# Dataset Storage Record Quality Audit and Exact Row Deduplication

> Dataset Storage Record Quality Audit and Exact Row Deduplication 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 two analytical reports on up to 200 dataset storage records: a record quality audit and exact row deduplication, using local engines on supplied used_mb and row_count data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-002?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/dataset-storage-record-quality-audit-and-exact-row-deduplication-5622f9c8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_w65_JQZSWQpGRrG8ap3aB

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 dataset-storage-record-quality-audit-and-exact-row-deduplication-5622f9c8 -d '<json body>'
```

Example prompt: Can you run a record quality audit and exact row deduplication on these dataset storage records? I have rows with fields like row_id, dataset_group, date, used_mb, and row_count — here are my 50 entries across groups 'alpha' and 'beta' from October 2026.

## When to prefer this

Choose this endpoint when you need both a data quality audit and exact deduplication on dataset storage records (used_mb, row_count) in a single low-cost call. Ideal for pre-ETL validation, billing reconciliation checks, or storage monitoring pipelines where you want offline, local analysis without any external data lookups. Best suited for batches of up to 200 rows where you need two structured reports at once.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern cause parse failures
- Empty rows array returns an error or empty report
- Extremely large numeric values for used_mb or row_count may cause unexpected behavior if outside expected range

## How this service works

Dataset storage — Record quality audit + Exact row deduplication: Record quality audit + Exact row deduplication for supplied dataset storage records (used_mb, row_count). 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 record quality audit identifying missing, null, or anomalous values in used_mb and row_count fields across the supplied rows, and (2) an exact row deduplication report listing which rows are identical duplicates. Both reports are computed locally against the supplied 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",
     "used_mb",
     "row_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "used_mb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "row_count": {
      "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",
     "used_mb": 10,
     "row_count": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "used_mb": 20,
     "row_count": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "used_mb": 15,
     "row_count": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "used_mb": 30,
     "row_count": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-storage-record-quality-audit-and-exact-row-deduplication-5622f9c8/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)