Monitor Amazon Refunds and Returns
Explain return volume, reasons, dispositions, concentration, listing-accuracy themes, and prior-period movement across FBA and merchant-fulfilled orders.
Use it for a clear operating job.
- High-return ASIN diagnosis
- Reason and disposition analysis
- Prior-period return monitoring
Quoting a return rate when shipped-unit denominators are missing or incompatible.
Start with the task, then add your scope.
Copy this into a connected client and replace the account, date, ASIN, or threshold details with yours.
Analyze our FBA and MFN returns for the last 90 days versus the prior period. Classify reasons, identify red-flag ASINs and listing-accuracy themes, and calculate return rate only where shipped units support it.A defined result, not a generic answer.
A reproducible returns report that separates controllable, remorse, operational, and other causes and identifies the ASINs that need action.
- FBA or MFN return records
- Shipped units when available
- Date range and comparison period
- Return-rate and reason analysis
- Red-flag ASIN list
- Markdown, workbook, or dashboard
Read the exact report it produces.
The report this Skill produced from a live 90-day FBA returns pull — 7,160 return units across 1,199 ASINs, anonymized but otherwise unedited.
The playbook your agent follows.
- 01
Acquire and inspect
Load the return report from your agent-ready data lake through Agent Flow MCP, then inspect its actual fields and coverage.
- 02
Normalize taxonomy
Map reasons and dispositions into a pinned, auditable classification.
- 03
Calculate carefully
Compute concentration, deltas, and return rate only when a valid shipped-unit denominator exists.
- 04
Render the deliverable
Produce the requested report format without recomputing the analytical result.
What keeps the workflow dependable.
The context and tools it coordinates.
Give your agent the complete playbook.
Connect Skills once, then start with the prompt above whenever this job comes up.