# Dataset Partition Sizes — Record Quality Audit, Exact Row Deduplication & Category Frequencies

> Dataset Partition Sizes — Record Quality Audit, Exact Row Deduplication & Category Frequencies 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 three independent analytical reports (record quality audit, exact row deduplication, and category frequency analysis) on up to 200 dataset partition size records containing row counts and file sizes.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-07-212?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-partition-sizes-record-quality-audit-exact-row-deduplication-49b157a8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nVGoN-26_eelA61usEAas

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-partition-sizes-record-quality-audit-exact-row-deduplication-49b157a8 -d '<json body>'
```

Example prompt: Can you run a record quality audit, exact deduplication check, and category frequency breakdown on these partition size records I have — they each have a row_id, dataset_group, date, row_count, and file_mb — there are about 50 rows total?

## When to prefer this

Choose this endpoint when you need three simultaneous analytical views (quality, deduplication, category frequencies) on a batch of dataset partition size records in a single call at low cost. It is ideal for offline batch profiling of up to 200 rows where no external lookups, predictions, or live data are needed. Prefer alternatives if you need statistical summaries beyond frequency counts, time-series analysis, or more than 200 rows per call.

## Known failure modes

- Submitting more than 200 rows returns an error or truncated results
- Rows missing required fields (row_id, dataset_group, date, row_count, file_mb) may cause validation errors
- Dates not matching YYYY-MM-DD pattern may be flagged or rejected
- row_id or dataset_group exceeding 80 characters may be rejected
- Empty rows array is not permitted (minItems: 1)
- Payment of 0.01 USDC must succeed via x402 protocol or the call is rejected

## How this service works

Dataset partition sizes — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + Category frequencies for supplied dataset partition sizes records (row_count, file_mb). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit flagging issues such as nulls, invalid values, or format violations per row; (2) an exact row deduplication report identifying identical rows across the submitted records; (3) a category frequency report showing how often each dataset_group value appears. All three are computed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "row_count",
     "file_mb"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "file_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",
     "file_mb": 1,
     "row_count": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "file_mb": 2,
     "row_count": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "file_mb": 3,
     "row_count": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "file_mb": 4,
     "row_count": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dataset-partition-sizes-record-quality-audit-exact-row-deduplication-49b157a8/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)