# Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Category Frequencies

> Label Review Analytics: Record Quality Audit + Exact Row Deduplication + 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 local analytical reports on label review data: record quality audit, exact row deduplication, and category frequency breakdown — all in one call for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-212?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-exact-row-deduplication-dd1e2a32
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_s_qH-QZTmrf05YIHA3Fjt

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-exact-row-deduplication-dd1e2a32 -d '<json body>'
```

Example prompt: Can you run a quality audit, find exact duplicate rows, and get category frequencies on my label review data? Here are the records: row-1 on 2026-10-01 in group-a with 10 reviewed_records and 1 changed_label, row-2 on 2026-10-02 in group-b with 20 reviewed_records and 2 changed_labels, row-3 on 2026-10-03 in group-a with 15 reviewed_records and 3 changed_labels.

## When to prefer this

Choose this endpoint when you need three complementary data quality reports — quality audit, deduplication, and category frequencies — on label review data in a single low-cost call. It is ideal for ML teams managing annotation pipelines who want to validate and summarize tabular review logs without sending data to an external model or prediction service. Best for datasets up to 200 rows where all analysis is performed locally with no external lookups.

## Known failure modes

- Input array exceeds 200 rows — request rejected with validation error
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause row-level validation failures
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Empty rows array returns error; minimum 1 row required
- Null numeric values for reviewed_records or changed_labels may reduce audit coverage

## How this service works

Label review — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + 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

Returns three independent analytical reports: (1) a record quality audit identifying null values, out-of-range fields, and formatting issues; (2) exact row deduplication results flagging identical rows; and (3) category frequency counts showing how often each dataset_group appears and aggregate stats on reviewed_records and changed_labels.

## 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-exact-row-deduplication-dd1e2a32/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)