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Supplier Qualification Data Quality Suite (Audit + Normalisation + Missing-Value Fill)
x402
Supplier Qualification Data Quality Suite (Audit + Normalisation + Missing-Value Fill) is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Runs three data-quality reports on supplier qualification records: a record quality audit, string normalisation, and explicit missing-value fill for checked_criteria and met_criteria fields — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Supplier qualification — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill 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 data-quality reports for up to 200 supplier qualification rows: (1) a record quality audit flagging malformed, incomplete, or out-of-range records; (2) a string normalisation report standardising company_group and other string fields; and (3) a missing-value fill report showing imputed values for the selected field (checked_criteria or met_criteria) using the chosen method (zero, mean, or median). All analysis is performed locally with no external lookups or predictions.
Example use cases
Pre-onboarding supplier data cleanse
“Before we onboard these suppliers, run a quality audit and string normalisation on my 120 qualification records, and fill any missing met_criteria values using the mean — I need to know which rows have issues.”
Quarterly procurement data governance check
“I need to validate our Q3 supplier qualification data for the audit committee — can you run all three quality reports on these 80 rows and use zero-fill for any missing checked_criteria fields?”
Fixing a messy imported vendor dataset
“We just imported 150 supplier qualification rows from a legacy system and the data is messy — please normalise the company_group strings, audit record quality, and impute any missing met_criteria using the median so we can compare vendors fairly.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-02-208?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, low-cost ($0.01 USDC for all three reports) data-quality pass on supplier qualification records — specifically combining quality auditing, string normalisation, and missing-value imputation in a single call. Ideal for batch pre-processing of up to 200 rows before downstream analytics or vendor onboarding workflows. Not suitable when you need live external data lookups, predictive scoring, or professional procurement assessment.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, company_group, checked_criteria, met_criteria) causes row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Values outside numeric bounds (-1e12 to 1e12) are rejected
- Invalid enum value for field or method parameters causes a 400-style error
- Empty rows array returns an error (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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