# Field Survey Coverage Analyzer — Category Frequencies & IQR Outlier Flags

> Field Survey Coverage Analyzer — Category Frequencies & IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Computes category-level frequency distributions and IQR-based outlier flags for field survey coverage records (surveyed_m2 and target_m2), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-22-107?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/field-survey-coverage-analyzer-category-frequencies-iqr-outlier-flags-0cae123b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0YBi998y24B2mxE14DeNz

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-category-frequencies-iqr-outlier-flags-0cae123b -d '<json body>'
```

Example prompt: Can you analyze my field survey coverage records and flag any IQR outliers in the surveyed_m2 field? I have rows for station groups like group-a and group-b from October 2026 — I want category frequency counts and outlier flags for up to 200 rows.

## When to prefer this

Use this endpoint when you have raw field survey coverage records (up to 200 rows) and need both a categorical frequency summary and IQR-based statistical outlier detection in a single call without any external data dependencies. Prefer this over general-purpose analytics tools when your data specifically involves surveyed_m2 and target_m2 measurements grouped by station and date, and you need two complementary reports (frequency + outlier flags) for a flat per-call fee.

## Known failure modes

- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, station_group, date, surveyed_m2, target_m2) in any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — rejected
- Empty rows array — minimum 1 item required
- Invalid field enum value (not surveyed_m2 or target_m2) — schema error

## How this service works

Field survey coverage — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied field survey coverage records (surveyed_m2, target_m2). 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) category frequency counts grouped by station_group for the selected field, and (2) IQR-based outlier flags per row identifying which records fall outside the interquartile range. Both reports are computed locally from the supplied rows with no external data lookups.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/field-survey-coverage-analyzer-category-frequencies-iqr-outlier-flags-0cae123b/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)