# Forecast Verification Inputs — String Normalisation + Numeric Row Ordering

> Forecast Verification Inputs — String Normalisation + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-09).

Normalises string fields and orders rows numerically for up to 200 forecast verification records (forecast_value, observed_value), returning 2 analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-24-025?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-09
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/forecast-verification-inputs-string-normalisation-numeric-row-ordering-f399f113
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lJP3bkIuwGaOpVf5DgN6B

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 forecast-verification-inputs-string-normalisation-numeric-row-ordering-f399f113 -d '<json body>'
```

Example prompt: Can you normalise the string fields and sort these forecast verification rows numerically by forecast_value? I have 4 records: row-1 for group-a on 2026-10-01 with forecast 10 and observed 1, row-2 for group-b on 2026-10-02 with forecast 20 and observed 2, row-3 for group-a on 2026-10-03 with forecast 15 and observed 3, and row-4 for group-b on 2026-10-04 with forecast 30 and observed 4 — give me both analytical reports.

## When to prefer this

Choose this endpoint when you need lightweight, local string normalisation and numeric row ordering specifically for forecast verification data (forecast_value / observed_value pairs) without requiring live weather lookups, predictions, or external data enrichment. Best suited for pre-processing pipelines where you want two bundled reports cheaply ($0.01 USDC for up to 200 rows) rather than building custom sort/normalise logic.

## Known failure modes

- More than 200 rows submitted — request rejected at maxItems constraint
- Invalid date format not matching YYYY-MM-DD pattern — validation error
- Missing required fields (row_id, station_group, date, forecast_value, observed_value) — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — rejected
- Empty rows array — minItems:1 violation
- Invalid field enum value — must be 'forecast_value' or 'observed_value'

## How this service works

Forecast verification inputs — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied forecast verification inputs records (forecast_value, observed_value). 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 analytical reports per call: one applying string normalisation to text fields (e.g. station_group) and one ordering up to 200 rows by the selected numeric field (forecast_value or observed_value), using local analytical engines with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/forecast-verification-inputs-string-normalisation-numeric-row-ordering-f399f113/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)