# Data Reconciliation — Adjacent Row Changes + Base-100 Series

> Data Reconciliation — Adjacent Row Changes + 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).

Computes adjacent row-over-row changes and a base-100 indexed series for up to 200 supplied source/target reconciliation records, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-155?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-adjacent-row-changes-base-100-series-87580a9b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hqRFYxPIo-_J9H4PdfVsb

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-adjacent-row-changes-base-100-series-87580a9b -d '<json body>'
```

Example prompt: I have 5 rows of reconciliation data for group-a from October 2026 — source totals are 100, 110, 105, 120, 115 and target totals are 98, 107, 103, 118, 112. Can you run the adjacent row changes and base-100 index reports on the source_total field, using row 0 as the base?

## When to prefer this

Choose this endpoint when you have up to 200 reconciliation records with source and target totals and need two specific analytical views — adjacent row changes and base-100 indexing — computed from your own supplied data without any external data fetching. Ideal for financial reconciliation workflows, data quality pipelines, or period-over-period trend analysis where you control the input data. Not suitable if you need forecasting, live data lookup, more than 200 rows, or other analytical report types.

## Known failure modes

- More than 200 rows submitted — request rejected at schema validation
- Missing required fields (row_id, dataset_group, date, source_total, target_total) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- base_index out of range (>=number of rows) may cause computation error
- Null values in source_total or target_total may affect delta/index calculations
- Payment of 0.01 USDC not completed causes 402 response

## How this service works

Data reconciliation — Adjacent row changes + Base-100 series: Adjacent row changes + 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

Two analytical reports per call: (1) adjacent row-over-row changes for the selected field (source_total or target_total) across all supplied rows, and (2) a base-100 indexed series anchored to the specified base_index row — both computed locally from the supplied data without any 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-adjacent-row-changes-base-100-series-87580a9b/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)