# Null Coverage Analytics — String Normalisation + Numeric Row Ordering

> Null Coverage Analytics — String Normalisation + 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 2026-10-10).

Normalises string fields and orders rows numerically for null coverage records (missing_values, total_values), producing 2 independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-025?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-10
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-string-normalisation-numeric-row-ordering-71cb132b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-szErKS8M8K-7mgNxN2o7

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 null-coverage-analytics-string-normalisation-numeric-row-ordering-71cb132b -d '<json body>'
```

Example prompt: Can you run the null coverage analytics on my dataset records — normalise the dataset_group strings and order the rows by missing_values? I have 4 rows: row-1 group-a 2026-10-01 with 10 missing out of 100, row-2 group-b 2026-10-02 with 20 missing out of 200, row-3 group-a 2026-10-03 with 5 missing out of 150, row-4 group-b 2026-10-04 with 30 missing out of 300.

## When to prefer this

Choose this endpoint when you need lightweight, offline null coverage analytics — specifically string normalisation of group labels and numeric ordering of rows by missing or total value counts — for datasets of up to 200 rows, without requiring any external data lookup, live prediction, or professional assessment. It is ideal for data quality pipelines, ETL audit workflows, or completeness reporting where you want two structured reports for a flat cost of $0.01 USDC.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) causes rejection
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Numeric values outside allowed range (-1e12 to 1e12) are rejected
- Invalid field enum value (not missing_values or total_values) causes error
- Empty rows array (minItems:1 violated) returns an error

## How this service works

Null coverage — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied null coverage records (missing_values, total_values). 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 independent analytical reports: (1) a string normalisation report for the specified field across the submitted rows, and (2) a numeric row ordering report sorted by the selected numeric field (missing_values or total_values). Results are computed locally from supplied data only, with no external lookups or predictions. Covers up to 200 rows per call.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-string-normalisation-numeric-row-ordering-71cb132b/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)