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Supplier Qualification — Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean
x402
Supplier Qualification — Record 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 analytical reports on supplier qualification records: a record quality audit, string normalisation, and a secondary-measure weighted mean for checked_criteria or met_criteria fields across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Supplier qualification — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean 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
Three analytical reports for the submitted supplier qualification rows: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) a string normalisation report standardising text fields like company_group; (3) a secondary-measure weighted mean computation for the selected field (checked_criteria or met_criteria) across rows. All reports are generated from the supplied data with no external lookups.
Example use cases
Procurement data quality check
“I have a CSV of supplier qualification records with checked_criteria and met_criteria for about 80 rows across three supplier groups — can you audit the record quality and normalise the string fields so I can spot any bad data before we finalise the vendor list?”
Weighted pass-rate analysis by group
“Run a secondary-measure weighted mean on my supplier qualification dataset — I've got 120 rows with met_criteria and checked_criteria, grouped by company, and I want to see how each group performs on the met_criteria field.”
Monthly supplier review data prep
“Before our monthly supplier review, can you do a full quality audit and string normalisation on these 200 supplier qualification records and give me the weighted mean for checked_criteria so I can present clean numbers to the team?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-02-205?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical operations (quality audit, string normalisation, and weighted mean) on supplier qualification data in a single call at low cost. It is ideal for batch preprocessing supplier records before procurement decisions, reporting, or data pipeline ingestion, especially when no external data enrichment or prediction is needed.
Side effects
- Rows array empty or exceeds 200 items — validation error returned
- date field does not match YYYY-MM-DD pattern — row rejected
- checked_criteria or met_criteria values outside ±1,000,000,000,000 range — validation error
- field enum value not 'checked_criteria' or 'met_criteria' — bad request
- Payment of 0.01 USDC not confirmed — 402 response blocking execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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