# Data Ingestion Batches — Record Quality Audit + String Normalisation + Equal-Width Histogram

> Data Ingestion Batches — Record Quality Audit + String Normalisation + Equal-Width Histogram 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 local analytical reports (record quality audit, string normalisation, and equal-width histogram) on up to 200 data ingestion batch records containing received_rows and accepted_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-01-202?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-batches-record-quality-audit-string-normalisation-3a962842
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uMBzsdzW4xx2mCMeRCabk

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-string-normalisation-3a962842 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and equal-width histogram (5 bins) on these data ingestion batch records — analysing the received_rows field — I've got up to 50 rows with row_id, dataset_group, date, received_rows, and accepted_rows?

## When to prefer this

Choose this endpoint when you need three simultaneous analytical reports (quality audit, string normalisation, histogram) on a batch of up to 200 data ingestion records in a single call for a flat $0.01 USDC fee, without requiring any external data lookups, predictions, or live connections. It is ideal for profiling ETL pipeline outputs, validating ingestion batch health, or characterising row count distributions before downstream processing.

## Known failure modes

- Rows array exceeds 200 items — request rejected
- Required fields (row_id, date, received_rows, accepted_rows) missing from row objects
- Invalid date format (must match YYYY-MM-DD pattern)
- bins parameter out of range (must be 1–30)
- field value not one of the allowed enum values (received_rows, accepted_rows)
- Payment of 0.01 USDC not provided or declined

## How this service works

Data ingestion batches — Record quality audit + String normalisation + Equal-width histogram: Record quality audit + String normalisation + Equal-width histogram 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 data issues such as nulls, out-of-range values, and missing fields; (2) a string normalisation report cleaning and standardising text fields like dataset_group and date; and (3) an equal-width histogram of the chosen numeric field (received_rows or accepted_rows) divided into the specified number of bins. All reports are computed locally from the supplied rows with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "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-string-normalisation-3a962842/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)