# Data Catalog Coverage — String Normalisation + Two-Measure Correlation

> Data Catalog Coverage — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).

Runs string normalisation and two-measure Pearson/Spearman correlation analysis on data catalog coverage records (documented_fields vs total_fields) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-21-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-catalog-coverage-string-normalisation-two-measure-correlation-bc8b694d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pmCe36dlevXBTI8OdktpB

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 data-catalog-coverage-string-normalisation-two-measure-correlation-bc8b694d -d '<json body>'
```

Example prompt: Can you run string normalisation and a two-measure correlation on my data catalog coverage records? I have 4 rows: row-1 on 2026-10-01 in group-a with 10 documented_fields and 1 total_fields, row-2 on 2026-10-02 in group-b with 20 documented_fields and 2 total_fields, row-3 on 2026-10-03 in group-a with 15 documented_fields and 3 total_fields, and row-4 on 2026-10-04 in group-b with 30 documented_fields and 4 total_fields.

## When to prefer this

Choose this endpoint when you need both string normalisation and two-measure statistical correlation on data catalog coverage fields (documented_fields vs total_fields) in a single call, without requiring external data lookups or predictions. It is best suited for batch analytical workflows on up to 200 rows of catalog metadata, where you want two distinct reports from shared local computation at minimal cost ($0.01 USDC per call).

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, documented_fields, total_fields) in any row — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values out of allowed range (±1,000,000,000,000) — rejected
- Insufficient data rows for meaningful correlation (e.g. only 1 row) — may return degenerate or undefined correlation

## How this service works

Data catalog coverage — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied data catalog coverage records (documented_fields, total_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

Returns two analytical reports: (1) a string normalisation report covering the dataset_group and other string fields, and (2) a two-measure correlation report quantifying the statistical relationship between documented_fields and total_fields across the supplied rows. Both reports are computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-catalog-coverage-string-normalisation-two-measure-correlation-bc8b694d/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)