# Data Reconciliation — Numeric Row Ordering + Date by Category Pivot

> Data Reconciliation — Numeric Row Ordering + Date by Category Pivot 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).

Generates two analytical reports (numeric row ordering and date-by-category pivot) for data reconciliation records comparing source and target totals, supporting up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-122?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-numeric-row-ordering-date-by-category-pivot-bdb6a9b8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_47VIfm4S7VcG841NU3sLo

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-numeric-row-ordering-date-by-category-pivot-bdb6a9b8 -d '<json body>'
```

Example prompt: I have reconciliation data for 4 rows across two groups — group-a and group-b — with dates from 2026-10-01 to 2026-10-04 and source/target totals. Can you run numeric row ordering and a date-by-category pivot on the source_total field and give me both reports?

## When to prefer this

Choose this endpoint when you need two simultaneous analytical views — numeric ordering and date-by-category pivot — on a reconciliation dataset of up to 200 rows with source and target totals. It is ideal for ETL validation, financial close reconciliation, or data migration checks where you want ranked row ordering alongside a categorical date pivot in a single low-cost call ($0.01 USDC), without needing external data lookups, predictions, or professional assessments.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, dataset_group, date, source_total, target_total) — validation error
- Date field not in YYYY-MM-DD format — pattern validation failure
- Numeric values outside ±1,000,000,000,000 range — schema rejection
- Invalid field enum value (not 'source_total' or 'target_total') — validation error
- Empty rows array — minItems constraint failure

## How this service works

Data reconciliation — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot 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

Two independent analytical reports computed locally from the supplied rows: (1) a numeric row ordering report ranking records by the chosen field (source_total or target_total), and (2) a date-by-category pivot report cross-tabulating totals by date and dataset_group. No external lookups or predictions are included.

## 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-numeric-row-ordering-date-by-category-pivot-bdb6a9b8/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)