# Label Review — String Normalisation + Base-100 Series

> Label Review — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).

Runs two analytical reports on label review data: string normalisation of text fields and a base-100 indexed series for a chosen numeric measure, across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-030?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-03
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/label-review-string-normalisation-base-100-series-b8759b95
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_gODF3j0Nq6Z-LBKwI9tqX

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-string-normalisation-base-100-series-b8759b95 -d '<json body>'
```

Example prompt: Can you run the string normalisation and base-100 series reports on my label review data? I have 4 rows: row-1 on 2026-10-01 group-a with 10 reviewed_records and 1 changed_labels, row-2 on 2026-10-02 group-b with 20 reviewed_records and 2 changed_labels, row-3 on 2026-10-03 group-a with 15 reviewed_records and 3 changed_labels, row-4 on 2026-10-04 group-b with 30 reviewed_records and 4 changed_labels — use reviewed_records as the measure and index from row 0.

## When to prefer this

Choose this endpoint when you have label review tabular data (up to 200 rows) and need two lightweight, offline analytical reports — string normalisation of categorical/text fields and a base-100 indexed numeric trend series — without needing live data lookups, ML predictions, or external integrations. It is cost-effective at $0.01 for both reports together and is ideal for QA pipelines, annotation monitoring dashboards, or exploratory analysis of label review exports.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- base_index out of range (0–199) — error returned
- Numeric fields outside allowed range (±1 trillion) — validation failure
- Missing required fields (row_id, reviewed_records, changed_labels, date) — schema error

## How this service works

Label review — String normalisation + Base-100 series: String normalisation + Base-100 series 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 derived solely from the supplied data: (1) a string normalisation report cleaning and standardising text fields (dataset_group etc.), and (2) a base-100 indexed numeric series for the chosen field (reviewed_records or changed_labels), anchored to the specified base_index row. No external lookups or predictions are made.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-string-normalisation-base-100-series-b8759b95/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)