# Page Extraction Coverage — String Normalisation + Date by Category Pivot

> Page Extraction Coverage — 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 2026-10-30).

Runs two local analytical reports (string normalisation and date-by-category pivot) on page extraction coverage data containing extracted_fields and expected_fields, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-web-02-035?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/page-extraction-coverage-string-normalisation-date-by-category-pivot-b12ab3e5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_77kyr49qhRCsyWKA9ktxY

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 page-extraction-coverage-string-normalisation-date-by-category-pivot-b12ab3e5 -d '<json body>'
```

Example prompt: Can you run string normalisation and a date-by-category pivot on my page extraction coverage records? I have rows with site_group, date, extracted_fields, and expected_fields — up to 50 rows — and I want both reports focused on the extracted_fields column.

## When to prefer this

Use this endpoint when you need two fast, local analytical transformations — string normalisation and a date-by-category pivot — on page extraction coverage data with up to 200 rows, without needing live lookups, external predictions, or professional assessments. It is ideal for data quality pipelines that need to clean field labels and summarise numeric extraction metrics grouped by site category and date, all for a fixed low cost of $0.01 USDC.

## Known failure modes

- Rows array is empty or exceeds 200 items — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- extracted_fields or expected_fields values outside allowed numeric range — rejected
- Missing required fields (row_id, site_group, date) — request rejected
- Invalid field enum value (not extracted_fields or expected_fields) — schema error

## How this service works

Page extraction coverage — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied page extraction coverage records (extracted_fields, expected_fields). 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 string normalisation report that cleans and standardises text fields (e.g. site_group) across the submitted rows, and (2) a date-by-category pivot table aggregating the selected numeric field (extracted_fields or expected_fields) grouped by date and site_group category. Both reports are computed locally against the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/page-extraction-coverage-string-normalisation-date-by-category-pivot-b12ab3e5/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)