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Supplier Qualification Data Quality Suite — Record Audit + String Normalisation + Two-Measure Correlation
x402
Supplier Qualification Data Quality Suite — Record Audit + String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Runs three local analytical reports on supplier qualification row data: a record quality audit, string normalisation, and correlation between checked_criteria and met_criteria fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Supplier qualification — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied supplier qualification records (checked_criteria, met_criteria). 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 generated locally from the supplied rows: (1) a record quality audit identifying malformed, missing, or out-of-range values; (2) a string normalisation report cleaning company_group and other text fields; and (3) a two-measure correlation report quantifying the statistical relationship between checked_criteria and met_criteria across up to 200 input rows.
Example use cases
Procurement team batch quality check
“I have 80 supplier qualification records with checked_criteria and met_criteria scores across different company groups and dates — can you audit them for data quality issues, normalise the company group strings, and tell me how correlated the two criteria measures are?”
Supplier onboarding data validation
“Before we onboard these 30 new suppliers, can you run a record quality audit and string normalisation on our qualification dataset and also check whether checked_criteria and met_criteria are correlated?”
Monthly supplier scorecard analytics
“I need three reports on this month's supplier qualification data — a quality audit to catch bad rows, normalised company group names, and a correlation between how many criteria were checked versus how many were met across 120 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-02-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined local analytical operations — record quality auditing, string normalisation, and two-measure statistical correlation — on a batch of up to 200 supplier qualification rows in a single cost-effective $0.01 USDC call. Prefer this over single-report endpoints when all three analyses are needed simultaneously. It performs no live lookups, external enrichment, or prediction, so it is suitable for offline/batch data hygiene and QA workflows.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, checked_criteria, met_criteria) cause row-level rejection
- Dates not matching YYYY-MM-DD pattern are flagged or rejected
- Null numeric values in both measure fields may degrade correlation output
- Empty row array returns an error (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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