Forecast (Holt linear trend)
POST /api/forecast-holtHolt's linear trend method - level + trend (no seasonality). Send POST /api/forecast-holt with the required fields values and horizon 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, horizon, alpha, beta and 1 more.
Two smoothing parameters: alpha (level) and beta (trend). Forecast extrapolates as a straight line from the last fitted level along the last fitted trend, so it grows or shrinks linearly with horizon. Use this when your series has a persistent up/down trend but no seasonal cycle (e.g. a SaaS MRR climb, a deflating cohort retention curve).
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
values | array | yes | Numeric series in chronological order (max 10000, min 4) Also accepted as data, series, numbers, nums, points. |
horizon | number | yes | Number of future periods to forecast (1 to 1000) Also accepted as periods, steps, ahead, forecast. |
alpha | number | no | Level smoothing, 0 < alpha < 1 (default 0.5) |
beta | number | no | Trend smoothing, 0 < beta < 1 (default 0.3) |
Example request
curl -i -X POST https://agent402.tools/api/forecast-holt \
-H "Content-Type: application/json" \
-d '{"values":[100,105,111,118,124,131,137,144,150,157],"horizon":3,"alpha":0.5,"beta":0.3}'
Without payment this returns HTTP 402 Payment Required with the exact price for forecast-holt; any x402 v2 or MPP client pays it and retries.
Example response
{
"method": "holt",
"n": 10,
"horizon": 3,
"alpha": 0.5,
"beta": 0.3,
"forecast": [
{
"step": 1,
"point": 163.2012,
"lower95": 161.6463,
"upper95": 164.756
},
{
"step": 2,
"point": 169.7416,
"lower95": 167.8871,
"upper95": 171.596
},
{
"step": 3,
"point": 176.282,
"lower95": 174.049,
"upper95": 178.515
}
]
}
| Field | Type | Always present | In the example |
|---|---|---|---|
method | string | yes | holt |
n | number | yes | 10 |
horizon | number | yes | 3 |
alpha | number | yes | 0.5 |
beta | number | yes | 0.3 |
forecast | array of objects | yes | 3 items in the example |
From an MCP client
catalog.call {
"slug": "forecast-holt",
"params": {
"values": [
100,
105,
111,
118,
124,
131,
137,
144,
150,
157
],
"horizon": 3,
"alpha": 0.5,
"beta": 0.3
}
}
On the hosted connector at https://agent402.tools/mcp, catalog.call runs forecast-holt free (rate-limited, no wallet). Local install: npx -y agent402-mcp.
Errors and behavior
valuesandhorizonare 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/forecast-holt 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/forecast-holt", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
"values": [
100,
105,
111,
118,
124,
131,
137,
144,
150,
157
],
"horizon": 3,
"alpha": 0.5,
"beta": 0.3
}),
});
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=forecast-holt")).json();
let n = 0;
while (lz(createHash("sha256").update(c.challenge + ":" + n).digest()) < c.difficulty) n++;
await fetch("https://agent402.tools/api/forecast-holt", { method: "POST", headers: { "X-Pow-Solution": c.token + ":" + n, "Content-Type": "application/json" }, body: JSON.stringify({"values":[100,105,111,118,124,131,137,144,150,157],"horizon":3,"alpha":0.5,"beta":0.3}) });
Part of these workflows
Forecast (Holt linear trend) 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.
- Forecasting bake-off - Don't guess which forecasting method to trust. Backtest all four (naive/drift, SES, Holt, Holt-Winters) on a real series, rank by out-of-sample RMSE, then forecast forward with the winner and its 95% prediction interval. Method selection without the hand-waving.
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