# Data Reconciliation — Numeric Row Ordering + Trailing Mean Series

> Data Reconciliation — Numeric Row Ordering + Trailing Mean 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).

Computes numeric row ordering and a trailing mean series for supplied data reconciliation records (source_total vs target_total) over up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-115?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-numeric-row-ordering-trailing-mean-series-1450545f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_iNMO-UBvWAh-hfkMUgoea

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-numeric-row-ordering-trailing-mean-series-1450545f -d '<json body>'
```

Example prompt: Run numeric row ordering and a trailing mean series with window size 3 on my reconciliation data for source_total — I have 4 rows: row-1 on 2026-10-01 (source 10, target 1, group-a), row-2 on 2026-10-02 (source 20, target 2, group-b), row-3 on 2026-10-03 (source 15, target 3, group-a), row-4 on 2026-10-04 (source 30, target 4, group-b).

## When to prefer this

Choose this endpoint when you need two lightweight analytical reports — numeric row ranking and a trailing mean series — computed entirely from your own supplied reconciliation data without any external data lookup, prediction, or live data fetch. Ideal for data quality pipelines, financial reconciliation workflows, and ETL audit trails where you control the input and just need fast local analytics at minimal cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected, maxItems exceeded
- Window size smaller than 2 or larger than 200 — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- source_total or target_total out of range (-1T to +1T) — validation error
- Missing required fields (row_id, dataset_group, date) — schema rejection
- field enum value not 'source_total' or 'target_total' — rejected

## How this service works

Data reconciliation — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean 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) a numeric row ordering report ranking the submitted rows by the selected field, and (2) a trailing mean series report showing the rolling average over the specified window size — all computed locally from the supplied source_total and target_total 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-numeric-row-ordering-trailing-mean-series-1450545f/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)