# Data Freshness — Numeric Row Ordering & IQR Outlier Flags

> Data Freshness — Numeric Row Ordering & 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 2026-10-22).

Ranks rows by age_minutes or record_count and flags IQR-based outliers in supplied data freshness records, producing two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-06-119?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-freshness-numeric-row-ordering-iqr-outlier-flags-68655240
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2JWwr6NLJ9a6kGDhZ8xM9

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 data-freshness-numeric-row-ordering-iqr-outlier-flags-68655240 -d '<json body>'
```

Example prompt: Can you rank these data freshness records by age_minutes and flag any IQR outliers? I have 4 rows: row-1 (group-a, 2026-10-01, age=10, count=1), row-2 (group-b, 2026-10-02, age=20, count=2), row-3 (group-a, 2026-10-03, age=15, count=3), row-4 (group-b, 2026-10-04, age=30, count=4) — give me both the ordering report and the outlier flags for age_minutes.

## When to prefer this

Choose this endpoint when you have up to 200 data freshness records with age_minutes and/or record_count fields and need both a ranked ordering and IQR-based outlier detection in a single low-cost call ($0.01 USDC). It is ideal for local, deterministic statistical analysis without any external data lookups, predictions, or side effects. Prefer this over generic analytics services when your domain is specifically data pipeline/freshness monitoring and you want two reports (ordering + outlier flags) in one request.

## Known failure modes

- Input array is empty (minItems:1 violated) — validation error
- More than 200 rows submitted — request rejected
- Missing required fields (row_id, date, dataset_group, age_minutes, record_count) — validation error
- Invalid date format (must match YYYY-MM-DD) — schema validation failure
- Field enum value not 'age_minutes' or 'record_count' — rejected
- All values null for selected field — IQR computation may be undefined
- Payment not attached or insufficient (requires 0.01 USDC via x402) — 402 response

## How this service works

Data freshness — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied data freshness records (age_minutes, record_count). 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) rows ordered/ranked by the selected numeric field (age_minutes or record_count), and (2) IQR-based outlier flags identifying which rows fall below Q1-1.5×IQR or above Q3+1.5×IQR. No external lookups or predictions are made — analysis is purely local and deterministic based on the supplied data.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "age_minutes",
     "record_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "age_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "record_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "age_minutes": 10,
     "record_count": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "age_minutes": 20,
     "record_count": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "age_minutes": 15,
     "record_count": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "age_minutes": 30,
     "record_count": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "age_minutes",
    "record_count"
   ],
   "type": "string",
   "default": "age_minutes"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-freshness-numeric-row-ordering-iqr-outlier-flags-68655240/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)