# Data Reconciliation — Duplicate Key Report + Adjacent Row Changes

> Data Reconciliation — Duplicate Key Report + 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).

Analyzes up to 200 reconciliation rows to produce two reports: a duplicate key detection report and an adjacent row change analysis for source and target totals.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-062?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-duplicate-key-report-adjacent-row-changes-97820ce3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0I6Uv_j4uuNOQCGdHmLHj

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-duplicate-key-report-adjacent-row-changes-97820ce3 -d '<json body>'
```

Example prompt: Can you run a duplicate key report and adjacent row changes analysis on my reconciliation data? I have about 50 rows with row_id, date, dataset_group, source_total, and target_total — I want to check the source_total field for duplicates and sequential shifts.

## When to prefer this

Choose this endpoint when you need simultaneous duplicate key detection and row-over-row change analysis on reconciliation data in a single API call. It is ideal for ETL validation, financial close checks, or data migration audits where both data integrity (no duplicate keys) and sequential consistency (no unexpected adjacent changes) matter. It works entirely on supplied data with no external lookups, making it deterministic and privacy-preserving.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, source_total, target_total) cause schema validation failure
- Dates not matching YYYY-MM-DD pattern are rejected
- row_id values longer than 80 characters are rejected
- Numeric values outside ±1,000,000,000,000 are rejected
- Submitting fewer than 1 row returns a validation error

## How this service works

Data reconciliation — Duplicate key report + Adjacent row changes: Duplicate key report + Adjacent row changes 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 duplicate key report identifying any row_id values that appear more than once within the supplied dataset, and (2) an adjacent row changes report showing value deltas between consecutive rows for the selected field (source_total or target_total), covering up to 200 input rows.

## 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-duplicate-key-report-adjacent-row-changes-97820ce3/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)