# Forecast Verification Inputs — Record Quality Audit + Grouped Numeric Summary

> Forecast Verification Inputs — Record Quality Audit + Grouped Numeric Summary 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).

Runs a record quality audit and a grouped numeric summary on up to 200 rows of forecast_value/observed_value pairs, returning two analytical reports computed locally.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-24-005?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/forecast-verification-inputs-record-quality-audit-grouped-numeric-ca5d2083
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lLEtuwTNCCauPzxzMUFth

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-record-quality-audit-grouped-numeric-ca5d2083 -d '<json body>'
```

Example prompt: Can you audit the quality of these forecast verification records and give me a grouped numeric summary by station group? I have up to 50 rows with row_id, station_group, date, forecast_value, and observed_value — I want to check for data issues and see summary stats grouped by group.

## When to prefer this

Choose this endpoint when you have tabular forecast verification data (forecast vs observed pairs) and need both a data quality check and grouped descriptive statistics in a single API call at low cost. It is best suited for pre-analysis validation of weather or numeric prediction datasets grouped by a categorical field, where no live data lookup, external prediction, or professional assessment is needed. Avoid if you need real-time forecast data, model training, or more than 200 rows processed at once.

## Known failure modes

- Empty rows array or missing required fields (row_id, date, forecast_value, observed_value) causes validation error
- Exceeding 200 rows returns an error about maxItems constraint
- Malformed date strings not matching YYYY-MM-DD pattern cause schema rejection
- Null values in forecast_value or observed_value are accepted but may reduce summary completeness
- Payment failure via x402 protocol prevents endpoint execution

## How this service works

Forecast verification inputs — Record quality audit + Grouped numeric summary: Record quality audit + Grouped numeric summary 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: (1) a record quality audit flagging issues such as nulls, out-of-range values, and duplicate row IDs across the submitted rows; and (2) a grouped numeric summary (counts, means, distributions) of forecast_value and observed_value broken down by station_group. Both reports are computed locally from the supplied 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",
     "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-record-quality-audit-grouped-numeric-ca5d2083/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)