# Data Reconciliation — Record Quality Audit + Numeric Row Ordering

> Data Reconciliation — Record Quality Audit + 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).

Performs a dual-report analysis on reconciliation data rows: audits record quality and orders rows numerically for up to 200 source/target total pairs.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-007?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/data-reconciliation-record-quality-audit-numeric-row-ordering-218ab886
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kwsBk7GrWLWxpK9lAoG-k

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-record-quality-audit-numeric-row-ordering-218ab886 -d '<json body>'
```

Example prompt: Can you run a record quality audit and numeric row ordering on my reconciliation data? I have 12 rows across two dataset groups — 'ledger-A' and 'ledger-B' — with dates from 2026-01-01 to 2026-01-12, and I want to analyze the source_total field.

## When to prefer this

Choose this endpoint when you need to locally audit data quality and produce ordered row rankings for reconciliation datasets of up to 200 rows without any external data lookup, prediction, or professional assessment. Ideal for ETL validation, financial reconciliation checks, and dataset integrity reviews where only source_total and target_total comparisons are needed and a bundled dual-report output at low cost is desirable.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, source_total, target_total) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) fails pattern validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Invalid field enum value (not source_total or target_total) causes error
- Empty rows array (minItems:1 violation) returns error

## How this service works

Data reconciliation — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering 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 for the submitted reconciliation rows: (1) a record quality audit identifying missing, null, or malformed values across fields, and (2) a numeric row ordering report ranking rows by the selected field (source_total or target_total). Both reports are computed locally 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_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-record-quality-audit-numeric-row-ordering-218ab886/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)