# Data Ingestion Batch Analyzer — Quality Audit, String Normalization & Deduplication

> Data Ingestion Batch Analyzer — Quality Audit, String Normalization & Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Runs three analytical reports on up to 200 data ingestion batch rows: a record quality audit, string normalization, and exact row deduplication — all using local engines with no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-191?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-ingestion-batch-analyzer-quality-audit-string-normalization-13e16891
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_WxSbIcwUWS8W5t5LiCUSs

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-batch-analyzer-quality-audit-string-normalization-13e16891 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalization, and deduplication check on my ingestion batch data? I have rows like: row-1 on 2026-10-01 in group-a with 10 received and 1 accepted, row-2 on 2026-10-02 in group-b with 20 received and 2 accepted — up to 10 rows total.

## When to prefer this

Choose this endpoint when you need a lightweight, affordable ($0.01 USDC) triple-report data quality pass on ingestion batch records without requiring an external data warehouse, live API, or heavyweight ETL tool. It is ideal for spot-checking ingestion pipelines, validating batch uploads before further processing, or automating periodic data quality audits on small-to-medium row sets (up to 200 rows). Prefer this over custom scripts when you need all three capabilities — quality audit, normalization, and deduplication — bundled in a single call.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) causes rejection
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Payment failure via x402 protocol results in no report being returned

## How this service works

Data ingestion batches — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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

Returns three independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, or suspicious accepted/received ratios; (2) a string normalization report identifying and correcting inconsistencies in text fields like dataset_group; (3) an exact row deduplication report identifying and removing identical rows. All computed locally with no external calls, covering up to 200 input rows.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-ingestion-batch-analyzer-quality-audit-string-normalization-13e16891/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)