# Field Survey Coverage Analyzer — Record Quality Audit, String Normalisation & Trailing Mean Series

> Field Survey Coverage Analyzer — Record Quality Audit, String Normalisation & Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Runs three local analytical reports on field survey coverage data: a record quality audit, string normalisation, and a trailing mean time series — all without external lookups or predictions.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-22-199?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/field-survey-coverage-analyzer-record-quality-audit-string-d65a31e9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_AyjCkgPhIkK17BD7wFprA

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 field-survey-coverage-analyzer-record-quality-audit-string-d65a31e9 -d '<json body>'
```

Example prompt: Run a record quality audit, string normalisation, and trailing mean series with a window of 3 on my field survey coverage data — here are the rows with row_id, station_group, date, surveyed_m2, and target_m2 — use surveyed_m2 as the target field.

## When to prefer this

Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and compute a rolling mean on field survey coverage data (surveyed_m2/target_m2) in a single call. It is ideal for batch preprocessing up to 200 survey records before downstream reporting, without any need for external lookups or live data. Prefer it over generic analytics tools when working specifically with structured survey coverage datasets that have station_group and area measurement columns.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, station_group, date, surveyed_m2, target_m2) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Window size outside 2–200 range — parameter error
- Both numeric fields null for all rows — computation may return empty series
- Payment of 0.01 USDC not completed — 402 Payment Required response

## How this service works

Field survey coverage — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied field survey coverage records (surveyed_m2, target_m2). 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

Three independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, and malformed fields; (2) a string normalisation report cleaning station_group and other string fields; and (3) a trailing mean time series computed over the chosen numeric field (surveyed_m2 or target_m2) with the specified window size — all derived locally without external data sources.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "surveyed_m2",
     "target_m2"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "target_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "surveyed_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",
     "target_m2": 1,
     "surveyed_m2": 10,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "target_m2": 2,
     "surveyed_m2": 20,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "target_m2": 3,
     "surveyed_m2": 15,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "target_m2": 4,
     "surveyed_m2": 30,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "surveyed_m2",
    "target_m2"
   ],
   "type": "string",
   "default": "surveyed_m2"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/field-survey-coverage-analyzer-record-quality-audit-string-d65a31e9/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)