# Data Reconciliation — Exact Row Deduplication + IQR Outlier Flags

> Data Reconciliation — Exact Row Deduplication + IQR Outlier Flags 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 flags IQR-based outliers in source_total/target_total reconciliation data, returning 2 independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-049?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-iqr-outlier-flags-1b299ea7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ffEVqG0o8uRMPiPwUrpN0

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-iqr-outlier-flags-1b299ea7 -d '<json body>'
```

Example prompt: I have a set of reconciliation records with source_total and target_total values across multiple dataset groups — can you run exact row deduplication and IQR outlier flagging on them and give me 2 analytical reports? Here are up to 200 rows across groups like 'group-a' and 'group-b' from October 2026.

## When to prefer this

Choose this endpoint when you have up to 200 reconciliation records with source_total and target_total fields and need both exact-match deduplication and IQR-based statistical outlier flagging in a single low-cost call. It is ideal for ETL validation, financial reconciliation audits, and data quality checks where you want deterministic, locally computed analytics without external data lookups or ML predictions. Prefer this over general-purpose data tools when you specifically need paired deduplication + IQR outlier reports on reconciliation-structured data for under $0.01.

## Known failure modes

- Input exceeds 200 rows — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, dataset_group, date, source_total, target_total) results in rejection
- source_total or target_total values outside ±1,000,000,000,000 range rejected
- Fewer than 1 row submitted — minimum not met
- row_id or dataset_group strings exceeding 80 characters cause validation error
- Payment of 0.01 USDC not completed — request not processed

## How this service works

Data reconciliation — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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: (1) a deduplication report identifying and removing exact duplicate rows from the submitted reconciliation records, and (2) an IQR outlier flagging report marking rows where source_total or target_total values fall outside the interquartile range, computed entirely from the supplied data 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-iqr-outlier-flags-1b299ea7/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)