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Building Footprint Observations — String Normalisation + Base-100 Series
x402
Building Footprint Observations — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Performs string normalisation and base-100 index series analysis on up to 200 building footprint observation records (footprint_m2, height_m), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — String normalisation + Base-100 series: String normalisation + Base-100 series 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
Two independent analytical reports: (1) string-normalised representation of the selected field (footprint_m2 or height_m) across all supplied rows, and (2) a base-100 indexed series for that field anchored at the specified base_index row, covering up to 200 building observation records with row_id, station_group, and date metadata preserved.
Example use cases
Portfolio footprint trend indexing
“I have monthly footprint measurements for 12 buildings across two station groups and I want to see a base-100 index for footprint_m2 starting from the first observation, plus string-normalised labels — can you run both reports on these 12 rows?”
Building height normalisation audit
“Can you normalise the height_m values in my 50 building observation records and produce a base-100 series anchored to row index 0? I need both the normalisation report and the index series to compare heights across station groups.”
Cross-group footprint baseline comparison
“I've got 80 rows of building footprint data split across group-a and group-b with dates and footprint_m2 values — please run string normalisation and generate a base-100 series for footprint_m2 from base index 0 so I can compare growth across groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-030?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw building footprint or height observation records (up to 200 rows) and need both string normalisation and a base-100 index series computed locally without any external lookups, predictions, or live data — especially when you want two distinct analytical views (normalised strings + indexed series) from a single low-cost call. It is not appropriate when you need live building data, geospatial lookups, predictive modelling, or more than 200 rows processed at once.
Side effects
- More than 200 rows submitted — request rejected at maxItems limit
- Missing required row fields (row_id, date, footprint_m2, height_m) — validation error
- base_index out of range for the number of submitted rows — error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in the selected field may affect base-100 computation — partial or error result
- Payment not settled (x402) — request blocked before processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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