# Label Review Record Quality Audit with IQR Outlier Flags

> Label Review Record Quality Audit with IQR Outlier Flags 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 a two-report analytical audit on label review data: a record quality audit and IQR-based outlier flagging for up to 200 rows of reviewed_records and changed_labels data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-014?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-record-quality-audit-with-iqr-outlier-flags-c80de7ed
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_K1WmDw7TvyKMzkA52kO93

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-record-quality-audit-with-iqr-outlier-flags-c80de7ed -d '<json body>'
```

Example prompt: Can you run a record quality audit and IQR outlier check on my label review data? I have 4 rows: row-1 on 2026-10-01 for group-a with 10 reviewed_records and 1 changed_label, row-2 on 2026-10-02 for group-b with 20 reviewed_records and 2 changed_labels, row-3 on 2026-10-03 for group-a with 15 reviewed_records and 3 changed_labels, and row-4 on 2026-10-04 for group-b with 30 reviewed_records and 4 changed_labels — flag outliers on the reviewed_records field.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01) dual-report audit — record quality plus IQR outlier detection — on up to 200 rows of label review data without requiring any external API calls, live predictions, or professional assessments. Ideal for ML annotation pipeline monitoring, data quality gates before model training, or periodic audits of labeling team output.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause row-level rejection
- Malformed dates not matching YYYY-MM-DD pattern are rejected
- Null values in the selected analytical field may reduce outlier detection accuracy
- Too few rows (fewer than 4-5) may make IQR computation unreliable or undefined

## How this service works

Label review — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two analytical reports: (1) a record quality audit summarizing completeness, consistency, and data issues across the submitted rows, and (2) IQR-based outlier flags identifying which row_ids have statistically anomalous values in the selected field (reviewed_records or changed_labels). No external lookups or predictions are made — all analysis is performed locally on the supplied data.

## 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-record-quality-audit-with-iqr-outlier-flags-c80de7ed/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)