# Dataset Storage Record Quality Audit + Adjacent Row Changes

> Dataset Storage Record Quality Audit + Adjacent Row Changes 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 local analytical reports on dataset storage records: a record quality audit and adjacent-row change detection for used_mb or row_count fields, across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-011?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-adjacent-row-changes-f8c425b7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_MuYWDw-US6Iifq6s1_-XH

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-adjacent-row-changes-f8c425b7 -d '<json body>'
```

Example prompt: Can you run a record quality audit and adjacent row changes report on my dataset storage data? Here are up to 200 rows with row_id, dataset_group, date, used_mb, and row_count fields — analyze the used_mb field for quality issues and row-to-row changes.

## When to prefer this

Choose this endpoint when you need a fast, low-cost ($0.01 USDC) dual-report analysis of dataset storage records — specifically a quality audit plus adjacent row change detection — on batches up to 200 rows, all computed locally without any external data lookups or live integrations. Prefer it over general-purpose analytics tools when working within dataset storage contexts (used_mb, row_count) and needing combined quality + sequential-change insight in a single call.

## Known failure modes

- Fewer than 1 row submitted — returns validation error
- More than 200 rows submitted — rejected, exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Invalid field enum value (not 'used_mb' or 'row_count') — rejected
- Missing required fields (row_id, dataset_group, date) — validation error
- Payment not included or insufficient — x402 payment required error

## How this service works

Dataset storage — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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 analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed entries across the submitted rows, and (2) an adjacent row changes report showing delta values between consecutive rows for the selected field (used_mb or row_count), 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",
     "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
  },
  "field": {
   "enum": [
    "used_mb",
    "row_count"
   ],
   "type": "string",
   "default": "used_mb"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-storage-record-quality-audit-adjacent-row-changes-f8c425b7/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)