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Elevation Samples — Record Quality Audit + String Normalisation + Grouped Numeric Summary
x402
Elevation Samples — 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 2026-11-02).
Runs three local analytical reports on elevation sample records: a record quality audit, string normalisation, and grouped numeric summary for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Elevation samples — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied elevation samples records (elevation_m, sample_weight). 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 reports for the submitted elevation sample records: (1) a record quality audit identifying missing, invalid, or malformed entries; (2) normalised versions of string fields such as station_group; and (3) a grouped numeric summary of the selected numeric field (elevation_m or sample_weight) aggregated by station_group. All processing is done locally with no external lookups.
Example use cases
Pre-analysis elevation data quality check
“I have 120 rows of elevation sensor readings with station_group, date, elevation_m, and sample_weight. Can you run a record quality audit on them and flag any bad or incomplete records before I use them in my model?”
Grouped elevation statistics by station
“I need a grouped numeric summary of my elevation_m readings broken down by station_group. Here are 80 sample records with row_id, station_group, date, elevation_m, and sample_weight — please compute the group-level stats.”
String normalisation for station labels
“My elevation dataset has inconsistent station_group labels — mixed casing, extra spaces, etc. Can you normalise those strings and also give me a data quality audit across the 60 rows I'll send?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-13-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and grouped numeric summary on elevation sample data in a single $0.01 call, without requiring any live data lookup or external computation. It is well suited for pre-processing pipelines where you want to validate, clean, and summarise up to 200 elevation records in one step.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, station_group, date, elevation_m, sample_weight) on any row causes rejection
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Null numeric values are accepted but may affect summary statistics
- Payment not included or insufficient USDC causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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