# SignalDesk AI IQR Outlier Detection

> SignalDesk AI IQR Outlier Detection is a paid API for AI agents from x402-agent.kariguetoazul.workers.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-13).

Detects statistical outliers in a numeric dataset using the interquartile range (IQR) method, returning quartiles, IQR, fence bounds, and the list of outlying values.

## Facts

- Endpoint: POST https://x402-agent.kariguetoazul.workers.dev/api/stats/iqr-outliers?utm_source=zero.xyz
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-13
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/signaldesk-ai-iqr-outlier-detection-53def870
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nJEPUb-RZTWUURmSgDKDo

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 signaldesk-ai-iqr-outlier-detection-53def870 -d '<json body>'
```

Example prompt: Can you find the statistical outliers in this list of numbers using IQR? Here are my values: [2, 3, 4, 2, 3, 100, 4, 3, 2, 4, 3].

## When to prefer this

Choose this endpoint when you need a fast, low-cost, stateless IQR-based outlier computation on a raw numeric array of up to 1000 values. It is ideal for agent pipelines that need to flag anomalies before further processing, or for data cleaning steps in automated workflows. Prefer this over a full statistical library call when operating within a serverless or agent environment that requires a pay-per-use micropayment model. Not suitable for streaming data, time-series-aware outlier detection, or datasets exceeding 1000 observations.

## Known failure modes

- Empty or missing 'values' array returns validation error
- Array exceeds 1000 items — request rejected with size error
- Non-numeric or non-finite values in the array may cause rejection or NaN results
- Payment not provided or insufficient USDC balance returns HTTP 402
- Values outside ±1,000,000,000,000,000 range rejected by schema validation
- Single-element arrays may produce degenerate IQR=0 results

## How this service works

Evidence-backed autonomous AI jobs and paid data tools. Queue/D1/cron run outside the chat; free quotas and bounded execution apply.

## Output

Returns a JSON object containing: q1 (first quartile), q3 (third quartile), iqr (interquartile range), lower (lower fence = Q1 - 1.5*IQR), upper (upper fence = Q3 + 1.5*IQR), and outliers (array of values from the input that fall outside the fences).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "values": {
   "type": "array",
   "items": {
    "type": "number",
    "maximum": 1000000000000000,
    "minimum": -1000000000000000
   },
   "maxItems": 1000,
   "minItems": 1,
   "description": "Up to 1000 finite observations."
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "q1": 2,
  "q3": 4,
  "iqr": 2,
  "lower": -1,
  "upper": 7,
  "outliers": [
   100
  ]
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/signaldesk-ai-iqr-outlier-detection-53def870/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from x402-agent.kariguetoazul.workers.dev](https://www.zero.xyz/host/x402-agent.kariguetoazul.workers.dev/llms.txt)