Step 1
Start from the untouched original file, the adjustments the merchant requested, a reference for the product true colour and finish, and the output size and format the image must be delivered in.
Photographs shot under mixed lighting make products look unlike what buyers receive, and past corrections were ad hoc. In this case, the immediate task is to improve the presentation of an existing product photograph. The workflow should produce an edited file or a step brief, recording any colour, contrast or texture shift away from the true appearance.
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 improve the presentation of an existing product photograph.
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: [the untouched original file, the adjustments the merchant requested, a reference for the product true colour and finish, and the required output size and format]. Apply only the requested corrections and compare against the reference after each one, watching for shifts in colour, contrast, sharpness or texture that make the item look different from what the buyer will receive.
Return the edited file or a step brief 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.
Start from the untouched original file, the adjustments the merchant requested, a reference for the product true colour and finish, and the output size and format the image must be delivered in.
Apply only the requested corrections and compare against the reference after each one, watching for shifts in colour, contrast, sharpness or texture that make the item look different from what the buyer will receive.
Deliver the edited file or a step brief recording every adjustment applied, then compare it side by side with the original at the stated output size, note each shift away from the true appearance and leave the original in place until the merchant approves.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Those that restore the recorded appearance, such as levelling exposure, correcting a colour cast or removing a background flaw. Removing a real feature of the product, or smoothing a texture buyers judge the item by, goes beyond correction.
Against the reference the merchant supplies for that product colour and finish. Where no reference exists, mark the result as unconfirmed rather than matching it to a similar listing, which only repeats an unknown error.
Yes, keep the untouched file as the fallback. If a later complaint questions the colour or the finish, the original is the only record of what was actually shot, and it lets the edit be redone.
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.