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Building Footprint Observations — Duplicate Key Report + Adjacent Row Changes
x402
Building Footprint Observations — Duplicate Key Report + 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 2026-10-29).
Analyzes up to 200 building footprint observation records to produce two reports: a duplicate key report and an adjacent row changes report for footprint_m2 or height_m fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — Duplicate key report + Adjacent row changes: Duplicate key report + Adjacent row changes for supplied building footprint observations records (footprint_m2, height_m). 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 analytical reports: (1) a duplicate key report identifying rows with repeated key combinations among the supplied records, and (2) an adjacent row changes report showing where the selected field (footprint_m2 or height_m) differs between consecutive rows — all computed locally from the supplied data with no external lookups.
Example use cases
Audit building survey data for duplicates
“I've got a CSV of 120 building footprint observations with row IDs, station groups, dates, footprint_m2, and height_m values — can you run a duplicate key report on them and also flag where the footprint_m2 changes between consecutive rows?”
QA check on height measurement records
“Before I load this batch of 80 building height observation records into our database, can you check for any duplicate row keys and show me all the adjacent row changes in the height_m column?”
Detect sequential anomalies in footprint data
“I have a series of daily building footprint observations across several station groups — please run a duplicate key report and an adjacent row changes analysis on the footprint_m2 field so I can spot any data entry errors.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-062?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate a batch of building footprint observation records for data quality issues — specifically duplicate key detection and sequential value changes — without needing live data, predictions, or external enrichment. It is ideal for pre-ingestion data QA pipelines where two reports are needed in a single $0.01 call.
Side effects
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, station_group, date, footprint_m2, or height_m) in one or more rows
- Invalid date format (must match YYYY-MM-DD pattern)
- Invalid field selector (must be footprint_m2 or height_m)
- Empty rows array submitted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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