# Transformation Throughput Analytics — Adjacent Row Changes & IQR Outlier Flags

> Transformation Throughput Analytics — Adjacent Row Changes & IQR Outlier Flags 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).

Analyzes transformation throughput records by computing adjacent row changes and IQR-based outlier flags for processed_rows or duration_seconds fields across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-157?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-analytics-adjacent-row-changes-iqr-outlier-404bc826
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EvxwWS_jX_hsur7Awb8iQ

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-analytics-adjacent-row-changes-iqr-outlier-404bc826 -d '<json body>'
```

Example prompt: Can you analyze my transformation throughput records for adjacent row changes and IQR outlier flags? I have 5 rows with date, row_id, dataset_group, processed_rows, and duration_seconds — please flag outliers on the processed_rows field.

## When to prefer this

Choose this endpoint when you need lightweight, local statistical analysis of transformation throughput time-series data — specifically adjacent-row delta computation and IQR outlier flagging — without requiring external data lookups, ML predictions, or professional assessments. Best for ETL/pipeline monitoring use cases with up to 200 rows at low cost.

## Known failure modes

- Missing required fields (row_id, date, processed_rows, duration_seconds) cause validation errors
- More than 200 rows submitted exceeds the maxItems limit
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Null values in the selected metric field may affect IQR computation
- Unsupported field enum value returns an error
- Payment of 0.01 USDC not received causes request rejection

## How this service works

Transformation throughput — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags 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 analytical reports: (1) adjacent row change values showing the difference between consecutive records for the selected field, and (2) IQR-based outlier flags marking records that fall outside the interquartile range bounds — both computed locally over the supplied dataset of up to 200 rows.

## 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-analytics-adjacent-row-changes-iqr-outlier-404bc826/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)