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Record Routing Quality Audit + String Normalisation + Secondary-Measure Weighted Mean
x402
Record Routing Quality Audit + String Normalisation + Secondary-Measure Weighted Mean 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).
Runs three local analytical reports on record routing data — quality audit, string normalisation, and secondary-measure weighted mean — for up to 200 rows of accepted/rejected record counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean 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: (1) a record quality audit flagging data issues in the accepted/rejected record counts, (2) normalised versions of the string fields, and (3) a secondary-measure weighted mean computed over the selected field (accepted_records or rejected_records), all derived from the supplied rows without any external lookups.
Example use cases
Daily routing pipeline quality check
“I have yesterday's record routing batch — 5 groups with dates and accepted/rejected counts for each. Can you run a quality audit, normalise the string fields, and give me a weighted mean on the accepted_records so I can flag any anomalies before the next pipeline run?”
Comparing rejection rates across dataset groups
“I want to analyse rejected_records across my three dataset groups over the past week — can you run the quality audit and weighted mean reports using rejected_records as the target field so I can see which group has the worst rejection rate?”
Pre-reporting data normalisation for routing logs
“Before I send our monthly routing report to the team, can you normalise the string fields and compute the weighted mean for accepted_records across all 12 date rows in our routing log so the output is clean and consistent?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-205?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, offline analytical pass over record routing data combining quality auditing, string normalisation, and weighted mean computation in a single cheap call ($0.01 USDC for all three reports). Best suited for ETL pipeline monitoring, data quality gates, and pre-reporting normalisation where no external lookups or predictions are needed and data fits within 200 rows.
Side effects
- Exceeds 200-row limit — request rejected
- Missing required fields (row_id, date, accepted_records, rejected_records) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range — rejected
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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