# Data Ingestion Batches — Record Quality Audit + Missing-Value Fill

> Data Ingestion Batches — Record Quality Audit + Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Audits record quality and fills missing values (received_rows or accepted_rows) in up to 200 data ingestion batch records using local analytical engines, returning two independent reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-019?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-record-quality-audit-missing-value-fill-213e5829
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_1dsjH1ieC9bYoHTvR-a0K

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-missing-value-fill-213e5829 -d '<json body>'
```

Example prompt: Can you audit the quality of these data ingestion batch records and fill in any missing accepted_rows values using median imputation? I have up to 50 rows with fields: row_id, dataset_group, date, received_rows, and accepted_rows — some accepted_rows are null.

## When to prefer this

Choose this endpoint when you need both a data quality audit AND statistical missing-value imputation for ingestion batch metrics (received_rows / accepted_rows) in a single call, without requiring live data lookups or external services. Ideal for ETL pipeline monitoring, data quality assurance workflows, and preprocessing ingestion logs before reporting. Prefer over manual scripts when you need two independent analytical reports at low cost ($0.01 USDC) for batches up to 200 rows.

## Known failure modes

- Input array is empty or exceeds 200 rows — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Invalid fill method or field enum value — bad request error
- Missing required fields (row_id, dataset_group, date) — schema validation error
- Payment not included or insufficient — 402 Payment Required

## How this service works

Data ingestion batches — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill 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

Returns two independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, or anomalies in the supplied rows, and (2) a missing-value fill report showing the imputed values for the specified field (received_rows or accepted_rows) using the chosen method (zero, mean, or median). All processing is performed locally with no external lookups or predictions.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batches-record-quality-audit-missing-value-fill-213e5829/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)