# Data Reconciliation: Exact Row Deduplication + Base-100 Series

> Data Reconciliation: Exact Row Deduplication + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Deduplicates supplied reconciliation rows and generates a Base-100 indexed series for source_total or target_total fields, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-047?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-base-100-series-b3e37fdf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fV-2BsE1vQAA2zIkNxwUG

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-base-100-series-b3e37fdf -d '<json body>'
```

Example prompt: Take these reconciliation rows for group-a and group-b across October 2026 — up to 4 rows with source_total and target_total values — deduplicate any exact duplicates and give me a Base-100 series indexed from the first row using source_total.

## When to prefer this

Choose this endpoint when you need both exact row deduplication and a Base-100 normalized series in a single call for up to 200 reconciliation rows containing source and target totals. It is ideal for financial or ETL reconciliation workflows where you need to clean duplicate records and simultaneously produce a rebased index for trend comparison — all offline with no external data dependencies. Prefer alternatives if you need trailing means, IQR outlier detection, or missing-value fill instead of Base-100 indexing.

## Known failure modes

- More than 200 rows supplied — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, source_total, or target_total) — validation error
- Date not in YYYY-MM-DD format — pattern mismatch error
- base_index out of range (0–199) — validation error
- All rows are duplicates leaving an empty dataset after deduplication
- source_total or target_total out of allowed range (±1,000,000,000,000)

## How this service works

Data reconciliation — Exact row deduplication + Base-100 series: Exact row deduplication + Base-100 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: (1) an exact-row-deduplicated version of the supplied reconciliation rows, identifying and removing duplicate entries; and (2) a Base-100 indexed series for the chosen field (source_total or target_total), rebased so the selected base_index row equals 100, allowing relative comparison across dates and groups. No external lookups or predictions are made.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-exact-row-deduplication-base-100-series-b3e37fdf/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)