# Data Reconciliation — Exact Row Deduplication + Daily Sum Series

> Data Reconciliation — 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 2026-10-15).

Performs exact row deduplication and daily sum series analysis on up to 200 supplied data reconciliation records comparing source_total and target_total values.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-044?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-reconciliation-exact-row-deduplication-daily-sum-series-300bdf6f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_WMTaTf3nEIGgizrPpAJan

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-daily-sum-series-300bdf6f -d '<json body>'
```

Example prompt: Reconcile these rows for me — run exact deduplication and a daily sum series on my source_total and target_total data: I have 4 rows from 2026-10-01 to 2026-10-04 across groups group-a and group-b, and I want both reports for the source_total field.

## When to prefer this

Choose this endpoint when you need both exact row deduplication and a daily sum time series on user-supplied reconciliation data in a single low-cost call. It is ideal for ETL validation, finance reconciliation audits, and data warehouse checks where you already have the data and need offline analytics without any live lookups or external data enrichment. At $0.01 USDC for two reports on up to 200 rows, it is cost-effective for batch reconciliation tasks embedded in automated pipelines.

## Known failure modes

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

## How this service works

Data reconciliation — Exact row deduplication + Daily sum series: Exact row deduplication + Daily sum series 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 computed locally: (1) an exact row deduplication report identifying and removing identical rows from the supplied dataset, and (2) a daily sum series aggregating the selected field (source_total or target_total) by date across the provided records. Both reports are based solely on the supplied input 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-daily-sum-series-300bdf6f/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)