few descriptions? Use the template. A catalog? Start with the audit.