The merchant is choosing between templates while the assortment itself varies in size, attributes and image formats. In this case, the immediate task is to choose a collection-page template suited to the assortment. The output should be a shortlist matched to those properties, with any layout depending on attributes the catalog lacks rejected.
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.
Act as a Shopify operations specialist.
Help me choose a collection-page template suited to the assortment.
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: [assortment size, the attributes that vary across those products, image aspect ratios and file sizes present in the set, the filters the merchant requires, and the current template with its known layout constraints]. Match those properties to each candidate template, rejecting any layout that depends on an attribute the catalog leaves empty or on uniform image dimensions the set does not have, and marking a template provisional when its suitability hinges on product data the merchant has not yet supplied.
Return a collection-page layout and copy brief verifying each recommended template against the supplied 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.Split the work into input, judgment, and deliverable phases. Verify each step's output before moving to the next.
Record the assortment size, the number of attributes that really vary across those products, the image aspect ratios and file sizes present in the set, the filters the merchant requires, and the template currently in use with its known layout constraints.
Match those properties to each candidate template, rejecting any layout that depends on an attribute the catalog leaves empty or on uniform image dimensions the set does not have, and marking a template provisional when its suitability hinges on product data the merchant has not yet supplied.
Deliver a shortlist of only the templates that survive, with the reason each one fits and each rejection was made, then verify the leading candidate against the collection holding the most uneven images before the same layout is applied anywhere else.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
The shape of the product data: how many items the set holds, which attributes vary and whether the images share one aspect ratio. A template that only looks right but relies on comparison fields the catalog lacks will fail the moment real products are loaded.
When shoppers must compare two or three attributes to choose, or when the set mixes portrait, square and landscape images. A dense grid crops precisely the difference that carries the decision, leaving products that look interchangeable.
Onto one representative collection first, then check the rendered page against the product list to confirm every filter, badge and variant still displays. Only after that pass should the layout be extended to further collections.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
Ciwi Spark builds Shopify-native AI tools and agents around the workflows merchants actually run: research, ads, translation, and customer support. Stop rewriting the same prompts by hand.