Outlier detection (IQR + z-score)
POST /api/outliersFlag outliers in a numeric series using either the IQR rule (Tukey fences at 1.5·IQR - robust, default) or z-score (|z| > threshold - assumes normality). Send POST /api/outliers with the required field values and pay $0.001 per call over x402 or MPP, or call it free by solving a proof-of-work challenge. It returns a JSON object with method, n, threshold, lowerBound, upperBound and 2 more.
Returns the outlier values + their indices + the thresholds used so you can decide whether to trust them.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
values | array | yes | Numeric series (max 10000, at least 4 values) Also accepted as data, series, numbers, nums, points. |
method | string | no | "iqr" (default) or "zscore" |
threshold | number | no | IQR multiplier (default 1.5) or z-score cutoff (default 3) |
Example request
curl -i -X POST https://agent402.tools/api/outliers \
-H "Content-Type: application/json" \
-d '{"values":[1,2,3,4,5,6,7,8,9,100],"method":"iqr"}'
Without payment this returns HTTP 402 Payment Required with the exact price for outliers; any x402 v2 or MPP client pays it and retries.
Example response
{
"method": "iqr",
"n": 10,
"threshold": 1.5,
"lowerBound": -4.625,
"upperBound": 14.375,
"outliers": [
{
"index": 9,
"value": 100
}
],
"outlierCount": 1
}
| Field | Type | Always present | In the example |
|---|---|---|---|
method | string | yes | iqr |
n | number | yes | 10 |
threshold | number | yes | 1.5 |
lowerBound | number | yes | -4.625 |
upperBound | number | yes | 14.375 |
outliers | array of objects | yes | 1 item in the example |
outlierCount | number | yes | 1 |
From an MCP client
catalog.call {
"slug": "outliers",
"params": {
"values": [
1,
2,
3,
4,
5,
6,
7,
8,
9,
100
],
"method": "iqr"
}
}
On the hosted connector at https://agent402.tools/mcp, catalog.call runs outliers free (rate-limited, no wallet). Local install: npx -y agent402-mcp.
Errors and behavior
valuesis required. An input the tool rejects returns an HTTP 4xx whose body carrieserror,tool,expected,requiredandexample, so the caller can correct it.- A paid call that ends in any status of 400 or above is not charged over x402, MPP or a prepaid credits key: settlement is cancelled when the tool fails. The exception is a Tempo push credential, a transfer the buyer sent before the call: it settles before the tool runs, so if the tool then fails the payment is recorded as a refund owed to the paying wallet.
- Free tier: no outbound network call leaves the server for this tool, so proof-of-work (16 leading zero bits of sha256) pays for it.
- A
GETorHEADto /api/outliers returns the same 402 quote, so the price can be read without a body. - An
Idempotency-Keyheader makes a retried paid call replay the first 200 instead of charging again (an answer larger than 1 MB is not replayed).
Paid call (JavaScript agent)
import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";
const client = new x402Client();
client.setSpendControls?.(false); // keep your own spending ceiling in code
registerExactEvmScheme(client, { signer: privateKeyToAccount(KEY) });
const payFetch = wrapFetchWithPayment(fetch, client);
const res = await payFetch("https://agent402.tools/api/outliers", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
"values": [
1,
2,
3,
4,
5,
6,
7,
8,
9,
100
],
"method": "iqr"
}),
});
No wallet? Pay with compute
Fetch a challenge, solve the sha256 puzzle (16 leading zero bits, a fraction of a second of CPU), and resend with the X-Pow-Solution header:
import { createHash } from "node:crypto";
const lz = (b) => { let t = 0; for (const x of b) { if (!x) { t += 8; continue; } t += Math.clz32(x) - 24; break; } return t; };
const c = await (await fetch("https://agent402.tools/api/pow/challenge?slug=outliers")).json();
let n = 0;
while (lz(createHash("sha256").update(c.challenge + ":" + n).digest()) < c.difficulty) n++;
await fetch("https://agent402.tools/api/outliers", { method: "POST", headers: { "X-Pow-Solution": c.token + ":" + n, "Content-Type": "application/json" }, body: JSON.stringify({"values":[1,2,3,4,5,6,7,8,9,100],"method":"iqr"}) });
Part of these workflows
Outlier detection (IQR + z-score) is one step in these 2 skill packs, each sold as a single call:
- Trend analysis - Take any numeric time series - a stock's daily close, a FRED macro indicator, a treasury yield history - and run it through the full quantitative workup: descriptives, moving averages, trend line, outliers, optional correlation against a benchmark, and a deterministic forecast forward with a 95% prediction interval. Everything an analyst writes a notebook for, in one chain of cheap calls.
- Number crunch - Statistical analysis suite: descriptive statistics, correlation analysis, and outlier detection on a single dataset.
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