# Dataset Storage — Record Quality Audit + Duplicate Key Report

> Dataset Storage — Record Quality Audit + Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Runs two local analytical reports on supplied dataset storage records: a record quality audit and a duplicate key detection report, covering up to 200 rows of used_mb and row_count data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-003?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/dataset-storage-record-quality-audit-duplicate-key-report-f0281882
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xKBOEeTl4lpxDkM-DmGJW

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-duplicate-key-report-f0281882 -d '<json body>'
```

Example prompt: Can you audit these dataset storage records for quality issues and duplicate keys? I have up to 50 rows with fields like row_id, dataset_group, date, used_mb, and row_count — I want both a record quality audit and a duplicate key report.

## When to prefer this

Choose this endpoint when you need fast, offline (no external lookup) quality and deduplication analysis for dataset storage records specifically containing used_mb and row_count metrics. It is especially useful as a pre-pipeline validation step or post-migration integrity check. Prefer this over generic data quality tools when your records conform to the row_id/dataset_group/date/used_mb/row_count schema and you need both quality and duplicate reports in a single cheap call.

## Known failure modes

- Rows array is empty or missing — validation error returned
- Row count exceeds 200 — request rejected with limit error
- Required fields (row_id, dataset_group, date, used_mb, row_count) missing from one or more rows — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected
- row_id or dataset_group string exceeds 80 characters — rejected
- Numeric fields outside allowed range — schema rejection

## How this service works

Dataset storage — Record quality audit + Duplicate key report: Record quality audit + Duplicate key report 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 issues such as null values, out-of-range figures, or malformed fields in used_mb and row_count columns; and (2) a duplicate key report identifying any rows sharing the same key fields (e.g. row_id or dataset_group+date combinations). No external lookups are performed — all analysis is local.

## 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-duplicate-key-report-f0281882/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)