# Schema Conformity Record Quality Audit + Deduplication + IQR Outlier Flags

> Schema Conformity Record Quality Audit + Deduplication + 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 records: a record quality audit, exact row deduplication, and IQR-based outlier flagging for valid_records or checked_records fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-220?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-deduplication-iqr-outlier-flags-80a94b71
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lgTo0cuZXNRMUgR2UBAGQ

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-deduplication-iqr-outlier-flags-80a94b71 -d '<json body>'
```

Example prompt: Can you run a record quality audit, exact deduplication check, and IQR outlier detection on my schema conformity data? I'm analyzing the valid_records field across these rows: row-1 (group-a, 2025-01-01, valid=95, checked=100), row-2 (group-b, 2025-01-02, valid=80, checked=100), row-3 (group-a, 2025-01-01, valid=95, checked=100), row-4 (group-c, 2025-01-03, valid=5, checked=100).

## When to prefer this

Choose this endpoint when you need three bundled data quality reports (audit + dedup + outlier detection) on schema conformity data in a single low-cost call. Ideal for datasets up to 200 rows where you want IQR-based statistical outlier detection alongside exact duplicate removal and a quality audit, without needing external data sources or predictions. Best suited for batch pre-processing of conformity tracking data before downstream ETL or reporting pipelines.

## Known failure modes

- Exceeds 200-row limit — request rejected
- Missing required fields (row_id, date, valid_records, checked_records) — validation error
- Invalid date format (not YYYY-MM-DD) — schema rejection
- Invalid field enum value (not valid_records or checked_records) — error
- Empty rows array — minimum 1 item required
- Numeric values outside allowed range ±1,000,000,000,000 — schema rejection

## How this service works

Schema conformity — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + 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: (1) a record quality audit summarizing completeness and field-level issues, (2) an exact row deduplication report identifying identical rows, and (3) IQR-based outlier flags on the selected 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-deduplication-iqr-outlier-flags-80a94b71/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)