# Aggregation Checks — String Normalisation + Numeric Distribution

> Aggregation Checks — 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 2026-10-23).

Analyzes up to 200 aggregation check records by performing string normalisation on group fields and numeric distribution analysis on source_sum or aggregate_sum values, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-17-022?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aggregation-checks-string-normalisation-numeric-distribution-bb053b8f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0opuFE-ndwP-HgAy_3F3X

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 aggregation-checks-string-normalisation-numeric-distribution-bb053b8f -d '<json body>'
```

Example prompt: Run string normalisation and numeric distribution analysis on these aggregation check records — I have 4 rows with dataset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, source_sum values of 10, 20, 15, 30 and aggregate_sum values of 1, 2, 3, 4 — analyze the source_sum field.

## When to prefer this

Choose this endpoint when you need both string normalisation of group/category fields and numeric distribution analysis for aggregation check records in a single low-cost call. It is ideal for data quality workflows involving source-vs-aggregate reconciliation data, ETL validation, or audit reporting where you already have the rows locally and need two analytical outputs without any external lookups or predictions.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, source_sum, aggregate_sum) on any row — error returned
- Date field not matching YYYY-MM-DD pattern — validation error
- Numeric values outside ±1,000,000,000,000 range — rejected
- Invalid field enum value (not 'source_sum' or 'aggregate_sum') — error
- Payment of 0.01 USDC not completed via x402 protocol — 402 response

## How this service works

Aggregation checks — String normalisation + Numeric distribution: String normalisation + Numeric distribution for supplied aggregation checks records (source_sum, aggregate_sum). 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

Two independent analytical reports: (1) a string normalisation report covering the dataset_group and other string fields in the supplied rows, and (2) a numeric distribution report for the selected field (source_sum or aggregate_sum), covering distribution statistics such as min, max, mean, spread, and frequency across up to 200 rows. No external data is fetched; analysis is performed entirely on the supplied records.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "source_sum",
     "aggregate_sum"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_sum": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "aggregate_sum": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_sum": 10,
     "aggregate_sum": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_sum": 20,
     "aggregate_sum": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_sum": 15,
     "aggregate_sum": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_sum": 30,
     "aggregate_sum": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "source_sum",
    "aggregate_sum"
   ],
   "type": "string",
   "default": "source_sum"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/aggregation-checks-string-normalisation-numeric-distribution-bb053b8f/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)