# Schema Conformity — Record Quality Audit + String Normalisation + IQR Outlier Flags

> Schema Conformity — Record Quality Audit + String Normalisation + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).

Runs three analytical reports on schema conformity data: a record quality audit, string normalisation, and IQR-based outlier flagging for valid_records and checked_records fields across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-203?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-record-quality-audit-string-normalisation-iqr-ce6f5053
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_A-42s13X-Sss_PqJgRMTw

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-iqr-ce6f5053 -d '<json body>'
```

Example prompt: Can you audit my schema conformity records for quality issues, normalise the strings, and flag any IQR outliers in the valid_records field? I have about 50 rows with columns row_id, dataset_group, date, valid_records, and checked_records.

## When to prefer this

Choose this endpoint when you need a bundled set of three data quality reports — record quality audit, string normalisation, and IQR outlier detection — on schema conformity metrics (valid_records, checked_records) for up to 200 rows at a flat cost. It is ideal for batch data quality checks on conformity tracking datasets where no live data lookup, prediction, or external action is needed. Prefer sibling endpoints if you need different analytical combinations such as daily sum series, histograms, or pivot tables.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, valid_records, checked_records) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- Invalid field enum value (anything other than valid_records or checked_records) causes an error
- Empty rows array is not accepted (minItems: 1)

## How this service works

Schema conformity — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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

Returns three independent analytical reports for the submitted schema conformity rows: (1) a record quality audit identifying completeness and consistency issues, (2) a string normalisation report cleaning up text fields, and (3) IQR-based outlier flags marking statistically anomalous values in the chosen numeric field (valid_records or checked_records). All analysis is performed locally on 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",
     "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-iqr-ce6f5053/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)