# Label Review Data Quality Audit — Record Quality Audit, String Normalisation & Missing-Value Fill

> Label Review Data Quality Audit — Record Quality Audit, String Normalisation & Missing-Value Fill 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).

Audits label review records for data quality issues, normalises string fields, and fills missing values using zero/mean/median imputation for up to 200 rows across reviewed_records and changed_labels fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-208?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-data-quality-audit-record-quality-audit-string-e04d205f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pS9ZyX90-WMM987Fthlfw

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-data-quality-audit-record-quality-audit-string-e04d205f -d '<json body>'
```

Example prompt: Run a quality audit, string normalisation, and median missing-value fill on these label review rows — here are 50 records with row_id, date, dataset_group, reviewed_records, and changed_labels; use median imputation on the reviewed_records field.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) batch audit of label review records covering quality checks, string normalisation, and missing-value imputation in a single call. It is ideal for annotation pipeline QA workflows where you want three standardised reports without external API calls, live predictions, or professional review. Best for datasets up to 200 rows with the specific reviewed_records and changed_labels schema.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause row-level validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside allowed range (-1e12 to 1e12) are rejected
- Empty rows array returns an error
- Invalid enum values for field or method parameters cause schema rejection

## How this service works

Label review — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill 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 anomalies, duplicates, or structural issues; (2) a string normalisation report showing standardised values for text fields like dataset_group; and (3) a missing-value fill report with imputed values for the chosen numeric field (reviewed_records or changed_labels) using the selected method (zero, mean, or median). All processing is local — no external lookups or predictions.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-data-quality-audit-record-quality-audit-string-e04d205f/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)