# Dataset Storage Record Quality Audit + Trailing Mean Series

> Dataset Storage Record Quality Audit + Trailing Mean 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 two local analytical reports on dataset storage records: a record quality audit and a trailing mean series for used_mb or row_count fields, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-010?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-trailing-mean-series-23dab88c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_r8oLXimBivLkefSw5A1Mi

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-trailing-mean-series-23dab88c -d '<json body>'
```

Example prompt: Run a record quality audit and trailing mean series on these dataset storage rows — use the used_mb field with a window size of 3 — I have about 50 rows across two groups, group-a and group-b, dated from 2026-10-01 onward.

## When to prefer this

Choose this endpoint when you need both a data quality audit and a trailing mean series computed together from supplied dataset storage records in a single low-cost call ($0.01 USDC). It is ideal for offline/batch analytical passes on up to 200 rows of storage metrics (used_mb, row_count) where no live data lookup or external prediction is needed. Prefer it over separate analytics tools when you want two coordinated local reports from the same row set without external side effects.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) in any row — validation error
- Missing required fields (row_id, dataset_group, date) in any row — schema error
- Window size less than 2 or greater than 200 — parameter error
- Field value outside allowed numeric range — validation error
- Payment not included or insufficient — 402 payment required

## How this service works

Dataset storage — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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 identifying issues such as missing values, out-of-range entries, or malformed records across the supplied rows; and (2) a trailing mean series computed over the selected field (used_mb or row_count) using the specified rolling window size. Both reports are derived entirely from the supplied data using local analytical engines — no external lookups or live data.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-storage-record-quality-audit-trailing-mean-series-23dab88c/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)