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Supplier Qualification — Record Quality Audit + String Normalisation + Trailing Mean Series
x402
Supplier Qualification — Record Quality Audit + String Normalisation + Trailing Mean Series 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 trailing mean series calculation, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Supplier qualification — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series 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 reports derived from the supplied rows: (1) a record quality audit flagging completeness and formatting issues, (2) a string normalisation report cleaning company_group values, and (3) a trailing mean series for the selected numeric field (checked_criteria or met_criteria) over the specified window. No external data is fetched; all analysis is performed on the submitted data.
Example use cases
Procurement data quality check
“I have 150 supplier qualification records with company_group, date, checked_criteria, and met_criteria. Can you audit their data quality, normalise the company group strings, and calculate a trailing mean over checked_criteria with a window of 5?”
Compliance criteria trend analysis
“Run a trailing mean series on the met_criteria field across my supplier qualification rows — there are about 80 rows — using a window of 4, and also include the quality audit and string normalisation reports.”
Supplier onboarding data review
“I'm reviewing a new batch of supplier qualification submissions — 60 rows — and need a quality audit to flag missing or malformed fields, string normalisation on the company group names, and a rolling mean of checked_criteria with window size 2.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-02-199?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to perform three types of offline analytics (quality audit, string normalisation, trailing mean) simultaneously on supplier qualification records in a single low-cost call, without needing live data lookup, prediction, or external integrations. Ideal for batch data hygiene and trend analysis on pre-collected supplier compliance datasets of up to 200 rows.
Side effects
- Fewer than 1 or more than 200 rows submitted — request rejected
- Missing required fields (row_id, company_group, date, checked_criteria, met_criteria) in any row — validation error
- Date values not matching YYYY-MM-DD pattern — schema rejection
- Window value outside 2–200 range — validation error
- Numeric values outside allowed range (-1e12 to 1e12) — schema rejection
- Non-numeric or null values in selected numeric field may affect mean series output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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