# Null Coverage Analytics: String Normalisation + Grouped Numeric Summary

> Null Coverage Analytics: String Normalisation + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).

Analyzes null/missing value coverage records by normalizing string fields and producing grouped numeric summaries across up to 200 rows, generating 2 reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-023?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-string-normalisation-grouped-numeric-summary-a9e2bdab
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Xi0x1shpecfjdHnGDs8yC

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-grouped-numeric-summary-a9e2bdab -d '<json body>'
```

Example prompt: Can you analyze this batch of null coverage records — I have up to 50 rows with dataset groups like 'group-a' and 'group-b', each with missing_values and total_values counts — and give me a string normalization report plus a grouped numeric summary for the missing_values field?

## When to prefer this

Choose this endpoint when you have tabular null-coverage or data-completeness records (with missing_values and total_values) and need both string normalization and grouped numeric aggregation in a single low-cost call. Ideal for data quality audits, pipeline monitoring, and pre-analysis completeness checks where you supply the data locally and don't need live data fetches, predictions, or external enrichment. Best for batch sizes up to 200 rows.

## Known failure modes

- Input array exceeds 200 rows — rejected with validation error
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) on any row causes rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- row_id exceeds 80 characters or is empty — validation error
- Field enum value not 'missing_values' or 'total_values' — rejected
- Empty rows array (minItems: 1 violated) causes failure
- Payment of 0.01 USDC not supplied — x402 payment required error

## How this service works

Null coverage — String normalisation + Grouped numeric summary: String normalisation + Grouped numeric summary 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

Returns two analytical reports: (1) a string normalization report for the supplied row/group/date fields, and (2) a grouped numeric summary of either missing_values or total_values broken down by dataset_group — covering up to 200 input rows. No external lookups or predictions are included; all analysis uses local computation on supplied data.

## 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-grouped-numeric-summary-a9e2bdab/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)