# Export Validation — String Normalisation + Date by Category Pivot

> Export Validation — String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Runs two local analytical reports on export validation data: string normalisation of a chosen metric field and a date-by-category pivot, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-14-035?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/export-validation-string-normalisation-date-by-category-pivot-fe9173d5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_DDywD7DdmiF0UGa6uqP3U

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 export-validation-string-normalisation-date-by-category-pivot-fe9173d5 -d '<json body>'
```

Example prompt: I have 150 export validation records with columns row_id, dataset_group, date, valid_rows, and exported_rows — can you run the string normalisation and date-by-category pivot reports on the valid_rows field?

## When to prefer this

Choose this endpoint when you need two simultaneous local analytics reports — string normalisation and date-by-category pivot — on export validation data (valid_rows/exported_rows) without requiring external lookups, live data, or predictions. It is cost-effective at $0.01 USDC for both reports on up to 200 rows. Prefer it over general analytics tools when your data is already structured as export validation records with date, group, and row-count fields.

## Known failure modes

- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, dataset_group, date, valid_rows, or exported_rows) on any row
- Date field not matching YYYY-MM-DD pattern — validation error
- Invalid field enum value — must be 'valid_rows' or 'exported_rows'
- Numeric values outside allowed range (±1,000,000,000,000)
- Empty rows array — minItems:1 not satisfied
- Payment failure via x402 protocol — endpoint returns 402

## How this service works

Export validation — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied export validation records (valid_rows, exported_rows). 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 independent analytical reports: (1) a string normalisation report for the selected metric field (valid_rows or exported_rows) and (2) a date-by-category pivot table showing the chosen metric broken down by date and dataset_group, computed locally from the supplied rows with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/export-validation-string-normalisation-date-by-category-pivot-fe9173d5/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)