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Spark playbook scenarios · Spark: AI Store Assistant

Draft AI-assisted descriptions grounded in product facts

New listings need copy before launch, and drafting it freely risks claims the attribute records cannot support. In this case, the immediate task is to draft AI-assisted descriptions grounded in product facts. The workflow should produce drafted descriptions with unsupported points marked, verified against the merchant's records.

Topic
Product Titles and Descriptions
Target keyword
shopify ai product descriptions
Copyable AI prompt

A prompt you can drop directly into Spark

First replace every [bracketed] placeholder with real store scope and constraints, then add any actual records or data you have, and paste it into your preferred AI assistant or Spark agent. Spark will follow this page's workflow to produce structured output and verification steps.

ai-prompt.txt
Act as a Shopify operations specialist.
Help me draft AI-assisted descriptions grounded in product facts.
My store context is [describe the business, products and target audience].

My scope is [specify the affected products, pages, customers or reporting period]. Use these inputs: [verified attribute records per product, brand voice rules with banned words, the target audience definition, and the pre-approved claims list].

Draft copy only from those inputs, grounding each benefit in a cited attribute, and mark every desirable statement that no supplied fact supports as an unverified claim requiring merchant sign-off before it can appear.
Return drafted descriptions with unsupported points marked, verified against the merchant's records for the specified task.
Show the relevant evidence or before-and-after examples and explain how I can verify the result.
If essential data is missing, ask for it and mark unsupported conclusions as unknown.
Do not invent metrics, product claims or customer facts.
For any publication, message, account or store change, use only connected tools within my explicitly authorized scope and report success only after verification; otherwise provide the draft or proposed steps.
Use in Spark
How to solve

A recommended resolution workflow

Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.

01

Step 1

Gather each product's verified attribute record, the brand voice rules with tone and banned words, the target audience definition, and the claims the merchant has already approved for the catalog.

02

Step 2

Draft copy only from those inputs, grounding each benefit in a cited attribute, and mark every desirable statement that no supplied fact supports as an unverified claim requiring merchant sign-off before it can appear.

03

Step 3

Deliver drafts with an attribute citation per sentence and a separate flagged-claims list, then verify that no sentence lacks a citation and that every flagged claim is absent from the published draft until confirmed.

FAQ

Common questions when running this scenario

Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.

Why keep flagged claims out of the live draft?

An unverified claim published by default becomes the merchant's liability for returns and disputes, so flagged statements wait for explicit sign-off; the citation trail shows exactly which facts each remaining sentence stands on.

How does brand voice get enforced in drafting?

The tone rules and banned-word list are supplied with the request and checked after drafting, so wording that drifts from the stated voice is corrected before delivery rather than discovered catalog-wide after publication.

What is checked before a draft ships?

Every sentence must cite an attribute that appears in the product record, and the flagged-claims list must be resolved or explicitly deferred by the merchant; drafts missing either check are returned rather than published.

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Next step

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