# Schema Conformity Base-100 Series and IQR Outlier Flags

> Schema Conformity Base-100 Series and 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 2026-10-18).

Computes a base-100 indexed time series and IQR-based outlier flags for schema conformity metrics (valid_records, checked_records) across up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-164?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-base-100-series-and-iqr-outlier-flags-1bd02db3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_osJvNPwsXEgEn_cojtove

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-base-100-series-and-iqr-outlier-flags-1bd02db3 -d '<json body>'
```

Example prompt: Can you run a base-100 series and IQR outlier analysis on my schema conformity data — I have 50 rows with valid_records and checked_records fields, starting the index at row 0, and I want to analyze the valid_records column?

## When to prefer this

Choose this endpoint when you have tabular schema conformity data (valid_records, checked_records) and need both a normalized base-100 trend series and IQR outlier detection in a single call for up to 200 rows. Ideal for data quality monitoring pipelines, audit reporting, and batch anomaly detection without requiring an external analytics platform. Not suitable for live data lookups, predictions, or datasets exceeding 200 rows.

## Known failure modes

- Fewer than 1 row submitted — minimum 1 row required
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, valid_records, checked_records) on any row
- Invalid date format — must match YYYY-MM-DD pattern
- base_index references a row index outside the supplied dataset
- All values null for the selected field — insufficient data for IQR computation
- Invalid field enum value — must be 'valid_records' or 'checked_records'

## How this service works

Schema conformity — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags 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 analytical reports: (1) a base-100 indexed time series for the selected field (valid_records or checked_records) relative to the specified base_index row, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range — all computed locally from 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-base-100-series-and-iqr-outlier-flags-1bd02db3/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)