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Case-pack Order Rounding – Sequential Input-Change Attribution
x402
Case-pack Order Rounding – Sequential Input-Change Attribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Performs waterfall/sequential input-change attribution analysis for case-pack order rounding, showing how changes in required_units or case_units between two states drive rounding differences.
Price / call$0.01
Success—
StatusUnknown
How this service works
Case-pack order rounding - Sequential input-change attribution: Sequential input-change attribution for Case-pack order rounding. Supplied retail figures only, up to 200 records. No platform access, live rates or order execution. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded sequential input-change attribution report.
Output
A bounded sequential input-change attribution report (up to 200 records) that decomposes the rounding difference between the before and after case-pack states, attributing the impact step-by-step to changes in required_units and case_units.
Example use cases
Explain order quantity rounding shift
“My required units went from 25 to 28 and my case size stayed at 12 — can you run a sequential attribution on the case-pack rounding to show me what changed and why?”
Case size change impact on rounding
“I changed my case size from 12 to 13 while keeping required units at 25 — do a waterfall attribution to show how that case size change affected the rounded order quantity.”
Joint input change decomposition
“Both my required units and case size changed — before it was 25 units, case size 12; after it's 28 units, case size 13. Run the sequential input-change attribution so I can see which variable was responsible for more of the rounding difference.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-retail-case-pack-rounding-waterfall?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to understand *why* a case-pack rounded order quantity changed between two states, attributing the delta sequentially to individual input changes. Prefer it over the before/after comparison endpoint when you want a step-by-step waterfall breakdown rather than just a side-by-side diff.
Side effects
- case_units must be at least 1 — zero or negative values will be rejected
- required_units or case_units exceeding 1,000,000 will fail validation
- missing required_units or case_units in either before or after object returns a validation error
- additional properties in the before/after objects are not allowed and will cause rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | object | |
| before | object |
Tags
x402
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