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Job Listing Inventories — Record Quality Audit + Exact Row Deduplication + Grouped Numeric Summary
x402
Job Listing Inventories — Record Quality Audit + Exact Row Deduplication + Grouped Numeric Summary 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 local analytical reports on job listing inventory data: a record quality audit, exact row deduplication, and a grouped numeric summary of listing_count or duplicate_listings fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Job listing inventories — Record quality audit + Exact row deduplication + Grouped numeric summary: Record quality audit + Exact row deduplication + Grouped numeric summary 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 reports: (1) a record quality audit flagging missing, malformed, or invalid fields; (2) an exact row deduplication report identifying and removing fully duplicate rows; and (3) a grouped numeric summary (e.g. sum, mean, count) of the selected numeric field (listing_count or duplicate_listings) broken down by company_group.
Example use cases
Audit recruiter platform listing data
“I've got a batch of job listing inventory rows from our recruiter platform — can you run a record quality audit, deduplicate any exact duplicate rows, and give me a grouped numeric summary by company group on listing_count? Here are up to 100 rows with row_id, company_group, date, listing_count, and duplicate_listings.”
Identify duplicate job postings by company
“We suspect our job board has a lot of duplicate listings polluting our counts. Can you take these 80 inventory records and run exact row deduplication plus a grouped summary of duplicate_listings per company group so we can see where the problem is worst?”
Data quality check before analytics pipeline
“Before we feed our job listing inventory data into our analytics pipeline, can you run a quality audit and grouped numeric summary on these records — up to 150 rows — so we can catch missing values, bad formats, or exact duplicates? Summarize on listing_count grouped by company_group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-13-211?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured job listing inventory tabular data (up to 200 rows) and need all three of: a data quality audit, exact duplicate detection, and a grouped numeric summary — all in a single low-cost call. Ideal as a pre-processing step before loading data into a pipeline or dashboard. Not suitable for live job board lookups, predictive analytics, or datasets exceeding 200 rows.
Side effects
- Fewer than 1 row provided — minimum row count not met
- More than 200 rows submitted — exceeds maximum batch size
- Row missing required fields (row_id, company_group, date, listing_count, duplicate_listings) — validation error
- date field not in YYYY-MM-DD format — pattern mismatch error
- Invalid field selector not in enum [listing_count, duplicate_listings] — schema error
- Numeric values outside allowed range — validation rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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