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Money Mind — Sample Size Calculator
x402
Money Mind — Sample Size Calculator is a paid API for AI agents from money-mind-extract.onrender.com, paid per call via x402, $0.31/call, status unknown (last checked 2026-10-18).
Computes the minimum number of observations required for a trading strategy test to have statistical power before running a backtest.
Price / call$0.31
Success—
StatusUnknown
How this service works
Pay-per-call adjudication for trading research. Eleven gates that killed 35 of our own concepts. Is your backtest real, is your price data real, is your t-stat inflated? USDC on Base, no account needed.
Output
Returns a JSON object with a 'reading' field containing a statistical interpretation and a 'verdict' field with a clear pass/fail or quantified recommendation on whether the dataset has enough observations for the test to be meaningful.
Example use cases
Pre-backtest power check for equity strategy
“I have 3 years of daily OHLCV data for a momentum strategy and want to know if that's enough observations before I start backtesting — can you calculate the required sample size to detect a realistic edge?”
Avoiding underpowered crypto DeFi test
“I'm about to test a DeFi yield farming strategy using 6 months of hourly data — tell me how many observations I actually need before this test can give a meaningful answer.”
Validating data sufficiency before ML model training
“We have 500 trades in our historical dataset for a machine learning-based trading model — is that sample large enough to produce a statistically valid result, or are we wasting our time?”
Technical details
Endpoint
POSThttps://money-mind-extract.onrender.com/samplesize?utm_source=zero.xyzWhen to prefer
Use this endpoint when you want to validate data sufficiency BEFORE investing time or money in a full backtest — it acts as a cheap ($0.31) pre-flight check that tells you whether your observations are enough to detect a real edge at meaningful statistical power. Prefer this over running a full backtest blindly, especially when working with limited historical data, short time windows, or rare trade signals. It is not a substitute for the full multi-gate adjudication endpoint but is the fastest and cheapest first gate.
Side effects
- Missing or malformed 'body' in the input object returns a validation error
- Insufficient test parameter details may produce a low-confidence or inconclusive verdict
- Payment failure via USDC on Base prevents the call from being processed
- Endpoint may time out or return 503 if the render.com host is cold-starting
- Ambiguous or underspecified strategy parameters may yield a generic rather than precise sample size estimate
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"reading": "...",
"verdict": "..."
}
}Tags
x402
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