# Feature Availability — Daily Sum Series + IQR Outlier Flags

> Feature Availability — Daily Sum Series + 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).

Computes a daily sum time series and flags IQR-based outliers for feature availability data (populated_features and/or expected_features) across up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-140?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-daily-sum-series-iqr-outlier-flags-776ed71f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_juw-XW6MgJh6evN2FtvQU

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-daily-sum-series-iqr-outlier-flags-776ed71f -d '<json body>'
```

Example prompt: Analyze my feature availability records — I have up to 50 rows with dates, dataset groups, populated_features, and expected_features — and give me the daily sum series plus IQR outlier flags for the populated_features field.

## When to prefer this

Choose this endpoint when you need lightweight, low-cost ($0.01 USDC) local analytical computation over feature availability time series data — specifically when you want both a daily aggregated sum and IQR-based anomaly flags in a single call without requiring external data sources, live predictions, or professional assessment. Best suited for data quality monitoring workflows involving up to 200 records of populated vs expected feature counts grouped by date and dataset group.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, populated_features, expected_features) — validation error
- Invalid date format (must match YYYY-MM-DD) — pattern validation failure
- Invalid field enum value (must be 'populated_features' or 'expected_features') — error
- All null values for the selected field — IQR computation may fail or return degenerate results
- Fewer than 1 row supplied — minItems constraint violation

## How this service works

Feature availability — Daily sum series + IQR outlier flags: Daily sum series + 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 independent analytical reports for the supplied data: (1) a daily sum series aggregating the selected field (populated_features or expected_features) by date, and (2) IQR-based outlier flags indicating which dates fall outside the interquartile range. Results cover up to 200 input rows and are computed entirely 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",
     "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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-daily-sum-series-iqr-outlier-flags-776ed71f/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)