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File Ingestion Date-by-Category Pivot
x402
File Ingestion Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Generates a date-by-category pivot report for file ingestion records, summarizing a chosen numeric metric (loaded bytes or parse errors) broken down by source category across dates.
Price / call$0.01
Success—
StatusUnknown
How this service works
File ingestion - Date by category pivot: Date by category pivot for File ingestion. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded date by category pivot report.
Output
A date-by-category pivot report showing the selected numeric metric (loaded_bytes or parse_errors) aggregated by source category for each date present in the input records — a cross-tabulation suitable for local descriptive analytics with no forecasting or external enrichment.
Example use cases
Daily ingestion load by source
“I have a week's worth of file ingestion logs with sources like 'group-a' and 'group-b' — can you pivot the loaded_bytes field by date and source so I can see which group is moving the most data each day?”
Parse error trend by category
“Here are 50 ingestion records from last month across three source categories. Pivot the parse_errors metric by date and source so I can spot which category has the worst error days.”
Multi-source ingestion health check
“I'm running a daily ingestion pipeline with multiple sources. Can you take these 120 records and generate a date-by-category breakdown of loaded_bytes so I can compare throughput across sources over the past two weeks?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-file-ingestion-pivot?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 typed file ingestion records and need a quick local pivot of loaded_bytes or parse_errors broken down by source category and date, with no requirement for external data enrichment or forecasting. It is best for lightweight, on-demand descriptive analytics on ETL or ingestion pipeline data at minimal cost ($0.01 USDC).
Side effects
- Input array is empty or missing (minItems:1 violated)
- More than 200 rows supplied (maxItems:200 exceeded)
- Date strings not matching YYYY-MM-DD pattern
- row_id missing or exceeds 80 characters
- field enum value not one of loaded_bytes or parse_errors
- Numeric fields out of allowed range (-1e12 to 1e12)
- Payment not attached or insufficient USDC balance
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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