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Data Reconciliation Analytics — Record Quality Audit, String Normalisation & Category Frequencies
x402
Data Reconciliation Analytics — Record Quality Audit, String Normalisation & Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Runs three local analytical reports on supplied data reconciliation rows: a record quality audit, string normalisation, and category frequency analysis — all in a single paid call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied data reconciliation records (source_total, target_total). 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 analytical reports for the supplied rows: (1) a record quality audit flagging nulls, invalid formats, and completeness issues; (2) a string normalisation report standardising dataset_group and other string fields; (3) a category frequency table showing how often each dataset_group value appears. All computed locally with no external lookups.
Example use cases
Monthly reconciliation quality check
“I've got about 150 reconciliation rows for October 2026 with source and target totals across dataset groups like 'retail' and 'wholesale' — can you audit the record quality, normalise the group name strings, and tell me how frequently each category appears?”
Data pipeline validation before reporting
“Before I send this reconciliation dataset to finance, can you run a record quality audit and category frequency report on my 80 rows? Each row has a row_id, a date, a dataset_group, and source and target totals — I want to catch any nulls or malformed strings first.”
Comparing source and target totals across groups
“I have 200 reconciliation records split across 'group-a' and 'group-b' with dates from 2026-09-01 to 2026-09-30 — please run the quality audit, string normalisation, and category frequency analysis so I can see which groups have the most records and whether there are any data issues.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-195?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 reconciliation records with source and target totals and need a bundled analytical package covering quality auditing, string normalisation, and category frequency counting in a single low-cost call. It is ideal for data pipeline validation, pre-reporting QA, and categorical summarisation where no external data lookup or prediction is needed.
Side effects
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, source_total, target_total) in one or more rows — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric totals outside allowed range (±1,000,000,000,000) — rejected
- Empty rows array — minItems constraint violation
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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