# Feature Availability Numeric Interval Filter + IQR Outlier Flags

> Feature Availability Numeric Interval Filter + 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 2026-10-20).

Filters feature availability records by a numeric interval and flags IQR-based outliers across populated_features or expected_features, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-130?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/feature-availability-numeric-interval-filter-iqr-outlier-flags-2072ad8f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4bhWRZyYEaD54-J4yn4pu

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 feature-availability-numeric-interval-filter-iqr-outlier-flags-2072ad8f -d '<json body>'
```

Example prompt: Analyze my feature availability data for rows from group-a and group-b dated 2026-10-01 through 2026-10-04 — filter the populated_features field to only rows between 0 and 100, and flag any IQR outliers across all 4 rows.

## When to prefer this

Choose this endpoint when you need simultaneous numeric range filtering and IQR outlier detection on feature availability records (populated_features / expected_features) in a single $0.01 call, without requiring any external lookups or live data connections. Ideal for data quality pipelines checking ML feature store completeness or flagging anomalous population counts across dataset groups.

## Known failure modes

- Missing required fields (row_id, date, populated_features, expected_features) cause validation errors
- More than 200 rows submitted exceeds the per-call limit
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Minimum value greater than maximum value may produce empty interval results
- Null values in the selected field may affect IQR computation
- Payment not processed or insufficient USDC balance blocks the request

## How this service works

Feature availability — Numeric interval filter + IQR outlier flags: Numeric interval filter + IQR outlier flags for supplied feature availability records (populated_features, expected_features). 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 reports: (1) rows matching the specified numeric interval for the chosen field, and (2) IQR-based outlier flags indicating which rows fall outside the interquartile range — both computed locally against the supplied data with no external calls.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "populated_features",
     "expected_features"
    ],
    "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
     },
     "expected_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "populated_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_features": 1,
     "populated_features": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_features": 2,
     "populated_features": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_features": 3,
     "populated_features": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_features": 4,
     "populated_features": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "populated_features",
    "expected_features"
   ],
   "type": "string",
   "default": "populated_features"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-numeric-interval-filter-iqr-outlier-flags-2072ad8f/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)