# Label Review Analytics — Record Quality Audit, String Normalisation & Numeric Row Ordering

> Label Review Analytics — Record Quality Audit, 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 2026-10-15).

Runs three independent analytical reports on label review data: record quality audit, string normalisation, and numeric row ordering for up to 200 rows of reviewed_records and changed_labels data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-196?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/label-review-analytics-record-quality-audit-string-normalisation-5c094dd7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QzZS6uxFV4B0-RIRZ0b9L

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 label-review-analytics-record-quality-audit-string-normalisation-5c094dd7 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and numeric row ordering on these label review records I have — about 50 rows with reviewed_records and changed_labels fields grouped by dataset_group — and order results by reviewed_records?

## When to prefer this

Choose this endpoint when you have up to 200 rows of label review data and need all three of record quality auditing, string normalisation, and numeric ordering in a single low-cost call ($0.01 USDC). It is ideal for ML data ops teams validating annotation batches before ingestion, where no live prediction, external lookup, or professional assessment is needed — purely local analytical computation on supplied data.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, reviewed_records, changed_labels) causes row-level rejection
- Dates not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 bounds cause schema validation failure
- Empty rows array returns an error
- Invalid field enum value (not reviewed_records or changed_labels) causes a bad request error

## How this service works

Label review — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied label review records (reviewed_records, changed_labels). 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 flagging data issues in the supplied rows, (2) a string normalisation report cleaning dataset_group and related string fields, and (3) a numeric row ordering report ranking rows by the selected field (reviewed_records or changed_labels). All 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",
     "reviewed_records",
     "changed_labels"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "changed_labels": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "reviewed_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "changed_labels": 1,
     "reviewed_records": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "changed_labels": 2,
     "reviewed_records": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "changed_labels": 3,
     "reviewed_records": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "changed_labels": 4,
     "reviewed_records": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "reviewed_records",
    "changed_labels"
   ],
   "type": "string",
   "default": "reviewed_records"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-analytics-record-quality-audit-string-normalisation-5c094dd7/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)