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Geospatial Tile Processing Data Quality Suite
x402
Geospatial Tile Processing Data Quality Suite is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Audits record quality, normalises strings, and flags IQR outliers for geospatial tile processing datasets (tile_count, processing_seconds) — up to 200 rows, three reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Geospatial tile processing — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied geospatial tile processing records (tile_count, processing_seconds). 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 structured analytical reports per call: (1) a record quality audit highlighting missing, malformed, or invalid rows; (2) normalised string values for station_group and other string fields; (3) IQR-based outlier flags identifying rows where tile_count or processing_seconds fall outside the interquartile range. All computed locally without external lookups.
Example use cases
Pipeline data quality gate
“Before I push this batch of geospatial tile processing logs to production, can you run a full quality audit, normalise all the station_group labels, and flag any tile_count values that look like outliers using IQR? Here are 120 rows from November 2026.”
Outlier detection in processing times
“I've got 80 rows of tile processing records and I'm worried some processing_seconds values are way off — can you run the IQR outlier check on processing_seconds and also do the string normalisation and record quality audit while you're at it?”
Station group label cleanup
“My geospatial pipeline data has inconsistent station_group names across 45 rows — can you normalise those strings, do the record quality audit, and also check tile_count for IQR outliers so I know what needs fixing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-21-203?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, low-cost ($0.01 USDC) three-in-one data quality pass — record auditing, string normalisation, and IQR outlier detection — specifically for geospatial tile processing datasets. It is best suited for offline or pre-pipeline validation of up to 200 rows where no live lookups, predictions, or external data enrichment are required. Prefer alternatives if you need real-time geospatial lookups, ML-based anomaly detection, or datasets exceeding 200 rows.
Side effects
- Empty rows array or missing required fields (row_id, date, tile_count, processing_seconds) returns validation error
- More than 200 rows submitted exceeds maxItems limit and is rejected
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Non-numeric tile_count or processing_seconds outside allowed range rejected
- Invalid field enum value (anything other than tile_count or processing_seconds) causes request failure
- Payment not included or insufficient USDC results in 402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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