# Null Coverage Analytics — Record Quality Audit, String Normalisation & Category Frequencies

> Null Coverage Analytics — Record Quality Audit, String Normalisation & Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Performs three analytical reports on supplied null-coverage records: a record quality audit, string normalisation, and category frequency analysis — all offline, up to 200 rows per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-195?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-record-quality-audit-string-normalisation-9821e806
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zHr7IdXvGDUqi1iN0h_Sf

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-record-quality-audit-string-normalisation-9821e806 -d '<json body>'
```

Example prompt: Can you run a null coverage audit on these 4 rows from my dataset — row-1 in group-a on 2026-10-01 has 10 missing out of 1 total, row-2 in group-b on 2026-10-02 has 20 missing out of 2 total, row-3 in group-a on 2026-10-03 has 15 missing out of 3 total, and row-4 in group-b on 2026-10-04 has 30 missing out of 4 total — and give me the record quality audit, string normalisation, and category frequencies?

## When to prefer this

Choose this endpoint when you have up to 200 rows of null-coverage data (missing_values and total_values per row with dataset groups and dates) and need all three analytical outputs — quality audit, string normalisation, and category frequencies — in a single low-cost call ($0.01 USDC). It is ideal for offline, batch data quality assessment without any need for live lookups, predictions, or external data sources.

## Known failure modes

- More than 200 rows supplied — endpoint rejects payload exceeding maxItems limit
- Missing required fields (row_id, dataset_group, date, missing_values, total_values) — validation error returned
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected by schema
- Empty rows array (minItems: 1 not met) — request rejected
- Payment not completed via x402 protocol — endpoint returns 402 before processing

## How this service works

Null coverage — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied null coverage records (missing_values, total_values). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit summarising null coverage health per row, (2) a string normalisation report cleaning and standardising text fields, and (3) a category frequency report showing counts and distributions across dataset_group values — all computed locally from the supplied data, with no external lookups.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-record-quality-audit-string-normalisation-9821e806/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)