# Schema Conformity — Record Quality Audit + String Normalisation + Adjacent Row Changes

> Schema Conformity — Record Quality Audit + String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).

Runs three local analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of schema conformity data containing valid_records and checked_records fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-200?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-record-quality-audit-string-normalisation-adjacent-1f814ae7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZXEGJwA2VeqEEdgOIWvxE

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 schema-conformity-record-quality-audit-string-normalisation-adjacent-1f814ae7 -d '<json body>'
```

Example prompt: Can you run the three-report schema conformity analysis on my rows — record quality audit, string normalisation, and adjacent row changes — for this batch of up to 200 entries with valid_records as the target field?

## When to prefer this

Choose this endpoint when you need three bundled analytical passes — quality audit, string normalisation, and adjacent row change detection — on schema conformity data in a single $0.01 call, without needing external data lookups, live predictions, or professional assessments. It is ideal for offline batch validation of ETL pipeline outputs or data quality monitoring workflows where the data is already in hand.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, valid_records, checked_records) causes rejection
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array (minItems:1 violated) returns an error

## How this service works

Schema conformity — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied schema conformity records (valid_records, checked_records). 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 returned together: (1) a record quality audit summarising completeness and validity of the supplied rows, (2) a string normalisation report showing standardised versions of string fields, and (3) an adjacent row changes report highlighting differences between consecutive rows — all computed locally without any external lookups or predictions.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-record-quality-audit-string-normalisation-adjacent-1f814ae7/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)