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Record Routing Quality Audit, String Normalisation & Numeric Row Ordering
x402
Record Routing 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 2026-10-23).
Runs three offline analytical reports on record routing data: quality audit, string normalisation, and numeric row ordering for accepted_records and rejected_records fields across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied record routing records (accepted_records, rejected_records). 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 supplied rows: (1) a record quality audit flagging issues in accepted_records or rejected_records, (2) string normalisation results for string fields such as dataset_group and row_id, and (3) a numerically ordered ranking of rows by the chosen field. All analysis is performed locally with no external lookups.
Example use cases
ETL pipeline record quality check
“I've got a batch of 50 record routing rows from our ETL pipeline with date, dataset group, accepted record counts, and rejected record counts — can you run a quality audit, string normalisation, and numeric ordering report on all of them focusing on the rejected_records field?”
Dataset group name cleanup
“Our routing dataset has inconsistent dataset_group strings and I need them normalised — can you run the string normalisation report along with the quality audit and numeric row ordering on these 30 rows using the accepted_records field?”
Rank routing rows by rejection volume
“I want to see my 80 record routing rows ordered numerically by rejected_records so I can spot which dataset groups have the most rejections — can you run the full three-report analysis on them?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled offline analytical operations — quality audit, string normalisation, and numeric ordering — on record routing data in a single low-cost call. Ideal for ETL pipelines, data validation workflows, or pre-processing steps where you have up to 200 routing records and want structured reports without any external lookups or predictions.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, accepted_records, rejected_records) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern cause rejection
- Numeric values outside ±1,000,000,000,000 boundary cause schema validation failure
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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