# Dataset Storage Record Quality Audit + Equal-Width Histogram

> Dataset Storage Record Quality Audit + Equal-Width Histogram 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 a record quality audit and equal-width histogram analysis on up to 200 dataset storage records (used_mb or row_count), returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-013?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-equal-width-histogram-8a0caee8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hoKfWc8pUKoHzbNyTOvot

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-equal-width-histogram-8a0caee8 -d '<json body>'
```

Example prompt: Can you audit the quality of these 50 dataset storage records and also give me an equal-width histogram with 8 bins for the used_mb field? I'll paste the rows — each has a row_id, dataset_group, date, used_mb, and row_count.

## When to prefer this

Choose this endpoint when you need both a data quality audit and a frequency distribution histogram for dataset storage records (used_mb or row_count) in a single call. It is ideal for pre-pipeline data validation, exploratory profiling of storage usage, or detecting anomalies across up to 200 rows. Prefer it over generic statistical APIs when your data has the specific dataset storage schema (row_id, dataset_group, date, used_mb, row_count) and you need two bundled analytical reports at low cost.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) causes schema validation failure
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- bins value outside 1–30 range is rejected
- Submitting an empty rows array is rejected (minItems: 1)
- Non-numeric values for used_mb or row_count when null is not acceptable may cause computation errors

## How this service works

Dataset storage — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram 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 reports: (1) a record quality audit flagging missing values, nulls, out-of-range entries, and other data issues per row; and (2) an equal-width histogram showing frequency distribution of the chosen field (used_mb or row_count) across the specified number of bins. Both reports are computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "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-equal-width-histogram-8a0caee8/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)