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Land Parcel Observations — Record Quality Audit + String Normalisation + Grouped Numeric Summary
x402
Land Parcel Observations — Record Quality Audit + String Normalisation + 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 2026-10-29).
Runs three local analytical reports on up to 200 land parcel observation records: a record quality audit, string normalisation, and a grouped numeric summary of area or perimeter measurements.
Price / call$0.01
Success—
StatusUnknown
How this service works
Land parcel observations — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied land parcel observations records (area_m2, perimeter_m). 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: (1) a record quality audit flagging malformed, missing, or out-of-range values; (2) string normalisation output for the station_group field; and (3) a grouped numeric summary (statistics by station_group) for the selected numeric field (area_m2 or perimeter_m). All processing is local — no external lookups or predictions.
Example use cases
Parcel survey data quality check
“I've got 150 rows of land parcel observations with area_m2 and perimeter_m values collected in the field — can you audit them for quality issues, normalise the station_group strings, and give me a grouped numeric summary of area_m2 by station group?”
Cleaning messy station group labels
“My parcel dataset has inconsistently formatted station_group labels across 80 rows. Can you run the string normalisation and quality audit reports on these records so I know what needs fixing before I load them into the database?”
Grouped perimeter analysis by zone
“I need a grouped numeric summary of perimeter_m values across my land parcel records — 60 rows broken into different station groups. Can you also run the quality audit at the same time to flag any bad rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-14-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 land parcel observation records and need three bundled analytical reports — quality audit, string normalisation, and grouped numeric summary — in a single low-cost call. It is ideal for pre-ingestion data validation or exploratory analysis of field survey data where no external lookup, live data, or predictive modelling is needed.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, station_group, date, area_m2, perimeter_m) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Selecting an invalid field value (not 'area_m2' or 'perimeter_m') returns an enum error
- Empty rows array is rejected (minItems: 1)
- Numeric values outside ±1,000,000,000,000 are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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