# Data Reconciliation — Exact Row Deduplication + Numeric Row Ordering

> Data Reconciliation — Exact Row Deduplication + 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 2026-10-19).

Deduplicates rows exactly and orders them numerically for source/target reconciliation data, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-042?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-exact-row-deduplication-numeric-row-ordering-9b071eda
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5Dbu867Flo2YMJywhNVat

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-exact-row-deduplication-numeric-row-ordering-9b071eda -d '<json body>'
```

Example prompt: I have a set of reconciliation records with source_total and target_total fields — can you deduplicate the exact duplicate rows and then sort them numerically by source_total? Here are my rows: row-1 (2024-01-01, group-a, source=1000, target=950), row-2 (2024-01-02, group-a, source=2000, target=1980), row-3 (duplicate of row-1, group-a, source=1000, target=950).

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) batch operation to both deduplicate exact duplicate reconciliation rows and produce a numerically ordered view of the same data in a single call. It is ideal for data quality prep steps in financial or operational reconciliation workflows involving up to 200 rows, when no live data lookup, prediction, or external system action is required.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group, source_total, target_total) cause validation errors
- Malformed date strings (not YYYY-MM-DD format) cause schema validation failure
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array (minItems: 1 not met) causes validation failure

## How this service works

Data reconciliation — Exact row deduplication + Numeric row ordering: Exact row deduplication + 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 analytical reports: one showing the dataset after exact duplicate rows have been removed, and one showing the rows sorted in numeric order by the specified field (source_total or target_total). Reports cover up to 200 input rows and are generated using local analytical engines 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-exact-row-deduplication-numeric-row-ordering-9b071eda/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)