# Data Reconciliation Analytics — Record Quality Audit + Exact Row Deduplication + Base-100 Series

> Data Reconciliation Analytics — Record Quality Audit + 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).

Runs three local analytical reports on supplied data reconciliation rows: a record quality audit, exact row deduplication, and a base-100 index series — all on up to 200 rows of source/target totals.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-218?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-analytics-record-quality-audit-exact-row-a0ea9993
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_UtlGHFo9iuQCZpole0N2j

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-analytics-record-quality-audit-exact-row-a0ea9993 -d '<json body>'
```

Example prompt: Can you run a record quality audit, deduplicate exact rows, and generate a base-100 index series on my reconciliation data? I have 4 rows across groups 'group-a' and 'group-b' with source_total and target_total values, and I want to use source_total as the field, indexed from row 0.

## When to prefer this

Choose this endpoint when you need three bundled analytical passes — quality audit, deduplication, and base-100 indexing — on a set of source/target reconciliation records in a single low-cost call. It is ideal for data engineering pipelines, financial reconciliation workflows, and ETL validation tasks where you want local, deterministic computation with no external data dependencies. Prefer it over single-purpose tools when you need all three report types simultaneously for up to 200 rows at $0.01 per call.

## Known failure modes

- More than 200 rows submitted — request rejected, maximum is 200 rows
- Missing required fields (row_id, dataset_group, date, source_total, target_total) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- base_index out of range (must be 0–199 and within row count) — computation error
- source_total or target_total outside allowed range (-1T to 1T) — validation rejection
- Empty rows array — minItems:1 constraint violated

## How this service works

Data reconciliation — Record quality audit + Exact row deduplication + Base-100 series: Record quality audit + Exact row deduplication + Base-100 series for supplied data reconciliation records (source_total, target_total). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit flagging completeness and validity issues across the supplied rows, (2) an exact row deduplication report identifying perfectly matching duplicate records, and (3) a base-100 index series for the specified field (source_total or target_total) anchored at the chosen base_index row — all computed locally 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-analytics-record-quality-audit-exact-row-a0ea9993/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)