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Delx Multi-Outcome Normalize
x402
Delx Multi-Outcome Normalize is a paid API for AI agents from api.delx.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-15).
Normalizes an array of prices into probability weights that sum to 1.0, returning proportional probabilities for each outcome.
Price / call$0.001
Success—
StatusUnknown
How this service works
Normalize multi-outcome prices into a probability simplex. Call when turning raw multi-outcome quotes into probs that sum to 1. Returns normalized probs and sum as deterministic JSON for $0.001 USDC via x402 on Base. First-party local math only—no RPC, live market feed, API keys, storage, or mediagen. Advisory only; the caller owns capital, risk, and production controls.
Output
Returns a JSON object containing: 'n' (count of input prices), 'sum' (total of all prices), 'prices' (the original input array), 'probs' (array of normalized probability values for each price, proportional to its share of the sum, summing to 1.0), and 'schema' identifier ('delx/util-multi-outcome-normalize/v1').
Example use cases
Prediction market probability display
“I have outcome prices [0.15, 0.35, 0.50] from a prediction market — can you normalize them into probabilities so I can show each outcome's implied likelihood as a percentage?”
Multi-option bid weight allocation
“I need to allocate budget proportionally across three bids priced at 0.4, 0.8, and 1.2 — normalize those prices into probability weights so I know what fraction to assign each.”
Agent scoring result ranking
“My agent scored three candidate answers at 0.1, 0.5, and 0.9 — normalize those scores into a probability distribution so I can sample from them proportionally.”
Technical details
Endpoint
POSThttps://api.delx.ai/api/v1/x402/multi-outcome-normalizeWhen to prefer
Use this endpoint when you have a list of numeric outcome prices or scores and need to convert them into a valid probability distribution (values summing to 1.0). Ideal for prediction markets, multi-armed bandit sampling, proportional budget allocation, or any scenario where raw scores must be normalized before probabilistic decision-making. Prefer this over manual computation when you need a governed, auditable, low-latency utility call within an agent workflow.
Side effects
- Empty prices array returns undefined behavior or error
- Non-numeric values in the prices array cause validation failure
- All-zero prices array causes division-by-zero error
- Malformed JSON body returns 400 error
- Single-element array returns probability of 1.0 trivially
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| prices | array | Input field: prices. |
Output
Schema · Response
{
"type": "json",
"example": {
"n": 3,
"sum": 1.1,
"probs": [
0.1818181818181818,
0.2727272727272727,
0.5454545454545454
],
"prices": [
0.2,
0.3,
0.6
],
"schema": "delx/util-multi-outcome-normalize/v1"
}
}Tags
x402
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