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Invoice Ageing Record Quality Audit, String Normalisation & Numeric Row Ordering
x402
Invoice Ageing Record Quality Audit, String Normalisation & Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs three local analytical reports on invoice ageing data: a record quality audit, string normalisation, and numeric row ordering by outstanding_amount or age_days — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Invoice ageing — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied invoice ageing records (outstanding_amount, age_days). 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 for the submitted invoice ageing rows: (1) a record quality audit identifying missing, null, or out-of-range values; (2) a string normalisation report standardising instrument_group and other string fields; and (3) a numeric row ordering report ranking rows by the specified field (outstanding_amount or age_days). All processing is done locally with no external lookups.
Example use cases
Pre-reporting invoice data quality check
“Before I send this month's accounts receivable report, can you audit these 120 invoice ageing rows for quality issues, normalise the instrument_group strings, and order them by age_days so I can spot the oldest outstanding amounts first?”
Cleaning messy invoice export from ERP
“I exported 80 invoice ageing records from our ERP and the group names look inconsistent — can you run a string normalisation and record quality audit on them, and also sort the rows by outstanding_amount descending?”
Flagging bad rows before finance dashboard load
“We're about to load 200 invoice ageing rows into our dashboard and I want to catch any bad data first — please run the record quality audit, normalise the strings, and give me the rows ordered by age_days.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-07-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC), self-contained batch analysis of invoice ageing data covering quality auditing, string normalisation, and numeric ordering in a single call — without needing live lookups, predictions, or external integrations. Ideal for pre-processing invoice exports before loading into dashboards or sending to stakeholders.
Side effects
- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — exceeds maximum, request rejected
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required field (row_id, instrument_group, date, outstanding_amount, or age_days) — schema error
- Field enum value not 'outstanding_amount' or 'age_days' — rejected
- Numeric values outside allowed range (-1e12 to 1e12) — validation error
- Payment not included or insufficient USDC — 402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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