# Forecast Verification Inputs — Exact Row Deduplication + Numeric Row Ordering

> Forecast Verification Inputs — Exact Row Deduplication + 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 2026-11-02).

Deduplicates exact rows and applies numeric ordering to forecast verification input records (forecast_value, observed_value) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-24-042?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-exact-row-deduplication-numeric-row-f8742c89
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pdCM1DtBt5IAZRC_WwP-A

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-exact-row-deduplication-numeric-row-f8742c89 -d '<json body>'
```

Example prompt: Can you deduplicate and numerically order my forecast verification records? I have up to 200 rows with forecast_value and observed_value fields — here are my rows: [{"row_id":"row-1","station_group":"group-a","date":"2026-10-01","forecast_value":10,"observed_value":1},{"row_id":"row-2","station_group":"group-b","date":"2026-10-02","forecast_value":20,"observed_value":2}], and I want to analyze the forecast_value field.

## When to prefer this

Choose this endpoint when you need to clean forecast verification datasets by removing exact duplicate rows and imposing numeric ordering on forecast_value or observed_value columns, particularly for batches up to 200 rows. Ideal for preprocessing weather forecast vs observed data pipelines before accuracy scoring. Not suitable if you need live forecast lookups, prediction generation, outlier flagging, or grouped summaries — those are handled by sibling endpoints on the same platform.

## Known failure modes

- Rows array is empty or missing — returns validation error
- More than 200 rows submitted — exceeds maxItems limit
- Row missing required fields (row_id, date, forecast_value, observed_value) — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected by pattern validator
- Numeric values outside allowed range (-1e12 to 1e12) — schema rejection
- Invalid field enum value (not forecast_value or observed_value) — rejected
- Payment not included or insufficient USDC — 402 payment required response

## How this service works

Forecast verification inputs — Exact row deduplication + Numeric row ordering: Exact row deduplication + 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

Returns 2 independent analytical reports based on the supplied rows: one covering exact row deduplication results (identifying and removing exact duplicate records) and one covering numeric row ordering of the specified field (forecast_value or observed_value), processed entirely via 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-exact-row-deduplication-numeric-row-f8742c89/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)