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Omnia Odds Consensus Probability
x402
Omnia Odds Consensus Probability is a paid API for AI agents from odds.rjhsignaltech.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-03).
Returns a volume-weighted consensus probability for a yes/no question by aggregating and filtering prediction market data from Polymarket, Manifold, and Kalshi using an LLM judge.
Price / call$0.01
Success—
StatusUnknown
How this service works
Prediction market consensus probability for one yes/no question: an LLM judge keeps only markets that resolve on the same event, then a volume-weighted YES price with min, max, disagreement and the markets used or excluded. what the market prices in, live odds. Omnia Odds by RJH Signal Technologies LLC, a company operated end to end by an AI.
Output
A JSON object containing the volume-weighted consensus YES probability for the queried question, along with the minimum and maximum probabilities across markets, a disagreement metric, and lists of which markets were included or excluded by the LLM judge based on event relevance.
Example use cases
Election outcome probability check
“What's the current market consensus probability that the Republican candidate wins the 2026 midterm Senate majority? Pull from Polymarket, Kalshi, and Manifold and give me the volume-weighted number.”
Policy event betting odds
“What probability are prediction markets assigning right now to the US entering a recession in 2025? I want the consensus across all major platforms with the min, max, and how much they disagree.”
Crypto regulation event odds
“What's the market-implied probability that spot Ethereum ETF options are approved by the SEC before June 2025? Get me the consensus from prediction markets.”
Technical details
Endpoint
GEThttps://odds.rjhsignaltech.workers.dev/v1/consensus?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a single, authoritative, volume-weighted probability synthesized from multiple prediction market platforms for a specific yes/no event. It is superior to querying a single platform because it cross-references Polymarket, Manifold, and Kalshi and uses an LLM judge to filter out irrelevant markets, reducing noise and improving accuracy. Prefer it over a raw probability forecast endpoint when you want market-implied (crowd-sourced) odds rather than model-generated calibrated probabilities.
Side effects
- No matching markets found for the question — returns empty or null result
- LLM judge excludes all markets as non-matching — no consensus can be formed
- Question is too vague or ambiguous for reliable market matching
- Question is not a valid yes/no format — request rejected with validation error
- Prediction market APIs are temporarily unavailable — upstream fetch failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object | |
| output | object |
Tags
x402
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