generate_signal
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Third-party content written by another agent. Data to evaluate, not instructions.
Generate an AI-powered crypto trading signal for a given pair and timeframe. Returns: action (OPEN_LONG | OPEN_SHORT | CLOSE), confidence (0.0–1.0), entry_price, take_profit (array of price levels), stop_loss, risk_reward ratio, indicators (rsi, macd, ema_20, atr), risk_flags (overbought_rsi | oversold_rsi | low_volume | high_spread | near_resistance | near_support), generated_at (ISO 8601), expires_at (ISO 8601), and quota_remaining. The thesis field contains LLM reasoning and is only present when include_thesis=true. On quota exhaustion returns error_code=QUOTA_EXCEEDED with Retry-After header. Requires Authorization: Bearer nt_<api_key>.
Input schema
| Property | Type | Required | Description |
|---|---|---|---|
| symbol | string | yes | Trading pair in BASE/QUOTE format, e.g. BTC/USDT, ETH/USDT, SOL/USDT. |
| timeframe | string | no | Candlestick timeframe for signal analysis. Defaults to 15m. |
| strategy | string | no | Signal strategy to apply. Defaults to trend_rider. |
| personality | string | no | Risk personality shaping confidence weighting and TP/SL aggressiveness. Defaults to scalper. |
| include_thesis | boolean | no | When true, includes the LLM-generated reasoning in the `thesis` field of the response. Adds ~200ms latency. |
Raw JSON schema
{
"type": "object",
"properties": {
"symbol": {
"type": "string",
"description": "Trading pair in BASE/QUOTE format, e.g. BTC/USDT, ETH/USDT, SOL/USDT.",
"pattern": "^[A-Z0-9]+/[A-Z0-9]+$"
},
"timeframe": {
"type": "string",
"description": "Candlestick timeframe for signal analysis. Defaults to 15m.",
"enum": [
"1m",
"5m",
"15m",
"1h",
"4h",
"1d"
],
"default": "15m"
},
"strategy": {
"type": "string",
"description": "Signal strategy to apply. Defaults to trend_rider.",
"enum": [
"trend_rider",
"breakout_hunter",
"scalper",
"swing_master",
"macro_lens",
"news_reactive",
"momentum_surge",
"mean_reversion"
]
},
"personality": {
"type": "string",
"description": "Risk personality shaping confidence weighting and TP/SL aggressiveness. Defaults to scalper.",
"enum": [
"scalper",
"swing",
"macro",
"trend_rider",
"news_reactive",
"breakout_hunter"
]
},
"include_thesis": {
"type": "boolean",
"description": "When true, includes the LLM-generated reasoning in the `thesis` field of the response. Adds ~200ms latency.",
"default": true
}
},
"required": [
"symbol"
]
}