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Job Listing Inventories — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Job Listing Inventories — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs three analytical reports on job listing inventory data: record quality audit, string normalisation, and daily sum series aggregation for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Job listing inventories — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum 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 computed locally on the supplied data: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed rows; (2) a string normalisation report cleaning and standardising text fields like company_group; and (3) a daily sum series aggregating the chosen numeric field (listing_count or duplicate_listings) by date. All reports cover up to 200 input rows.
Example use cases
Daily listing count trends by company
“I have job listing inventory records for two company groups over the past month — can you aggregate them into a daily sum series for listing_count and also run a quality audit and string normalisation on the data? Here are the rows with row_id, company_group, date, listing_count, and duplicate_listings.”
Data quality check before reporting
“Before I send this job listing dataset to my manager, can you audit the record quality and normalise the company_group strings? I have about 80 rows with listing_count and duplicate_listings and I need to make sure there are no formatting issues or data problems.”
Duplicate listing trend analysis
“Can you run all three reports — quality audit, string normalisation, and daily sum series — on my job listing inventory data, focusing on the duplicate_listings field? I have around 120 rows covering several company groups and want to see the daily totals for duplicates.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-13-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and daily sum aggregation — on job listing inventory data in a single low-cost call. It is ideal for offline/batch data cleaning and summarisation pipelines where no live data lookup, prediction, or external action is needed, and where you want a cheap, deterministic computation on up to 200 rows of listing_count and duplicate_listings records.
Side effects
- More than 200 rows supplied — request rejected or truncated
- Missing required row fields (row_id, date, company_group, listing_count, duplicate_listings) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field selector not in allowed enum values — rejected
- Empty rows array — error response
- Numeric values outside allowed range — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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