Step 1
Take each SKU's sellable stock at the reporting moment, its recorded sales over the demand window the merchant names, the returns and adjustments falling inside that window, and the unit or cost basis the figure is stated in.
Replenishment decisions are made without knowing how long stock lasts at the recorded demand rate. In this case, the immediate task is to estimate remaining inventory coverage in days. The workflow should produce an inventory health analysis and prioritized actions, dividing available stock by the stated demand rate and labelling the result an estimate.
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 estimate remaining inventory coverage in days.
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: [sellable stock per SKU at the reporting moment, recorded sales and returns inside the merchant's chosen demand window, and the unit or cost basis the figure is stated in]. Divide sellable stock by the average daily demand observed in that window, report rather than divide the SKUs that recorded no demand at all by showing their stock with an undetermined coverage label, and note beside any figure whose window caught a promotion or a stockout.
Return an inventory health analysis and prioritized actions 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.
Take each SKU's sellable stock at the reporting moment, its recorded sales over the demand window the merchant names, the returns and adjustments falling inside that window, and the unit or cost basis the figure is stated in.
Divide sellable stock by the average daily demand observed in that window, report rather than divide the SKUs that recorded no demand at all by showing their stock with an undetermined coverage label, and note beside any figure whose window caught a promotion or a stockout.
Deliver an inventory health analysis listing coverage days with the window and demand rate used on every row, label each figure an estimate, add prioritized actions, and reconcile sellable stock with the current inventory export before publishing.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Because it assumes the demand rate observed inside the window continues unchanged. A promotion, a stockout or one large order distorts that rate, so the number is published as an estimate with the window stated beside it rather than as a promise about when stock runs out.
It is given no coverage number at all, since dividing by zero demand produces an infinite figure that outranks every other SKU and hides the real problem. Its stock on hand is reported with an undetermined label and the SKU is routed to the dead or slow stock review instead.
Only where the merchant's policy says so, and then in a separate column, because folding an expected receipt into current coverage makes a SKU look safe today. The estimate column stays sellable stock on hand, and the expected receipt appears with its own date.
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.