# Transformation Throughput — Record Quality Audit + String Normalisation + Adjacent Row Changes

> Transformation Throughput — Record Quality Audit + String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Runs three local analytical reports on transformation throughput records: record quality audit, string normalisation, and adjacent row change detection for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-200?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-record-quality-audit-string-normalisation-3ce621c1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_BM7-jYFKxo38b6Y-rdEkI

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-record-quality-audit-string-normalisation-3ce621c1 -d '<json body>'
```

Example prompt: Run a record quality audit, string normalisation, and adjacent row changes analysis on my transformation throughput data — here are 4 rows with processed_rows and duration_seconds fields, grouped by dataset_group across dates 2026-10-01 through 2026-10-04, and I want the report for the processed_rows field.

## When to prefer this

Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and adjacent row change detection — on transformation throughput records (processed_rows, duration_seconds) in a single low-cost call. It is ideal when you have up to 200 rows of ETL pipeline data and want offline, local analysis without any live lookups or external data enrichment.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Providing an unsupported field enum value causes a schema error
- Empty rows array (minItems:1 violated) returns an error

## How this service works

Transformation throughput — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied transformation throughput records (processed_rows, duration_seconds). 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

Three independent analytical reports generated from the supplied rows: (1) a record quality audit flagging missing, invalid, or out-of-range values; (2) a string normalisation report identifying and standardising inconsistencies in string fields; (3) an adjacent row changes report highlighting value changes between consecutive rows — all computed locally 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
  },
  "field": {
   "enum": [
    "processed_rows",
    "duration_seconds"
   ],
   "type": "string",
   "default": "processed_rows"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-record-quality-audit-string-normalisation-3ce621c1/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)