# Forecast Verification Inputs — Record Quality Audit + Exact Row Deduplication + Daily Sum Series

> Forecast Verification Inputs — Record Quality Audit + Exact Row Deduplication + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Runs three local analytical reports (record quality audit, exact row deduplication, and daily sum series) on up to 200 forecast verification input rows containing forecast and observed values.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-24-215?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/forecast-verification-inputs-record-quality-audit-exact-row-2afe3ac6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_drLE4qvw6eUfTjntssxnd

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-exact-row-2afe3ac6 -d '<json body>'
```

Example prompt: Can you run a record quality audit, exact duplicate check, and daily sum series on my forecast verification data? Here are up to 200 rows with row_id, station_group, date, forecast_value, and observed_value fields — I want all three reports on the forecast_value column.

## When to prefer this

Use this endpoint when you need a combined three-in-one batch analysis pass over forecast verification data without any external lookups or live predictions. It is ideal when you already have paired forecast and observed numeric records and want simultaneous quality auditing, deduplication, and daily aggregation in a single low-cost call. Prefer this over building individual analysis pipelines when your dataset is under 200 rows and turnaround speed matters.

## Known failure modes

- Empty rows array or more than 200 rows causes validation failure
- Rows missing required fields (row_id, date, forecast_value, observed_value) are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation errors
- Invalid field selector (not 'forecast_value' or 'observed_value') returns an error
- Payment failure via x402 protocol blocks execution

## How this service works

Forecast verification inputs — Record quality audit + Exact row deduplication + Daily sum series: Record quality audit + Exact row deduplication + Daily sum series for supplied forecast verification inputs records (forecast_value, observed_value). 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 on the supplied forecast verification rows: (1) a record quality audit flagging null values, out-of-range entries, and structural issues; (2) an exact row deduplication report identifying and listing duplicate records; and (3) a daily sum series aggregating either forecast_value or observed_value by date across all rows.

## 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-exact-row-2afe3ac6/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)