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Record Routing Quality Audit and Numeric Row Ordering
x402
Record Routing Quality Audit and 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 2026-10-15).
Performs a data quality audit and numeric row ordering on up to 200 record routing rows (accepted_records, rejected_records) and returns two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering for supplied record routing records (accepted_records, rejected_records). 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 for the submitted rows: (1) a record quality audit assessing the supplied accepted_records and rejected_records values for data quality issues, and (2) a numeric row ordering report ranking the rows by the selected field (accepted_records or rejected_records). All analysis is performed locally on the supplied data — no external lookups or live data sources are used.
Example use cases
Daily pipeline acceptance rate audit
“I have a week's worth of record routing data across two dataset groups — can you run a quality audit and rank the rows by accepted_records? Here are 5 rows: row-1 on 2025-01-06 group-a 500 accepted 12 rejected, row-2 on 2025-01-07 group-b 480 accepted 30 rejected, row-3 on 2025-01-08 group-a 510 accepted 8 rejected, row-4 on 2025-01-09 group-b 490 accepted 22 rejected, row-5 on 2025-01-10 group-a 520 accepted 5 rejected.”
Rejection spike investigation
“My data team suspects there are quality issues in our routing pipeline last month — please audit these 6 routing rows for data quality and order them by rejected_records so I can see which days had the most rejections: row-1 2025-03-01 group-a 1000 accepted 50 rejected, row-2 2025-03-08 group-b 900 accepted 120 rejected, row-3 2025-03-15 group-a 950 accepted 30 rejected, row-4 2025-03-22 group-b 870 accepted 200 rejected, row-5 2025-03-29 group-a 980 accepted 15 rejected, row-6 2025-03-30 group-b 860 accepted 175 rejected.”
Multi-group routing comparison report
“Can you generate a quality audit and numeric ranking for these record routing records across three dataset groups, sorted by accepted_records? row-1 2025-06-01 group-alpha 300 accepted 5 rejected, row-2 2025-06-01 group-beta 450 accepted 20 rejected, row-3 2025-06-01 group-gamma 200 accepted 2 rejected, row-4 2025-06-02 group-alpha 310 accepted 8 rejected, row-5 2025-06-02 group-beta 430 accepted 25 rejected.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-007?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit AND a numeric row ordering on record routing data in a single low-cost call. It is best suited for ETL pipeline monitoring, data quality checks on routing acceptance/rejection counts, and batch analytical reporting on up to 200 rows at $0.01 USDC. It is not appropriate when you need live data lookups, external predictions, or professional assessments — it operates only on data you supply.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, dataset_group, accepted_records, rejected_records) causes a schema validation failure
- Invalid date format (not YYYY-MM-DD) is rejected by pattern validation
- Numeric values outside the allowed range (-1000000000000 to 1000000000000) are rejected
- Invalid field enum value (anything other than 'accepted_records' or 'rejected_records') causes an error
- Empty rows array is rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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