# Data Reconciliation — Daily Sum Series + Trailing Mean Series

> Data Reconciliation — Daily Sum Series + 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 daily sum series and trailing mean series analytics for supplied data reconciliation records comparing source and target totals, returning two independent reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-136?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-daily-sum-series-trailing-mean-series-790e0b36
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5oYpuCG8YdY_DEHT1Blva

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-daily-sum-series-trailing-mean-series-790e0b36 -d '<json body>'
```

Example prompt: Can you run daily sum and trailing mean series reports on my reconciliation data — I've got rows with source_total and target_total by date across two groups, and I want a window size of 7? There are about 50 rows total.

## When to prefer this

Choose this endpoint when you need both a daily sum aggregation and a trailing moving average computed together in a single paid call on up to 200 reconciliation rows — ideal for comparing source vs target totals across groups over time without any external lookups, predictions, or live data. Best suited for offline or batch analytical workflows where you supply all the data and want lightweight statistical summaries at low cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row provided — minimum array length not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, source_total, target_total) in any row
- Date field not in YYYY-MM-DD format — pattern validation failure
- Window size less than 2 or greater than 200 — integer constraint violation
- Numeric values exceeding ±1,000,000,000,000 — range validation failure
- Payment not completed — x402 payment required error

## How this service works

Data reconciliation — Daily sum series + Trailing mean series: Daily sum series + 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 independent analytical reports: (1) a daily sum series aggregating the specified field (source_total or target_total) across dataset groups by date, and (2) a trailing mean series computed over the specified rolling window size — both derived from the supplied reconciliation rows with no external data 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-daily-sum-series-trailing-mean-series-790e0b36/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)