Order states have accumulated over time, so one order can sit in two places or stall until somebody notices it. In this case, the immediate task is to organize routine order handling using clear states. The workflow should produce an order handling workflow and test cases, with every state traced to the merchant's own order records.
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 organize routine order handling using clear states.
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: [every order state the store applies with its agreed meaning, the entry and exit condition recorded per state, the orders whose latest state event is older than the review window, and the merchant's stated ageing limit]. Merge states that share an entry condition into one named state with a single owner, define the exit condition of each surviving state as an event that can be observed in the order record, and mark as stalled any order whose latest event predates the merchant's stated ageing limit.
Return an order handling workflow and test cases 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.
Collect, for one merchant-defined review window, every order state the store currently applies with the meaning agreed for each one, the entry and exit condition recorded for it, and the orders whose latest state event is older than the window, reading the state from the order record itself rather than from a saved view or an export filter.
Merge states that share an entry condition into one named state with a single owner, define the exit condition of each surviving state as an event that can be observed in the order record, and mark as stalled any order whose latest event predates the merchant's stated ageing limit.
Deliver an order handling workflow with a test case for each state, reconcile the count of orders in every state with the order export for the same window, and list separately each state that cannot be traced to an order record.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
An order counts as stalled when its latest state event is older than the merchant's stated ageing limit and no exit event has been recorded, so the check reads event timestamps rather than how long somebody believes the order has been open; an order still inside the limit stays routine even if it feels slow to the team.
They are merged into one state carrying the entry condition both already shared, and the retired name is recorded so historical orders can still be read; merging happens only on identical entry conditions, which keeps an order from being relabelled into a state with a different owner.
Every state in the workflow is matched to orders in the export for the review window and the per-state counts are summed back to the total order count, since a diagram never exercised against records hides states nobody actually uses; a state with no matching order is removed or flagged as untraceable rather than left on the diagram.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
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