# Label Review Analytics — Record Quality Audit, String Normalisation & Category Frequencies

> Label Review 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 2026-10-15).

Runs three analytical reports on label review data: record quality audit, string normalisation, and category frequency analysis for up to 200 rows of reviewed records and changed labels.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-195?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-328b88f5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vBrZIDs49Z3AsKyKFVsik

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-328b88f5 -d '<json body>'
```

Example prompt: Can you audit the quality of my label review records, normalise the strings, and show me category frequencies? I have up to 50 rows with dataset groups like 'group-a' and 'group-b', dates from 2026-10-01, reviewed_records counts, and changed_labels counts.

## When to prefer this

Choose this endpoint when you need a quick, cheap ($0.01 USDC) bundle of three data quality and normalisation reports on label review data without requiring any external data sources, live predictions, or professional assessments. It is ideal for ML/annotation teams wanting to validate a label review export before downstream use, particularly when the dataset is under 200 rows and you want quality audit, string normalisation, and frequency analysis in a single call.

## Known failure modes

- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, reviewed_records, changed_labels) — validation error
- Date fields not matching YYYY-MM-DD pattern — schema validation failure
- Null or out-of-range numeric values for reviewed_records or changed_labels — may produce incomplete audit results
- Payment not included or insufficient — x402 payment required error

## How this service works

Label review — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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

Three independent analytical reports: (1) a record quality audit flagging completeness, nulls, and anomalies; (2) a string normalisation report standardising text fields like dataset_group; (3) a category frequency table showing distribution counts for categorical fields across the supplied rows. All derived purely from the supplied input 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",
     "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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-analytics-record-quality-audit-string-normalisation-328b88f5/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)