# Null Coverage Analytics: Record Quality Audit + String Normalisation + Base-100 Series

> Null Coverage Analytics: Record Quality Audit + String Normalisation + Base-100 Series 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).

Runs three local analytical reports (record quality audit, string normalisation, and base-100 index series) on supplied null-coverage data (missing_values and total_values) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-201?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-record-quality-audit-string-normalisation-b888e1b4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tY6pmk6nfY1mN21tF7p_1

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-b888e1b4 -d '<json body>'
```

Example prompt: Can you run the three null-coverage analytics reports — record quality audit, string normalisation, and base-100 series — on my dataset? I have 4 rows: row-1 in group-a on 2026-10-01 with 10 missing out of 1 total, row-2 in group-b on 2026-10-02 with 20 missing out of 2 total, row-3 in group-a on 2026-10-03 with 15 missing out of 3 total, and row-4 in group-b on 2026-10-04 with 30 missing out of 4 total. Use 'missing_values' as the field and base index 0.

## When to prefer this

Choose this endpoint when you need a combined, low-cost bundle of three data-quality analytics (quality audit, string normalisation, base-100 series) on null-coverage records without needing external data lookups, predictions, or live integrations. It is best suited for offline or batch data quality checks on small-to-medium datasets (up to 200 rows) where all data is already available as missing_values and total_values pairs.

## Known failure modes

- Validation error if rows array is empty or exceeds 200 items
- Schema violation if row objects are missing required fields (row_id, dataset_group, date, missing_values, total_values)
- Invalid date format if date strings do not match YYYY-MM-DD pattern
- base_index out of range if it exceeds the number of submitted rows minus one
- Numeric overflow if missing_values or total_values exceed the 1,000,000,000,000 limit
- Payment failure if 0.01 USDC x402 payment is not attached

## How this service works

Null coverage — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series 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

Three independent analytical reports for the supplied null-coverage records: (1) a record quality audit flagging anomalies in missing/total value fields, (2) a string normalisation report cleaning dataset_group and row_id labels, and (3) a base-100 indexed series for the chosen field relative to the specified base row — all computed locally without external lookups or predictions.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-record-quality-audit-string-normalisation-b888e1b4/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)