# Data Ingestion Batches — Quality Audit + Deduplication + Numeric Ordering

> Data Ingestion Batches — Quality Audit + Deduplication + Numeric Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).

Runs three independent analytical reports (record quality audit, exact row deduplication, and numeric row ordering) on a batch of data ingestion records containing received_rows and accepted_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-213?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batches-quality-audit-deduplication-numeric-ordering-c4fc3e3a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hu9fW0bI1hM7RPDCzA3l-

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-quality-audit-deduplication-numeric-ordering-c4fc3e3a -d '<json body>'
```

Example prompt: Run a quality audit, exact duplicate check, and numeric ordering on these ingestion batch records — rows have row_id, dataset_group, date, received_rows, and accepted_rows — and order by received_rows. Here are up to 200 rows from our pipeline.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) batch analysis of data ingestion records that combines three reports in a single call — quality auditing, deduplication, and numeric ordering — without needing external data sources, predictions, or live lookups. Ideal for ETL monitoring, pipeline QA, and ingestion log review where all data is already available locally and you want consolidated analytical output in one request.

## Known failure modes

- Batch exceeds 200 rows — request is rejected or truncated
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation errors
- Date field does not match YYYY-MM-DD pattern — row rejected
- Numeric values outside ±1,000,000,000,000 range cause schema validation failure
- Empty rows array (minItems:1 not met) returns an error
- Invalid field enum value (not received_rows or accepted_rows) causes rejection

## How this service works

Data ingestion batches — Record quality audit + Exact row deduplication + Numeric row ordering: Record quality audit + Exact row deduplication + Numeric row ordering for supplied data ingestion batches records (received_rows, accepted_rows). 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

Three independent analytical reports on the submitted batch: (1) a record quality audit flagging missing, null, or out-of-range values in received_rows and accepted_rows; (2) an exact row deduplication report identifying identical rows; (3) a numeric ordering report ranking rows by the selected field (received_rows or accepted_rows). All 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-quality-audit-deduplication-numeric-ordering-c4fc3e3a/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)