# Data Reconciliation Analytics — Record Quality Audit, Exact Row Deduplication & Daily Sum Series

> Data Reconciliation Analytics — Record Quality Audit, Exact Row Deduplication & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Runs three independent analytical reports (record quality audit, exact row deduplication, and daily sum series) on supplied source/target reconciliation data for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-215?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-reconciliation-analytics-record-quality-audit-exact-row-20b13019
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_WDCWpHT9Pyar3KXFcFVyN

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-analytics-record-quality-audit-exact-row-20b13019 -d '<json body>'
```

Example prompt: Can you run a full data reconciliation analysis on my records — quality audit, exact duplicate detection, and daily sum series for the source_total field? Here are my rows: row-1 on 2025-01-01 in group-a with source 1000 and target 990, row-2 on 2025-01-02 in group-b with source 2000 and target 2000, row-3 on 2025-01-01 in group-a with source 1000 and target 990 (duplicate of row-1).

## When to prefer this

Choose this endpoint when you need three reconciliation-focused analytical reports in a single call at minimal cost ($0.01 USDC): record quality auditing, exact duplicate detection, and daily sum aggregation. It is ideal for ETL validation, financial reconciliation pipelines, and data quality checks on datasets up to 200 rows where no external data enrichment or prediction is needed — everything is computed from your supplied rows only.

## Known failure modes

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

## How this service works

Data reconciliation — Record quality audit + Exact row deduplication + Daily sum series: Record quality audit + Exact row deduplication + Daily sum series 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 data issues in the supplied rows, (2) an exact row deduplication report identifying repeated records, and (3) a daily sum series aggregating the selected field (source_total or target_total) by date. All computed locally on the submitted 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-analytics-record-quality-audit-exact-row-20b13019/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)