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Savings Ledger — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Savings Ledger — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Audits record quality, normalises strings, and computes daily sum series for savings ledger rows (deposit_amount or withdrawal_amount) across up to 200 rows, producing 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Savings ledger — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied savings ledger records (deposit_amount, withdrawal_amount). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports: (1) a record quality audit flagging issues such as missing, null, or out-of-range values across the supplied rows; (2) a string normalisation report cleaning and standardising the instrument_group and other string fields; and (3) a daily sum series aggregating the chosen numeric field (deposit_amount or withdrawal_amount) by date. All computed locally with no external lookups.
Example use cases
Monthly savings deposit audit
“I have 50 rows of savings ledger data for October. Can you audit the record quality, normalise the instrument group labels, and give me a daily sum series for deposit_amount? Here are the rows with row IDs, dates in YYYY-MM-DD format, instrument groups, deposits, and withdrawals.”
Withdrawal trend summarisation
“Can you run all three reports — record quality audit, string normalisation, and daily sum series — on my savings ledger entries, focusing on the withdrawal_amount field? I have about 120 rows covering Q3.”
Detecting dirty savings records
“My savings ledger has inconsistent instrument group names and possibly missing or malformed amounts across 80 rows. Can you audit the data quality and normalise the strings for me, plus show me the daily deposit totals over that period?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-23-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have savings ledger rows with deposit and withdrawal amounts and need all three of: data quality auditing, string field normalisation, and a daily aggregated sum series in a single $0.01 call. It is ideal for batch offline analysis of up to 200 rows without needing live data, external APIs, or professional financial assessments.
Side effects
- Rows exceeding 200 items will be rejected (maxItems constraint)
- Missing required fields (row_id, date, deposit_amount, withdrawal_amount, instrument_group) will cause validation errors
- Dates not matching YYYY-MM-DD pattern will fail schema validation
- Numeric amounts outside ±1,000,000,000,000 will be rejected
- Empty rows array (minItems: 1) will fail
- Invalid field enum value (only 'deposit_amount' or 'withdrawal_amount' accepted)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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