# Data Reconciliation: Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes

> Data Reconciliation: Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes 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).

Runs three local analytical reports on reconciliation row data (source_total vs target_total): a record quality audit, exact row deduplication check, and adjacent row change detection, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-217?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-record-quality-audit-exact-row-deduplication-c41def7d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_81rl1a0UnIplyF4jZkJHI

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-exact-row-deduplication-c41def7d -d '<json body>'
```

Example prompt: Audit my reconciliation data for quality issues, exact duplicate rows, and adjacent row changes — here are my rows: row-1 on 2026-10-01 in group-a has source_total 10 and target_total 1, row-2 on 2026-10-02 in group-b has source_total 20 and target_total 2, and row-3 on 2026-10-03 in group-a has source_total 15 and target_total 3; analyze the source_total field.

## When to prefer this

Choose this endpoint when you need three simultaneous reconciliation-focused analytical reports — quality audit, deduplication, and adjacent-change detection — on a small-to-medium dataset (up to 200 rows) of source/target total pairs, without needing external data lookups, predictions, or live enrichment. It is especially useful as a lightweight, low-cost ($0.01 USDC) batch validation step in ETL pipelines or financial reconciliation workflows.

## Known failure modes

- Exceeding 200 rows causes request rejection
- Missing required fields (row_id, dataset_group, date, source_total, target_total) per row triggers validation error
- Invalid date format (non-YYYY-MM-DD) causes schema rejection
- Values outside ±1,000,000,000,000 range rejected by schema
- Payment failure (insufficient USDC) prevents processing

## How this service works

Data reconciliation — Record quality audit + Exact row deduplication + Adjacent row changes: Record quality audit + Exact row deduplication + Adjacent row changes for supplied data reconciliation records (source_total, target_total). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit flagging nulls, formatting issues, and field completeness; (2) an exact row deduplication report identifying identical records; and (3) an adjacent row changes report showing value differences between consecutive rows — 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-record-quality-audit-exact-row-deduplication-c41def7d/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)