# Building Footprint Observations — String Normalisation + Base-100 Series

> 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.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-16-030?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/building-footprint-observations-string-normalisation-base-100-series-33ec5412
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_UyfJ4ry1Mzs4ZQzIFXANa

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability building-footprint-observations-string-normalisation-base-100-series-33ec5412 -d '<json body>'
```

Example prompt: I have 4 building footprint observations — row-1 (group-a, 2026-10-01, footprint 10 m², height 1 m), row-2 (group-b, 2026-10-02, footprint 20 m², height 2 m), row-3 (group-a, 2026-10-03, footprint 15 m², height 3 m), row-4 (group-b, 2026-10-04, footprint 30 m², height 4 m) — can you run string normalisation and a base-100 series on the footprint_m2 field starting from row index 0 and give me both reports?

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "footprint_m2",
     "height_m"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "height_m": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "footprint_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "height_m": 1,
     "footprint_m2": 10,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "height_m": 2,
     "footprint_m2": 20,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "height_m": 3,
     "footprint_m2": 15,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "height_m": 4,
     "footprint_m2": 30,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "footprint_m2",
    "height_m"
   ],
   "type": "string",
   "default": "footprint_m2"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/building-footprint-observations-string-normalisation-base-100-series-33ec5412/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)