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Vendor Evaluation — Daily Sum Series + IQR Outlier Flags
x402
Vendor Evaluation — Daily Sum Series + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes daily sum time series and IQR-based outlier flags for vendor evaluation records (supplied_score, maximum_score) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Vendor evaluation — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied vendor evaluation records (supplied_score, maximum_score). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports: (1) a daily sum time series aggregating the selected field (supplied_score or maximum_score) by date, and (2) IQR-based outlier flags identifying which dates or records fall outside the interquartile range, based on the supplied input rows. No external data is fetched; all analysis is performed on the provided records.
Example use cases
Quarterly vendor performance review
“I have 150 vendor evaluation rows for Q3 with supplied_score and maximum_score columns across multiple company groups — can you compute the daily sum series and flag any IQR outliers in the supplied_score field so I can spot which dates had abnormal scoring?”
Detecting anomalous procurement scoring days
“We received vendor bids scored daily across two supplier groups over the past month. Can you aggregate those scores by date and use IQR outlier detection on the maximum_score field to highlight which days had unusual totals?”
Multi-group vendor scorecard audit
“I need to audit our vendor evaluation data — I've got about 80 rows across company groups 'west-region' and 'east-region' with dates and supplied scores. Run the daily sum time series and IQR outlier flags on the supplied_score field and tell me which days look like statistical outliers.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-10-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a daily aggregated time series and IQR-based statistical outlier detection on vendor evaluation data in a single call. It is ideal for batch offline analysis of up to 200 pre-collected vendor scoring rows where no live data lookup or external enrichment is needed. Prefer it over generic analytics tools when working specifically with company-grouped vendor records containing supplied and maximum score fields.
Side effects
- Empty or missing rows array returns an error
- rows exceeding 200 items are rejected
- invalid date format (not YYYY-MM-DD) causes validation failure
- null values in supplied_score or maximum_score may affect aggregation results
- invalid field enum value (not 'supplied_score' or 'maximum_score') causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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