Delx Commerce — Bitcoin 30-Minute Up/Down Prediction is a paid API for AI agents from commerce.delx.ai, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-01).
Returns a probabilistic up/down prediction for Bitcoin price movement over the next 30 minutes, based on caller-supplied price observations.
Pay-per-result APIs for agents. No signup. Exact price. Verifiable delivery. USDC on Base + Solana via x402.
Returns a JSON object with the asset (BTC), prediction schema version, status ('estimate'), the directional lean ('up' or 'down'), probability of up (p_up) and down (p_down), a data quality score and label, the model version and caveats (e.g. uncalibrated probability), the 30-minute horizon, and warnings such as 'not_trading_advice' and 'probability_is_uncalibrated'.
POSThttps://commerce.delx.ai/api/v1/x402/bitcoin-up-down-30m?utm_source=zero.xyzChoose this endpoint when you need a lightweight, pay-per-call Bitcoin short-term directional signal without requiring account registration, and when you can supply your own historical price observations. It is ideal for autonomous agents that need a verifiable, priced prediction for BTC over a 30-minute horizon using caller-supplied data rather than live market feeds. Prefer alternatives if you need calibrated probabilities for financial decisions, multi-asset coverage, or longer forecast horizons.
| Field | Type | Description |
|---|---|---|
| fee_bps | integer | |
| observations | array | |
| market_up_price | number | |
| market_down_price | number | |
| window_open_price | number | |
| window_close_timestamp | integer |
{
"type": "json",
"example": {
"asset": "BTC",
"model": {
"version": "delx-local-updown-v1",
"no_live_market_data": true,
"probability_is_uncalibrated": true,
"deterministic_for_same_input": true
},
"schema": "delx/prediction-updown-estimate/v1",
"status": "estimate",
"estimate": {
"lean": "up",
"p_up": 0.800833,
"p_down": 0.199167
},
"warnings": [
"caller_supplied_prices_not_verified",
"probability_is_uncalibrated",
"not_trading_advice"
],
"data_quality": {
"label": "adequate_input_coverage",
"score": 0.758333,
"observations_used": 8
},
"horizon_minutes": 30,
"input_provenance": "caller_supplied"
}
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