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Job Listing Inventories — Record Quality Audit + String Normalisation + Numeric Distribution
x402
Job Listing Inventories — Record Quality Audit + String Normalisation + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of job listing inventory data containing listing counts and duplicate listing counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Job listing inventories — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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
Three independent analytical reports delivered together: (1) a record quality audit flagging missing values, invalid formats, and outliers; (2) a string normalisation report highlighting inconsistencies in text fields like company_group; (3) a numeric distribution report (min, max, mean, percentiles, etc.) for the selected numeric field (listing_count or duplicate_listings). All analysis is performed locally on the supplied rows with no external lookups.
Example use cases
Audit recruitment platform listing quality
“I have a batch of 50 job listing inventory records from our recruitment platform with company groups, dates, listing counts, and duplicate listing counts — can you run a full quality audit, string normalisation check, and numeric distribution report on the listing_count field for all of them?”
Detect data issues before dashboard load
“Before we load this week's job listing inventory data into our dashboard, can you audit these 80 rows for record quality problems, normalise the company_group strings, and give me a distribution breakdown of duplicate_listings values?”
Profile duplicate listings across employers
“We've got 150 rows of job listing inventory data across multiple employer groups — can you run the three analytical reports (quality audit, string normalisation, numeric distribution) focused on the duplicate_listings field so we can see where duplicates are concentrated?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-13-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous local data quality and profiling reports on job listing inventory records without any live data lookup or external enrichment. It is ideal for pre-processing pipeline validation, data cleaning workflows, or quick exploratory data profiling on batches of up to 200 rows. Prefer this over general-purpose analytics tools when you specifically need all three report types (quality audit, string normalisation, numeric distribution) in a single cheap call ($0.01 USDC) for the job listings domain.
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 (not YYYY-MM-DD) triggers schema validation failure
- field selector not one of the allowed enum values ('listing_count' or 'duplicate_listings') causes rejection
- All-null numeric field may produce empty or degenerate distribution report
- Empty rows array rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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