# Label Review Analytics — String Normalisation + Numeric Distribution

> Label Review Analytics — String Normalisation + Numeric Distribution 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).

Analyzes up to 200 label-review records, producing a string normalization report and a numeric distribution report for the reviewed_records or changed_labels field.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-022?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-string-normalisation-numeric-distribution-bd13fd3f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_a3Y3nN6xoioqHmBf34jRx

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-string-normalisation-numeric-distribution-bd13fd3f -d '<json body>'
```

Example prompt: I have 4 label review records from October 2026 — row-1 through row-4, groups a and b, with reviewed_records ranging from 10 to 30 and changed_labels from 1 to 4. Can you run the string normalization and numeric distribution reports on the reviewed_records field for me?

## When to prefer this

Choose this endpoint when you have tabular label-review data (up to 200 rows) and need both a string normalization check and a numeric distribution profile in a single low-cost call ($0.01 USDC). It is ideal for ML annotation pipeline audits, data quality checks before model training, and exploratory analysis of label churn. Prefer it over general-purpose analytics tools when you specifically need the reviewed_records/changed_labels schema and want a bundled two-report output without any external API dependencies or live lookups.

## Known failure modes

- More than 200 rows submitted — request rejected, must batch into smaller calls
- Missing required fields (row_id, date, reviewed_records, changed_labels) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — schema rejection
- Invalid field enum value (must be reviewed_records or changed_labels) — error response
- Empty rows array — minimum 1 item required

## How this service works

Label review — String normalisation + Numeric distribution: String normalisation + Numeric distribution 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 independent analytical reports: (1) a string normalization report covering the string fields in the submitted records (e.g. dataset_group, date formatting), and (2) a numeric distribution report for the selected field (reviewed_records or changed_labels), including statistics such as min, max, mean, and distribution shape across up to 200 submitted rows. 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-analytics-string-normalisation-numeric-distribution-bd13fd3f/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)