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Job Listing Inventories — Record Quality Audit, String Normalisation & Base-100 Series
x402
Job Listing Inventories — Record Quality Audit, String Normalisation & Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs three analytical reports (record quality audit, string normalisation, and base-100 index series) on up to 200 rows of job listing inventory data containing listing counts and duplicate listing figures.
Price / call$0.01
Success—
StatusUnknown
How this service works
Job listing inventories — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied job listing inventories records (listing_count, duplicate_listings). 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 analytical reports: (1) a record quality audit flagging missing values, outliers, or malformed entries; (2) a string normalisation report standardising text fields like company_group and date; and (3) a base-100 index series for the selected numeric field (listing_count or duplicate_listings) anchored at the specified base row. All computed locally with no external lookups.
Example use cases
Weekly job listing data quality check
“I've collected a week's worth of job listing inventory rows across two company groups with listing_count and duplicate_listings values — can you audit the record quality, normalise the strings, and build a base-100 series on listing_count starting from the first row?”
Duplicate listing analysis for recruitment team
“Run a quality audit and base-100 series on my duplicate_listings figures across these 50 job listing inventory records grouped by company, starting the base index at position 0, so I can see which groups have data issues.”
Monthly inventory normalisation across company groups
“I have about 120 job listing inventory records for October 2026 across multiple company groups — please run all three reports (record quality audit, string normalisation, and base-100 series) on the listing_count field so I can clean up our dataset.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-13-201?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three analytical operations — quality audit, string normalisation, and base-100 indexing — applied to job listing inventory data in a single cost-efficient call. It is ideal for small-to-medium datasets (up to 200 rows) where no live external data, predictions, or professional assessments are required, and where the data is already collected and supplied by the caller.
Side effects
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, company_group, date, listing_count, or duplicate_listings) in any row
- Invalid date format (must be YYYY-MM-DD)
- base_index value out of range (must be 0–199 and within submitted row count)
- Payment failure — 0.01 USDC not successfully transmitted via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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