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Money Mind A/B Test Adjudication
x402
Money Mind A/B Test Adjudication 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).
Corrects A/B test results for multiple-comparison bias and determines whether variant B genuinely beat variant A in a statistically valid way.
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 'verdict' (pass/fail or real/not real judgment) and a 'reading' (detailed statistical explanation of whether variant B genuinely beat variant A after correcting for how many variants were compared).
Example use cases
Validating a split-test winner across many variants
“I ran an A/B test on my ad campaign with 8 variants and variant D beat the control with p=0.03 — but I'm worried I p-hacked it. Can you correct for all 8 comparisons and tell me if variant D is a genuine winner?”
Checking a trading strategy A/B result
“I backtested two versions of my momentum strategy and version B had a higher Sharpe ratio, but I tried about 15 parameter combinations before picking these two final candidates. Is version B's outperformance real after correcting for the 15 variants I evaluated?”
Audit an experiment before going to production
“Before I ship this product change, I want to make sure my A/B test holds up — I compared 5 variants total and the winner had a t-stat of 2.1. Can Money Mind tell me if that's statistically valid after multiple-comparison correction, or if I should keep testing?”
Technical details
Endpoint
POSThttps://money-mind-extract.onrender.com/abtest?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have an A/B test or experiment result and need to determine whether the winner is statistically valid after accounting for the number of variants compared (multiple-comparison correction). Especially useful when you suspect p-hacking, data dredging, or inflated t-statistics from testing many variants before reporting. Prefer this over a generic stats library when you want a pay-per-call, no-account-needed adjudication with a plain-language verdict.
Side effects
- Missing required body fields causes validation error
- Insufficient data in the test body to compute correction
- Payment of 0.31 USDC not provided or rejected — 402 response
- Malformed HTTP input object returns schema error
- Ambiguous or incomplete variant count may produce unreliable correction
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"reading": "...",
"verdict": "..."
}
}Tags
x402
Reviews
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