Step 1
Collect the open operational questions, the orders, tickets or shipments each touches, the integration and app logs covering the affected period, the process steps involved, and the interventions the merchant has authorised.
Several operational problems are open at once, each sitting at a different step of a different process. In this case, the immediate task is to coordinate operational investigations and permitted actions. The workflow should produce an agent task plan and action log that traces each issue to its failing step and marks unresolved gaps with the record needed.
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 coordinate operational investigations and permitted actions.
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 open operational questions, the orders, tickets or shipments each touches, the integration and app logs for the affected period, the process steps involved, and the interventions the merchant has authorised]. Trace each issue to the specific step at which it fails by matching the order or ticket against that step's expected state, keep every intervention inside the authorised set, and hand back anything needing a permission or record not held.
Return an agent task plan and action log marking each unresolved gap with the record needed 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 the open operational questions, the orders, tickets or shipments each touches, the integration and app logs covering the affected period, the process steps involved, and the interventions the merchant has authorised.
Trace each issue to the specific step at which it fails by matching the order or ticket against that step's expected state, keep every intervention inside the authorised set, and hand back anything needing a permission or record not held.
Deliver the task plan and action log naming per issue the failing step, the supporting evidence, the action taken and its verification, marking each unresolved gap with the missing record or approval and the person able to supply it.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
Whenever the next step needs a permission, record or system it does not have. Guessing fills the gap with a plausible story and hides the fact that the investigation never had what it needed.
As open items naming the missing record or approval and who can provide it, never as settled, because anything closed without evidence in the log invites the same failure to recur.
Only where retries are explicitly permitted, logged and checked for idempotency against the affected record; repeated attempts can duplicate writes, and a retry that keeps succeeding at the wrong value turns a genuine failure into a quiet loop.
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.