# Schema Conformity Analytics — IQR Outlier Flags + Two-Measure Correlation

> Schema Conformity Analytics — IQR Outlier Flags + Two-Measure Correlation 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 IQR-based outlier detection and two-measure correlation analysis on schema conformity records (valid_records, checked_records) for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-176?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-analytics-iqr-outlier-flags-two-measure-correlation-98af941e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_72ywSaLw058G6hCgBRYs6

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-analytics-iqr-outlier-flags-two-measure-correlation-98af941e -d '<json body>'
```

Example prompt: Can you run IQR outlier detection and a two-measure correlation report on my schema conformity data — I have about 50 rows with valid_records and checked_records fields across multiple dataset groups, and I want to see which rows are flagged as outliers and how the two measures relate to each other?

## When to prefer this

Choose this endpoint when you have schema conformity or data validation metrics (valid_records, checked_records) and need both outlier detection and correlation analysis in a single low-cost call. It is ideal for data quality monitoring workflows where you want to flag anomalous batches and understand the relationship between two related count measures without any external data lookup or prediction.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — rejected with maxItems error
- Missing required fields (row_id, date, valid_records, checked_records) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Null values in both measures may reduce correlation reliability
- Insufficient variance in data may produce degenerate IQR or correlation results

## How this service works

Schema conformity — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two independent analytical reports: (1) IQR outlier flags identifying which rows have valid_records or checked_records values that fall outside the interquartile range bounds, and (2) a two-measure correlation report quantifying the statistical relationship between valid_records and checked_records across the supplied rows.

## 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-analytics-iqr-outlier-flags-two-measure-correlation-98af941e/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)