# Transformation Throughput — String Normalisation + Category Frequencies

> Transformation Throughput — String Normalisation + 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 2026-10-19).

Analyzes transformation throughput records by normalizing string fields and computing category frequency distributions across up to 200 rows in a single call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-024?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-string-normalisation-category-frequencies-13749311
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_r-OqorSotGFm3YZypidgl

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 transformation-throughput-string-normalisation-category-frequencies-13749311 -d '<json body>'
```

Example prompt: I have a list of up to 200 ETL throughput records — each with a row ID, dataset group, date, processed row count, and duration in seconds — can you run the string normalization and category frequency reports on them for me?

## When to prefer this

Choose this endpoint when you need both string normalization and category frequency analysis on transformation throughput records in a single low-cost call. It is ideal for ETL monitoring, pipeline auditing, and data quality workflows where you already have the data locally and do not need live lookups, predictions, or external enrichment. Best suited for batch sizes up to 200 rows processed together.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Numeric fields outside the allowed range cause schema rejection
- Empty rows array returns an error due to minItems:1 constraint

## How this service works

Transformation throughput — String normalisation + Category frequencies: String normalisation + Category frequencies for supplied transformation throughput records (processed_rows, duration_seconds). 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 for the submitted rows: (1) a string normalization report that standardizes and cleans the string fields (e.g. dataset_group), and (2) a category frequency report that counts how often each distinct category value appears across the dataset. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "processed_rows",
     "duration_seconds"
    ],
    "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
     },
     "processed_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "duration_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "processed_rows": 10,
     "duration_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "processed_rows": 20,
     "duration_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "processed_rows": 15,
     "duration_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "processed_rows": 30,
     "duration_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-string-normalisation-category-frequencies-13749311/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)