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Geospatial Tile Processing — Record Quality Audit + Adjacent Row Changes
x402
Geospatial Tile Processing — Record Quality Audit + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-31).
Runs two analytical reports on supplied geospatial tile processing records: a record quality audit and an adjacent row changes analysis, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Geospatial tile processing — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes for supplied geospatial tile processing records (tile_count, processing_seconds). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, or formatting problems in the supplied rows, and (2) an adjacent row changes report highlighting differences between consecutive rows for the selected field (tile_count or processing_seconds). No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Tile processing pipeline quality check
“I've got 120 rows of daily tile processing records — each with a row ID, station group, date, tile_count, and processing_seconds. Can you audit their quality and flag any adjacent row changes in tile_count?”
Station group anomaly detection
“Run a record quality audit and adjacent row changes analysis on these geospatial tile records for station groups alpha and beta — I want to see where processing_seconds jumps unexpectedly between consecutive rows.”
Pre-analysis data validation for tile dataset
“Before I hand this tile processing dataset off to my analytics team, can you run both the quality audit and the adjacent row changes report on it, focusing on the tile_count field across all 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-21-011?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local analytical reporting on geospatial tile processing records without requiring external data lookups or live predictions. It is best suited for small-to-medium datasets (up to 200 rows) where you want both a data quality audit and a consecutive-row change detection report in a single low-cost call ($0.01 USDC). Prefer it over general analytics platforms when the data is already structured with tile_count and processing_seconds fields and you need fast, deterministic results.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, tile_count, processing_seconds) — validation error
- Invalid date format (must match YYYY-MM-DD) — schema validation failure
- Field selector not one of allowed enum values — rejected
- Empty rows array — request rejected
- Payment not included or insufficient — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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