# Aggregation Checks — String Normalisation + Secondary-Measure Weighted Mean

> Aggregation Checks — String Normalisation + Secondary-Measure Weighted Mean 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).

Performs string normalisation and secondary-measure weighted mean calculations on up to 200 supplied aggregation check records containing source_sum and aggregate_sum fields, returning 2 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-17-034?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/aggregation-checks-string-normalisation-secondary-measure-weighted-mean-5ecccc5e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pmN6BrmaynTlr9adDtHAu

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-secondary-measure-weighted-mean-5ecccc5e -d '<json body>'
```

Example prompt: Can you run string normalisation and a secondary-measure weighted mean on these aggregation check rows? I have 4 records — group-a on 2026-10-01 with source_sum 10 and aggregate_sum 1, group-b on 2026-10-02 with source_sum 20 and aggregate_sum 2, group-a on 2026-10-03 with source_sum 15 and aggregate_sum 3, and group-b on 2026-10-04 with source_sum 30 and aggregate_sum 4 — and I want the analysis run on the source_sum field.

## When to prefer this

Choose this endpoint when you need to apply both string normalisation and weighted mean analytics together on batch aggregation check data (up to 200 rows) in a single low-cost call. It is ideal for reconciliation workflows comparing source_sum against aggregate_sum across date-grouped records where no external data lookups or predictions are needed. Prefer this over general-purpose analytics services when you specifically need the dual-report output (normalisation + weighted mean) in one transaction for under $0.01 USDC.

## Known failure modes

- Input array is empty or exceeds 200 rows — validation error returned
- Required fields (row_id, dataset_group, date, source_sum, aggregate_sum) missing from any row — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected with pattern error
- Numeric values outside ±1,000,000,000,000 range — rejected
- Invalid field enum value (not source_sum or aggregate_sum) — rejected
- Payment not included or insufficient USDC — 402 Payment Required

## How this service works

Aggregation checks — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean 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 2 independent analytical reports: one covering string normalisation results across the supplied rows and one covering the secondary-measure weighted mean calculation for the selected field (source_sum or aggregate_sum), computed locally without any external lookups or predictions. Covers up to 200 input rows per call.

## 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-secondary-measure-weighted-mean-5ecccc5e/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)