# Data Reconciliation — Grouped Numeric Summary + Category Frequencies

> Data Reconciliation — Grouped Numeric Summary + Category Frequencies 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).

Computes grouped numeric statistics and category frequency distributions for data reconciliation records containing source and target totals, processing up to 200 rows in two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-086?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/data-reconciliation-grouped-numeric-summary-category-frequencies-937cbaba
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_J6u8EjN_PdCE1ZN_Wx20S

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 data-reconciliation-grouped-numeric-summary-category-frequencies-937cbaba -d '<json body>'
```

Example prompt: Analyze these 150 reconciliation records for me — group them by dataset_group and give me a numeric summary of source_total values, plus frequency counts for each category.

## When to prefer this

Choose this endpoint when you need two quick, serverless analytical views — grouped numeric descriptives and category frequency counts — on a batch of up to 200 reconciliation records with source and target totals, without needing external data enrichment, predictions, or live lookups. It is ideal for lightweight ETL audit checks, financial close reviews, or data quality assessments where you already have the rows in hand and want fast local computation at low cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted returns a validation error
- Missing required fields (row_id, dataset_group, date, source_total, target_total) causes rejection
- Date strings not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid field enum value (not 'source_total' or 'target_total') causes an error

## How this service works

Data reconciliation — Grouped numeric summary + Category frequencies: Grouped numeric summary + Category frequencies for supplied data reconciliation records (source_total, target_total). 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: (1) a grouped numeric summary (e.g. count, min, max, mean, sum) of the chosen field — source_total or target_total — broken down by dataset_group, and (2) category frequency counts showing how many records belong to each dataset_group, all computed locally without external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-grouped-numeric-summary-category-frequencies-937cbaba/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)