# Aggregation Checks — Grouped Numeric Summary + Numeric Row Ordering

> Aggregation Checks — Grouped Numeric Summary + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Produces two analytical reports for aggregation check records: a grouped numeric summary and a numeric row ordering, both computed locally on up to 200 supplied rows of source_sum and aggregate_sum data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-17-087?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/aggregation-checks-grouped-numeric-summary-numeric-row-ordering-42a98e41
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_SWwbLL06GECuOj93D_3hI

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-grouped-numeric-summary-numeric-row-ordering-42a98e41 -d '<json body>'
```

Example prompt: I have 4 aggregation check records across two groups — group-a had source_sum 10 and 15 on 2026-10-01 and 2026-10-03, group-b had source_sum 20 and 30 on 2026-10-02 and 2026-10-04, with aggregate_sums 1, 3, 2, 4 respectively. Can you run both a grouped numeric summary and a numeric row ordering on source_sum for these records?

## When to prefer this

Choose this endpoint when you need both a grouped numeric summary and a numeric row ordering in a single call for up to 200 aggregation check records, without requiring any live data lookup, external enrichment, or prediction. It is ideal for reconciliation workflows, pipeline audits, and data quality checks where you supply the rows directly and want two complementary analytical views at minimal cost ($0.01 USDC for both reports).

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, source_sum, aggregate_sum) cause a schema validation failure
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error due to minItems:1 constraint
- Payment failure (insufficient USDC) prevents report generation

## How this service works

Aggregation checks — Grouped numeric summary + Numeric row ordering: Grouped numeric summary + Numeric row ordering 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

Returns two independent analytical reports computed on the supplied rows: (1) a grouped numeric summary aggregating source_sum and/or aggregate_sum values by dataset_group, and (2) a numeric row ordering ranking rows by the selected field (source_sum or aggregate_sum). Both reports are derived entirely from the input 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",
     "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-grouped-numeric-summary-numeric-row-ordering-42a98e41/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)