# SignalDesk AI Z-Score Calculator

> SignalDesk AI Z-Score Calculator 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).

Computes z-scores, mean, and standard deviation for a numeric dataset of up to 1000 observations

## Facts

- Endpoint: POST https://x402-agent.kariguetoazul.workers.dev/api/stats/z-scores?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-z-score-calculator-71729a87
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_C2_tyujCrjMv0WwrL8YMW

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-z-score-calculator-71729a87 -d '<json body>'
```

Example prompt: Can you calculate the z-scores for these numbers: [12, 15, 14, 10, 18, 22, 11]? I want to know which values are statistical outliers.

## When to prefer this

Choose this endpoint when you need fast, serverless z-score computation without standing up your own statistical infrastructure. It is ideal for anomaly detection, outlier flagging, or data normalization pipelines where you have up to 1000 observations and want a pay-per-call model at $0.001 USDC.

## Known failure modes

- Empty array or missing 'values' field returns a validation error
- Array exceeding 1000 items is rejected
- Non-finite numbers (Infinity, NaN) are rejected due to min/max bounds
- Single-element arrays will have a standard deviation of 0, causing division-by-zero behavior
- Payment failure or insufficient USDC balance blocks execution

## 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 the array of z-scores (one per input value), the mean of the input dataset, and the standard deviation. Z-scores indicate how many standard deviations each observation is from the mean.

## 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": {
  "mean": 2,
  "z_scores": [
   -1.224744871391589,
   0,
   1.224744871391589
  ],
  "standard_deviation": 0.816496580927726
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/signaldesk-ai-z-score-calculator-71729a87/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)