# Data Ingestion Batches — Record Quality Audit + Date by Category Pivot

> Data Ingestion Batches — Record Quality Audit + Date by Category Pivot 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 analytical reports on supplied data ingestion batch records: a record quality audit (checking received_rows vs accepted_rows integrity) and a date-by-category pivot table, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-017?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/data-ingestion-batches-record-quality-audit-date-by-category-pivot-4647a854
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_l2rqs1kCz5edW7ExO1aah

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 data-ingestion-batches-record-quality-audit-date-by-category-pivot-4647a854 -d '<json body>'
```

Example prompt: Can you run a record quality audit and date-by-category pivot on my ingestion batch data? Here are the rows: row-1 on 2024-01-15, dataset group 'sales', received_rows=1000, accepted_rows=950; row-2 on 2024-01-16, dataset group 'returns', received_rows=500, accepted_rows=480 — use received_rows as the field for the pivot.

## When to prefer this

Choose this endpoint when you need two complementary analytical views — a quality audit and a date-category pivot — on data ingestion batch records in a single low-cost call ($0.01 USDC). Ideal for ETL monitoring, pipeline quality review, and batch acceptance rate analysis without requiring external data sources or live connections. Best when you already have the ingestion batch data in hand and want structured analytical output quickly.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation errors
- Date field not matching YYYY-MM-DD pattern returns schema validation error
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected
- Invalid field enum value (not 'received_rows' or 'accepted_rows') causes error
- Empty rows array rejected due to minItems:1 constraint

## How this service works

Data ingestion batches — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied data ingestion batches records (received_rows, accepted_rows). 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

Two analytical reports: (1) a record quality audit summarizing data completeness and acceptance metrics (received_rows vs accepted_rows) for each supplied row, and (2) a date-by-category pivot table grouping the selected field (received_rows or accepted_rows) by date and dataset_group. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "received_rows",
     "accepted_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "accepted_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "received_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "accepted_rows": 1,
     "dataset_group": "group-a",
     "received_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "accepted_rows": 2,
     "dataset_group": "group-b",
     "received_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "accepted_rows": 3,
     "dataset_group": "group-a",
     "received_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "accepted_rows": 4,
     "dataset_group": "group-b",
     "received_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "received_rows",
    "accepted_rows"
   ],
   "type": "string",
   "default": "received_rows"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-record-quality-audit-date-by-category-pivot-4647a854/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)