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Savings Ledger String Normalisation and Keyed Dataset Comparison
x402
Savings Ledger String Normalisation and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Normalises strings and performs keyed dataset comparison on two sets of savings ledger records (deposit_amount, withdrawal_amount), returning two independent analytical reports for up to 200 rows each.
Price / call$0.01
Success—
StatusUnknown
How this service works
Savings ledger — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied savings ledger records (deposit_amount, withdrawal_amount). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: one covering string normalisation of the supplied savings ledger fields and one covering a keyed dataset comparison between the two supplied datasets, highlighting differences in deposit_amount and withdrawal_amount per row. No live data, predictions, or external lookups are included.
Example use cases
Reconciling two monthly savings exports
“I have two CSV exports of our savings ledger for October — one from our core system and one from the reconciliation team. Can you normalize the strings and compare them row by row by row_id and date to flag any differences in deposit_amount or withdrawal_amount? Each dataset has about 150 rows.”
Auditing instrument group deposit discrepancies
“We suspect some instrument groups in our savings ledger have inconsistent deposit amounts between our internal records and the third-party statement. Can you run a keyed comparison on both datasets — up to 200 rows each — and give me a normalisation plus difference report?”
Verifying savings data before month-end close
“Before we close out the month, can you compare our preliminary savings ledger against the final version? I need string normalisation applied and a keyed dataset comparison by row_id to identify any rows where withdrawal_amount or deposit_amount changed.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-23-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two structured savings ledger datasets and need both string normalisation and a keyed row-level comparison in a single low-cost call. It is ideal for reconciliation workflows, month-end audits, and data validation tasks where no live lookup or external prediction is needed and datasets fit within 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, instrument_group, date, deposit_amount, withdrawal_amount) — validation error
- Invalid date format (must match YYYY-MM-DD) — schema validation failure
- row_id values non-unique across dataset — comparison may produce ambiguous results
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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