# Data Reconciliation — Numeric Interval Filter + Trailing Mean Series

> Data Reconciliation — Numeric Interval Filter + 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).

Applies a numeric interval filter and computes a trailing mean series on data reconciliation records (source_total vs target_total), returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-126?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-interval-filter-trailing-mean-series-f921c45d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_PdgJ3TFWYOpIiPOAF4Kei

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-interval-filter-trailing-mean-series-f921c45d -d '<json body>'
```

Example prompt: I have reconciliation data with source_total and target_total values — can you filter rows where source_total is between 5 and 50, and also compute a trailing mean with a window of 3 over source_total, across these 4 rows: row-1 (2026-10-01, group-a, 10, 1), row-2 (2026-10-02, group-b, 20, 2), row-3 (2026-10-03, group-a, 15, 3), row-4 (2026-10-04, group-b, 30, 4)?

## When to prefer this

Choose this endpoint when you need both a range-based filter and a rolling average computed together on reconciliation data (source_total vs target_total) in a single API call, without needing live data lookup, ML prediction, or external system integration. It is ideal for lightweight, local analytical passes over up to 200 pre-aggregated rows at very low cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row or more than 200 rows provided returns a validation error
- window size larger than the number of rows may produce incomplete or no trailing mean values
- date fields not matching YYYY-MM-DD pattern are rejected
- source_total or target_total values outside ±1,000,000,000,000 are rejected
- missing required fields (row_id, dataset_group, date) cause schema validation failure
- minimum greater than maximum may produce an empty filtered result set

## How this service works

Data reconciliation — Numeric interval filter + Trailing mean series: Numeric interval filter + 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

Two analytical reports: (1) a filtered subset of the input rows where the chosen field (source_total or target_total) falls within the specified [minimum, maximum] interval, and (2) a trailing mean series computed over the chosen field using the specified rolling window size — both derived from the supplied reconciliation records without any external data lookup.

## 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
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-numeric-interval-filter-trailing-mean-series-f921c45d/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)