# Land Parcel Observations — Record Quality Audit + Category Frequencies

> Land Parcel Observations — Record Quality Audit + Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Runs two local analytical reports on land parcel observation data: a record quality audit and category frequency counts for up to 200 rows of area/perimeter measurements.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-14-006?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/land-parcel-observations-record-quality-audit-category-frequencies-fe4aa3f5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_TwHhLbVUaymAnjTJOLKBx

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 land-parcel-observations-record-quality-audit-category-frequencies-fe4aa3f5 -d '<json body>'
```

Example prompt: Can you audit the quality of these land parcel records and give me a category frequency breakdown by station_group? I have 4 rows with fields row_id, date, area_m2, perimeter_m, and station_group — for example row-1 on 2026-10-01 in group-a with area 10 m² and perimeter 1 m.

## When to prefer this

Choose this endpoint when you need simultaneous data quality auditing and category frequency analysis on land parcel observation records (area_m2, perimeter_m) in a single low-cost call. It is ideal for pre-ingestion validation of survey or GIS datasets, offline/local analysis without external API dependencies, and when you need both quality flags and station_group frequency summaries in one response for up to 200 rows at $0.01 USDC.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, area_m2, perimeter_m, station_group) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Payment not provided or insufficient USDC causes 402 response

## How this service works

Land parcel observations — Record quality audit + Category frequencies: Record quality audit + Category frequencies for supplied land parcel observations records (area_m2, perimeter_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 record quality audit identifying issues such as null values, out-of-range numbers, or malformed dates across each row's area_m2 and perimeter_m fields; and (2) category frequency counts showing how often each distinct station_group value appears in the supplied dataset. Both reports are computed locally on the submitted data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "area_m2",
     "perimeter_m"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "area_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "perimeter_m": {
      "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",
     "area_m2": 10,
     "perimeter_m": 1,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "area_m2": 20,
     "perimeter_m": 2,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "area_m2": 15,
     "perimeter_m": 3,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "area_m2": 30,
     "perimeter_m": 4,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/land-parcel-observations-record-quality-audit-category-frequencies-fe4aa3f5/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)