FBA Shipment Identifier Alias Map
Turn your carrier references and FBA shipment IDs into a review with clear source references.
Amazon seller operations
Put the events in your customer returns and warehouse events into date order.
A downloadable skill for your AI agent.
Unresolved item-status paths.
Source references, missing information, and questions to review stay with the findings.
Open your download and follow the start guide. Use an AI agent that can load skill files and run the included tools.
Customer returns and warehouse events. Confirm the case and period you want to check.
Copy the request below into your agent. Add the files and any task details it needs.
Check the findings against the original records. Choose where to save the report and follow up on open questions.
Use the FBA Return Disposition Timeline skill. Review the attached records: customer returns and warehouse events. Prepare this result: unresolved item-status paths. Include a source reference for each finding. List missing information and questions that need my review. Ask me to confirm the scope and where to save the report before you start.
It checks the supplied dates and time zones before ordering events. Unclear dates remain marked for review.
Customer returns and warehouse events.
For this task, keep one review row for each return unit + event. Record customer return, receipt, disposition, and availability. Keep the source location beside each value.
Link each unit and cost record to its shipment or case. Preserve prior reimbursement, reversal, removal, disposal, and received status.
Use the current supplied policy and documented cost basis. A candidate claim is not proof of eligibility or reimbursement value.
The helper does not infer causation, missing events, elapsed business days, or clock offsets. Equal timestamps do not establish event order.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | at: 2026-10-31T09:00:00; event: customer return recorded |
|---|---|
| Sample record | at: 2026-10-31T10:00:00+02:00; event: Earlier UTC event |
More information is needed
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"at": "2026-10-31T09:00:00", "event": "customer return recorded", "id": "r1", "key": "return unit + event / SYNTHETIC-001"}{"at": "2026-10-31T10:00:00+02:00", "event": "Earlier UTC event", "id": "r2", "key": "return unit + event / SYNTHETIC-001"}After purchase, extract the ZIP. Run these commands from the skill folder. Use a new output folder.
python3 scripts/checks.py
python3 scripts/audit.py assets/example.json \
--files-root assets/sample-files --output-dir example-result
Expected exit code: 2. Code 0 means no helper finding. Code 1 means a finding or review item. Code 2 means incomplete or invalid input.
The check uses the records you supply. Review each finding against the original documents.
Ask your agent to save the completed task report in a folder you choose. The report template includes the result, source references, missing information, and next actions.
Tonotes does not receive your work documents through this website. Documents you share with an AI service follow that service's storage settings.
US$11 includes one skill in a ZIP with 18 files. You receive the instructions and tools to run the task with your own records.
Use an agent that supports SKILL.md instructions and Python 3.10 or later with SQLite. Your AI-agent service is separate.
Start with customer returns and warehouse events. Confirm the case, period, and source versions before the review.
Use seller, marketplace, shipment, FNSKU or SKU, claim to keep records distinct. The agent records the original value, an exact quote, and the source location.
Check date precision and time zones, then order valid events. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: unresolved item-status paths. Include missing evidence, unresolved questions, and the next action for each open item.
Eight synthetic cases check the tool locally. Live-agent accuracy on real documents has not been tested.