A fixed pool of units has to be shared across one variant family, and today whoever edits first decides the split. In this case, the immediate task is to allocate a defined stock pool across eligible variants. The workflow should produce an inventory reconciliation and proposed correction file grounded in the merchant's own variant 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 allocate a defined stock pool across eligible variants.
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 pool definition and the units it contains, the merchant's variant eligibility rules, current per-variant levels and reservations, demand evidence per variant, and any shared component constraint]. Rank the eligible variants by their recorded demand evidence and allocate pool units down that ranking until the pool is exhausted, deducting reserved units first and stopping at the shared component limit, then record the shortfall against every variant receiving less than its demand evidence supports.
Return an inventory reconciliation and proposed correction file verified 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.
Collect the pool definition with the units it contains, the eligibility rules the merchant sets for variants in the family, current per-variant levels and reservations, the demand evidence recorded per variant, and any shared component constraint.
Rank the eligible variants by their recorded demand evidence and allocate pool units down that ranking until the pool is exhausted, deducting reserved units first and stopping at the shared component limit, then record the shortfall against every variant receiving less than its demand evidence supports.
Deliver an inventory reconciliation with one row per variant showing the allocated quantity, the demand behind it, the shortfall and the constraint that capped it, add a proposed correction file, and verify that allocated units sum to the pool and that no variant exceeds its available component and physical stock.
Cover decision rules, frequent misunderstandings, and required inputs so the team aligns on prerequisites before execution.
From the merchant's stated rules, usually recorded demand by size or colour and sometimes a channel or bundle commitment, never by splitting the pool evenly. An even split gives the weakest variant the same stock as the strongest and recreates the imbalance the allocation was meant to fix.
No; the allocation runs down the demand ranking and stops when the pool is empty, and each proposed quantity is checked against units physically held and against the shared component limit. An overallocation here becomes an oversell as soon as the storefront publishes it.
They stay in the file with an explicit zero and their shortfall recorded rather than being dropped, so the merchant can see which sizes or colours the pool could not cover. Where the pool is short across the board the report says so instead of spreading the shortfall invisibly.
Start with scenarios under the same topic, then expand into cross-topic matches suggested by similarity.
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