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Job Listing Inventories — String Normalisation + IQR Outlier Flags
x402
Job Listing Inventories — String Normalisation + 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 2026-11-02).
Normalises string fields and flags IQR-based outliers across listing_count and duplicate_listings fields in job listing inventory records (up to 200 rows, 2 reports).
Price / call$0.01
Success—
StatusUnknown
How this service works
Job listing inventories — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied job listing inventories records (listing_count, duplicate_listings). 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 per call: (1) string normalisation output for the company_group and date string fields, and (2) IQR-based outlier flags for the selected numeric field (listing_count or duplicate_listings) across the supplied rows. No external lookups or predictions are made; all analysis is performed locally on the submitted data.
Example use cases
Auditing duplicate listings across recruiters
“I have a dataset of job listing records by company group with listing_count and duplicate_listings columns — can you normalize the strings and flag any duplicate_listings values that are IQR outliers across my 150 rows?”
Cleaning job board inventory before reporting
“Before I send my job board inventory report to stakeholders, can you normalize the company_group strings and use IQR to flag any listing_count outliers in my 80-row dataset?”
Spotting anomalous posting surges by date
“I want to find which dates have unusually high listing_count values in my job inventory records — please normalize the string fields and run IQR outlier flagging on listing_count across these 120 rows grouped by company group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-13-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have job listing inventory records (with listing_count and/or duplicate_listings fields) and need both string normalisation and IQR-based statistical outlier detection in a single low-cost call. Ideal for pre-reporting data cleaning pipelines where you want to identify anomalous listing volumes without building custom statistical tooling. Best suited for datasets up to 200 rows where no live data lookup or predictive modelling is required.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, listing_count, duplicate_listings) cause validation errors
- Invalid date format (must match YYYY-MM-DD pattern) causes schema rejection
- Numeric values outside allowed range cause validation failure
- Insufficient data variance for meaningful IQR calculation may yield uninformative outlier flags
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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