# Dataset Storage Analytics — String Normalisation + Numeric Distribution

> Dataset Storage Analytics — String Normalisation + Numeric Distribution 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).

Analyzes up to 200 dataset storage records, producing a string normalization report and a numeric distribution report for either used_mb or row_count fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-18-022?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-analytics-string-normalisation-numeric-distribution-1cac513d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Y5ITOIUfqHYK9Qe2ysjS5

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-analytics-string-normalisation-numeric-distribution-1cac513d -d '<json body>'
```

Example prompt: Can you analyze my dataset storage records — I have about 50 rows with dataset_group labels, dates, used_mb, and row_count values — and give me a string normalization report on the groups plus a numeric distribution breakdown for used_mb?

## When to prefer this

Choose this endpoint when you need quick, local statistical analysis of dataset storage records (up to 200 rows) combining string normalization of group labels with numeric distribution of either used_mb or row_count — at a flat cost of $0.01 USDC per call covering both reports. Prefer this over general-purpose analytics tools when you specifically have structured storage records with these fields and want both text normalization and distribution in a single call without external data lookups or predictions.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Invalid field enum value (not 'used_mb' or 'row_count') causes rejection
- All numeric values are null — distribution report may be empty or return no statistics
- Payment not attached or insufficient — x402 payment required before processing

## How this service works

Dataset storage — String normalisation + Numeric distribution: String normalisation + Numeric distribution 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 string normalization report summarizing the dataset_group field values (e.g. casing, whitespace, deduplication), and (2) a numeric distribution report (e.g. min, max, mean, percentiles, bucket frequencies) for the selected numeric field (used_mb or row_count) across up to 200 input rows. All analysis is performed 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-analytics-string-normalisation-numeric-distribution-1cac513d/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)