👑 King of Gold — Professional XAU/USD Trading Dashboard

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EMA Crossover ──\nconst maCrossover: Strategy = {\n id: \"ma-crossover\", name: \"EMA Crossover\", category: \"Trend\",\n description: \"Golden/Death cross between 9 and 21 EMA\",\n evaluate: (c) => {\n const closes = c.map((x: any) => x.close);\n if (closes.length < 50) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const e9 = ema(closes, 9), e21 = ema(closes, 21);\n const p9 = e9[e9.length - 2], p21 = e21[e21.length - 2];\n const c9 = e9[e9.length - 1], c21 = e21[e21.length - 1];\n if (p9 <= p21 && c9 > c21) return { signal: \"BUY\", score: 75, confidence: 70 };\n if (p9 >= p21 && c9 < c21) return { signal: \"SELL\", score: 75, confidence: 70 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 2. RSI Reversal ──\nconst rsiStrategy: Strategy = {\n id: \"rsi-reversal\", name: \"RSI Reversal\", category: \"Momentum\",\n description: \"Overbought/oversold RSI reversal\",\n evaluate: (c) => {\n const closes = c.map((x: any) => x.close);\n if (closes.length < 15) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const r = rsi(closes, 14);\n const last = r[r.length - 1];\n if (last < 30) return { signal: \"BUY\", score: 60, confidence: 65 };\n if (last > 70) return { signal: \"SELL\", score: 60, confidence: 65 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 3. MACD Momentum ──\nconst macdStrategy: Strategy = {\n id: \"macd-momentum\", name: \"MACD Momentum\", category: \"Momentum\",\n description: \"MACD histogram direction change\",\n evaluate: (c) => {\n const closes = c.map((x: any) => x.close);\n if (closes.length < 35) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const { histogram: h } = macd(closes);\n if (h[h.length - 2] < 0 && h[h.length - 1] > 0) return { signal: \"BUY\", score: 70, confidence: 68 };\n if (h[h.length - 2] > 0 && h[h.length - 1] < 0) return { signal: \"SELL\", score: 70, confidence: 68 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 4. Bollinger Squeeze ──\nconst bollingerStrategy: Strategy = {\n id: \"bollinger-squeeze\", name: \"Bollinger Squeeze\", category: \"Volatility\",\n description: \"Price touching bands after squeeze\",\n evaluate: (c) => {\n const closes = c.map((x: any) => x.close);\n if (closes.length < 21) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const { upper, lower } = bollinger(closes, 20, 2);\n const price = closes[closes.length - 1];\n if (price <= lower[lower.length - 1]) return { signal: \"BUY\", score: 65, confidence: 62 };\n if (price >= upper[upper.length - 1]) return { signal: \"SELL\", score: 65, confidence: 62 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 5. VWAP Deviation ──\nconst vwapStrategy: Strategy = {\n id: \"vwap-deviation\", name: \"VWAP Deviation\", category: \"Mean Reversion\",\n description: \"Price deviation from VWAP\",\n evaluate: (c) => {\n if (c.length < 20) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const v = vwap(c);\n const price = c[c.length - 1].close;\n const dev = (price - v[v.length - 1]) / v[v.length - 1];\n if (dev < -0.001) return { signal: \"BUY\", score: 55, confidence: 58 };\n if (dev > 0.001) return { signal: \"SELL\", score: 55, confidence: 58 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 6. Volume Spike ──\nconst volumeSpike: Strategy = {\n id: \"volume-spike\", name: \"Volume Spike\", category: \"Confirmation\",\n description: \"Volume spike confirming price move\",\n evaluate: (c) => {\n if (c.length < 20) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const vols = c.slice(-20).map((x: any) => x.volume);\n const avg = vols.slice(0, -1).reduce((a: number, b: number) => a + b, 0) / 19;\n const lastVol = vols[vols.length - 1];\n const up = c[c.length - 1].close > c[c.length - 2].close;\n if (lastVol > avg * 2) return { signal: up ? \"BUY\" : \"SELL\", score: 60, confidence: 60 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 7. S/R Breakout ──\nconst supportResistance: Strategy = {\n id: \"sr-breakout\", name: \"S/R Breakout\", category: \"Breakout\",\n description: \"Breakout above resistance or below support\",\n evaluate: (c) => {\n if (c.length < 50) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const lookback = c.slice(-50, -1);\n const resistance = Math.max(...lookback.map((x: any) => x.high));\n const support = Math.min(...lookback.map((x: any) => x.low));\n const close = c[c.length - 1].close;\n if (close > resistance * 1.001) return { signal: \"BUY\", score: 72, confidence: 65 };\n if (close < support * 0.999) return { signal: \"SELL\", score: 72, confidence: 65 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 8. ATR Trailing ──\nconst atrTrailing: Strategy = {\n id: \"atr-trailing\", name: \"ATR Trailing\", category: \"Trend\",\n description: \"Price beyond ATR trailing stop\",\n evaluate: (c) => {\n if (c.length < 22) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const a = atr(c, 14);\n const close = c[c.length - 1].close, prev = c[c.length - 2].close;\n if (close > prev + a * 2) return { signal: \"BUY\", score: 58, confidence: 55 };\n if (close < prev - a * 2) return { signal: \"SELL\", score: 58, confidence: 55 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 9. Stochastic Cross ──\nconst stochasticStrategy: Strategy = {\n id: \"stochastic-cross\", name: \"Stochastic Cross\", category: \"Momentum\",\n description: \"%K crossing %D in extreme zones\",\n evaluate: (c) => {\n if (c.length < 20) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const { k, d } = stochastic(c, 14, 3);\n const lk = k[k.length - 1], ld = d[d.length - 1];\n const pk = k[k.length - 2], pd = d[d.length - 2];\n if (pk < pd && lk > ld && lk < 20) return { signal: \"BUY\", score: 62, confidence: 60 };\n if (pk > pd && lk < ld && lk > 80) return { signal: \"SELL\", score: 62, confidence: 60 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 10. ADX Trend ──\nconst adxStrategy: Strategy = {\n id: \"adx-trend\", name: \"ADX Trend Strength\", category: \"Trend\",\n description: \"ADX above 25 with DI alignment\",\n evaluate: (c) => {\n if (c.length < 28) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const { adx: a, plusDI, minusDI } = adx(c.slice(-28), 14);\n if (a > 25 && plusDI > minusDI) return { signal: \"BUY\", score: 64, confidence: 62 };\n if (a > 25 && minusDI > plusDI) return { signal: \"SELL\", score: 64, confidence: 62 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 11. Ichimoku Cloud ──\nconst ichimokuStrategy: Strategy = {\n id: \"ichimoku-cloud\", name: \"Ichimoku Cloud\", category: \"Trend\",\n description: \"Price above/below cloud with TK cross\",\n evaluate: (c) => {\n if (c.length < 60) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const { tenkan, kijun, senkouA, senkouB } = ichimoku(c);\n const price = c[c.length - 1].close;\n const cT = Math.max(senkouA[senkouA.length - 1], senkouB[senkouB.length - 1]);\n const cB = Math.min(senkouA[senkouA.length - 1], senkouB[senkouB.length - 1]);\n const tk = tenkan[tenkan.length - 1] > kijun[kijun.length - 1];\n if (price > cT && tk) return { signal: \"BUY\", score: 68, confidence: 65 };\n if (price < cB && !tk) return { signal: \"SELL\", score: 68, confidence: 65 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 12. Fibonacci Retracement ──\nconst fibonacciStrategy: Strategy = {\n id: \"fib-retrace\", name: \"Fibonacci Retracement\", category: \"Pullback\",\n description: \"Bounce from 0.618 or 0.5 level\",\n evaluate: (c) => {\n if (c.length < 30) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const swing = c.slice(-30);\n const hi = Math.max(...swing.map((x: any) => x.high));\n const lo = Math.min(...swing.map((x: any) => x.low));\n const range = hi - lo;\n const price = c[c.length - 1].close;\n const fib618 = hi - range * 0.618, fib5 = hi - range * 0.5;\n const dist = Math.min(Math.abs(price - fib618), Math.abs(price - fib5));\n if (dist / range < 0.005) {\n const recent = c.slice(-5).reduce((a: number, x: any) => a + x.close, 0) / 5;\n if (recent > fib618) return { signal: \"BUY\", score: 58, confidence: 55 };\n return { signal: \"SELL\", score: 58, confidence: 55 };\n }\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 13. Pivot Points ──\nconst pivotStrategy: Strategy = {\n id: \"pivot-points\", name: \"Pivot Points\", category: \"Mean Reversion\",\n description: \"Price action around daily pivot\",\n evaluate: (c) => {\n if (c.length < 2) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const prev = c[c.length - 2];\n const pivot = (prev.high + prev.low + prev.close) / 3;\n const price = c[c.length - 1].close;\n const range = prev.high - prev.low;\n if (range > 0 && Math.abs(price - pivot) / range < 0.01) {\n return { signal: price > pivot ? \"BUY\" : \"SELL\", score: 50, confidence: 50 };\n }\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 14. Engulfing Pattern ──\nconst engulfingStrategy: Strategy = {\n id: \"engulfing\", name: \"Engulfing Pattern\", category: \"Price Action\",\n description: \"Bullish/Bearish engulfing candlestick\",\n evaluate: (c) => {\n if (c.length < 3) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const prev = c[c.length - 2], curr = c[c.length - 1];\n const pBody = Math.abs(prev.close - prev.open), cBody = Math.abs(curr.close - curr.open);\n if (cBody > pBody * 1.5) {\n if (prev.close < prev.open && curr.close > curr.open && curr.close > prev.open && curr.open < prev.close)\n return { signal: \"BUY\", score: 70, confidence: 68 };\n if (prev.close > prev.open && curr.close < curr.open && curr.close < prev.open && curr.open > prev.close)\n return { signal: \"SELL\", score: 70, confidence: 68 };\n }\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\n// ── 15. Morning/Evening Star ──\nconst morningStar: Strategy = {\n id: \"morning-evening-star\", name: \"Morning/Evening Star\", category: \"Price Action\",\n description: \"Three-candle reversal pattern\",\n evaluate: (c) => {\n if (c.length < 4) return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n const c1 = c[c.length - 3], c2 = c[c.length - 2], c3 = c[c.length - 1];\n const b1 = Math.abs(c1.close - c1.open), b2 = Math.abs(c2.close - c2.open), b3 = Math.abs(c3.close - c3.open);\n if (c1.close < c1.open && c3.close > c3.open && b2 < b1 * 0.3 && b3 > b1 * 0.8 && c2.close < c1.close && c3.open > c2.close)\n return { signal: \"BUY\", score: 72, confidence: 70 };\n if (c1.close > c1.open && c3.close < c3.open && b2 < b1 * 0.3 && b3 > b1 * 0.8 && c2.close > c1.close && c3.open < c2.close)\n return { signal: \"SELL\", score: 72, confidence: 70 };\n return { signal: \"NEUTRAL\", score: 0, confidence: 0 };\n },\n};\n\nexport const STRATEGIES: Strategy[] = [\n maCrossover, rsiStrategy, macdStrategy, bollingerStrategy, vwapStrategy,\n volumeSpike, supportResistance, atrTrailing, stochasticStrategy, adxStrategy,\n ichimokuStrategy, fibonacciStrategy, pivotStrategy, engulfingStrategy, morningStar,\n];\n\nexport interface StrategyResult {\n strategyId: string; name: string; signal: Signal; score: number;\n confidence: number; category: string;\n}\n\nexport function evaluateStrategies(timeframes: any, weights?: Record): StrategyResult[] {\n const results: StrategyResult[] = [];\n for (const s of STRATEGIES) {\n const w = weights?.[s.id] ?? 1.0;\n if (w <= 0) continue;\n const evalData = timeframes.m15 || timeframes.h1 || timeframes.h4 || timeframes.daily;\n if (!evalData || evalData.length < 5) continue;\n const res = s.evaluate(evalData);\n if (res.signal === \"NEUTRAL\") continue;\n results.push({\n strategyId: s.id, name: s.name, signal: res.signal,\n score: res.score * w, confidence: res.confidence, category: s.category,\n });\n }\n return results;\n}\n",[],[130,174,176],"45ee84f6-85fd-4a69-99bc-1dd1541c872f","market.ts","0621e3a4-82fd-11f1-82ac-1607ee4eb77e",6,["D",1784415866543],"import { getNextKey, exhaustKey } from \"./api-key-manager.ts\";\n\ninterface Candle {\n timestamp: number;\n open: number;\n high: number;\n low: number;\n close: number;\n volume: number;\n}\n\nconst cache = new Map();\nconst CACHE_TTL = 45000;\n\nexport async function fetchGoldData(interval = \"1min\", outputSize = 100): Promise {\n const cacheKey = `gold_${interval}_${outputSize}`;\n const cached = cache.get(cacheKey);\n if (cached && Date.now() - cached.ts < CACHE_TTL) return cached.data;\n\n let attempt = 0;\n while (attempt < 5) {\n const key = await getNextKey();\n if (!key) throw new Error(\"All API keys exhausted — set TWELVE_DATA_API_KEYS env var\");\n\n const ctrl = new AbortController();\n const timer = setTimeout(() => ctrl.abort(), 10000);\n try {\n const url = `https://api.twelvedata.com/time_series?symbol=XAU/USD&interval=${interval}&outputsize=${outputSize}`;\n const res = await fetch(url, {\n headers: { Authorization: `apikey ${key}` },\n signal: ctrl.signal,\n });\n clearTimeout(timer);\n\n if (res.status === 429) {\n await exhaustKey(key);\n attempt++;\n continue;\n }\n if (!res.ok) throw new Error(`HTTP ${res.status}`);\n\n const json = await res.json();\n if (!json.values) throw new Error(json.message || \"No values in response\");\n\n const candles: Candle[] = json.values.map((v: any) => ({\n timestamp: new Date(v.datetime).getTime(),\n open: parseFloat(v.open),\n high: parseFloat(v.high),\n low: parseFloat(v.low),\n close: parseFloat(v.close),\n volume: parseInt(v.volume || \"0\"),\n })).reverse();\n\n cache.set(cacheKey, { data: candles, ts: Date.now() });\n return candles;\n } catch (e) {\n clearTimeout(timer);\n attempt++;\n if (attempt >= 5) throw e;\n await new Promise((r) => setTimeout(r, 1000 * 2 ** attempt));\n }\n }\n throw new Error(\"All fetch attempts failed\");\n}\n\nexport async function getLivePrice(): Promise {\n const data = await fetchGoldData(\"1min\", 1);\n return data[data.length - 1].close;\n}\n\n// Fallback: generate simulated candles when no API key is configured\nexport function generateSimCandles(count = 100, basePrice = 2350): Candle[] {\n const candles: Candle[] = [];\n let price = basePrice;\n const now = Date.now();\n for (let i = count - 1; i >= 0; i--) {\n const change = (Math.random() - 0.48) * 3;\n const open = price;\n price = Math.max(1800, price + change);\n const high = Math.max(open, price) + Math.random() * 2;\n const low = Math.min(open, price) - Math.random() * 2;\n candles.push({\n timestamp: now - i * 60000,\n open,\n high,\n low,\n close: price,\n volume: 1000 + Math.random() * 5000,\n });\n }\n return candles;\n}\n",[],[130,174,184],"64938629-e424-40c7-8ce9-c3fc72e6df0d","indicators.ts","d6db7290-82fc-11f1-a610-1607ee4eb77e",["D",1784415787311],"// ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n// Technical Indicators — pure functions, no imports\n// ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nexport function sma(data: number[], period: number): number {\n if (data.length < period) return 0;\n return data.slice(-period).reduce((a, b) => a + b, 0) / period;\n}\n\nexport function ema(data: number[], period: number): number[] {\n const k = 2 / (period + 1);\n const out: number[] = [data[0]];\n for (let i = 1; i < data.length; i++) {\n out.push(data[i] * k + out[i - 1] * (1 - k));\n }\n return out;\n}\n\nexport function emaValue(data: number[], period: number): number {\n const arr = ema(data, period);\n return arr[arr.length - 1] || 0;\n}\n\nexport function rsi(closes: number[], period = 14): number[] {\n if (closes.length < period + 1) return [];\n const out: number[] = [];\n let gains = 0, losses = 0;\n for (let i = 1; i <= period; i++) {\n const ch = closes[i] - closes[i - 1];\n if (ch > 0) gains += ch; else losses -= ch;\n }\n let avgGain = gains / period;\n let avgLoss = losses / period;\n for (let i = period + 1; i < closes.length; i++) {\n const ch = closes[i] - closes[i - 1];\n const g = ch > 0 ? ch : 0;\n const l = ch < 0 ? -ch : 0;\n avgGain = (avgGain * (period - 1) + g) / period;\n avgLoss = (avgLoss * (period - 1) + l) / period;\n const rs = avgLoss === 0 ? 100 : avgGain / avgLoss;\n out.push(100 - 100 / (1 + rs));\n }\n return out;\n}\n\nexport function macd(closes: number[]): { macd: number[]; signal: number[]; histogram: number[] } {\n const e12 = ema(closes, 12);\n const e26 = ema(closes, 26);\n const m: number[] = closes.map((_, i) => (e12[i] || 0) - (e26[i] || 0));\n const sig = ema(m, 9);\n const hist: number[] = m.map((v, i) => v - (sig[i] || 0));\n return { macd: m, signal: sig, histogram: hist };\n}\n\nexport function bollinger(closes: number[], period = 20, mult = 2) {\n const middle: number[] = [], upper: number[] = [], lower: number[] = [];\n for (let i = period - 1; i < closes.length; i++) {\n const slice = closes.slice(i - period + 1, i + 1);\n const avg = slice.reduce((a, b) => a + b, 0) / period;\n const variance = slice.reduce((a, b) => a + (b - avg) ** 2, 0) / period;\n const std = Math.sqrt(variance);\n middle.push(avg);\n upper.push(avg + std * mult);\n lower.push(avg - std * mult);\n }\n return { middle, upper, lower };\n}\n\nexport function vwap(candles: any[]): number[] {\n let tpv = 0, vol = 0;\n const out: number[] = [];\n for (const c of candles) {\n const tp = (c.high + c.low + c.close) / 3;\n tpv += tp * c.volume;\n vol += c.volume;\n out.push(vol === 0 ? c.close : tpv / vol);\n }\n return out;\n}\n\nexport function atr(candles: any[], period = 14): number {\n if (candles.length < period + 1) return 0;\n const trs: number[] = [];\n for (let i = 1; i < candles.length; i++) {\n trs.push(Math.max(\n candles[i].high - candles[i].low,\n Math.abs(candles[i].high - candles[i - 1].close),\n Math.abs(candles[i].low - candles[i - 1].close),\n ));\n }\n return trs.slice(-period).reduce((a, b) => a + b, 0) / period;\n}\n\nexport function stochastic(candles: any[], kP = 14, dP = 3) {\n const k: number[] = [];\n for (let i = kP - 1; i < candles.length; i++) {\n const slice = candles.slice(i - kP + 1, i + 1);\n const lo = Math.min(...slice.map((c: any) => c.low));\n const hi = Math.max(...slice.map((c: any) => c.high));\n const cur = candles[i].close;\n k.push(hi === lo ? 50 : ((cur - lo) / (hi - lo)) * 100);\n }\n const d: number[] = [];\n for (let i = dP - 1; i < k.length; i++) {\n d.push(k.slice(i - dP + 1, i + 1).reduce((a, b) => a + b, 0) / dP);\n }\n return { k, d };\n}\n\nexport function adx(candles: any[], period = 14) {\n if (candles.length < period + 2) return { adx: 0, plusDI: 0, minusDI: 0 };\n const trs: number[] = [], pDM: number[] = [], mDM: number[] = [];\n for (let i = 1; i < candles.length; i++) {\n const h = candles[i].high, l = candles[i].low, pc = candles[i - 1].close;\n const ph = candles[i - 1].high, pl = candles[i - 1].low;\n trs.push(Math.max(h - l, Math.abs(h - pc), Math.abs(l - pc)));\n pDM.push(h - ph > pl - l ? Math.max(h - ph, 0) : 0);\n mDM.push(pl - l > h - ph ? Math.max(pl - l, 0) : 0);\n }\n const aTR = trs.slice(-period).reduce((a, b) => a + b, 0) / period;\n const pDI = aTR > 0 ? (pDM.slice(-period).reduce((a, b) => a + b, 0) / period) / aTR * 100 : 0;\n const mDI = aTR > 0 ? (mDM.slice(-period).reduce((a, b) => a + b, 0) / period) / aTR * 100 : 0;\n const dx = (pDI + mDI) > 0 ? Math.abs(pDI - mDI) / (pDI + mDI) * 100 : 0;\n return { adx: isNaN(dx) ? 0 : dx, plusDI: pDI, minusDI: mDI };\n}\n\nexport function ichimoku(candles: any[]) {\n const tenkan: number[] = [], kijun: number[] = [], sA: number[] = [], sB: number[] = [];\n for (let i = 51; i < candles.length; i++) {\n const h9 = Math.max(...candles.slice(i - 8, i + 1).map((c: any) => c.high));\n const l9 = Math.min(...candles.slice(i - 8, i + 1).map((c: any) => c.low));\n const h26 = Math.max(...candles.slice(i - 25, i + 1).map((c: any) => c.high));\n const l26 = Math.min(...candles.slice(i - 25, i + 1).map((c: any) => c.low));\n const h52 = Math.max(...candles.slice(i - 51, i + 1).map((c: any) => c.high));\n const l52 = Math.min(...candles.slice(i - 51, i + 1).map((c: any) => c.low));\n const t = (h9 + l9) / 2, k = (h26 + l26) / 2;\n tenkan.push(t); kijun.push(k);\n sA.push((t + k) / 2); sB.push((h52 + l52) / 2);\n }\n return { tenkan, kijun, senkouA: sA, senkouB: sB };\n}\n",[],[130,174,192],"b5b4c7cf-d6bf-4cd7-88f1-a80e4e26fcdb","ict-alignment.ts","4fcf25e8-82fd-11f1-a032-1607ee4eb77e",9,["D",1784415990161],"// ── ICT Concepts ──\nexport function detectICT(timeframes: any) {\n const m15 = timeframes.m15 || [];\n return {\n orderBlocks: detectOrderBlocks(m15),\n fvgs: detectFVGs(m15),\n bos: detectBOS(m15),\n choch: detectCHoCH(m15),\n };\n}\n\nfunction detectOrderBlocks(candles: any[]) {\n const obs: any[] = [];\n for (let i = 2; i < candles.length; i++) {\n const c = candles[i], prev = candles[i - 1], prev2 = candles[i - 2];\n if (prev2.close < prev2.open && c.close > c.open && c.close > prev2.high)\n obs.push({ type: \"BULLISH\", price: prev2.close, time: prev2.timestamp });\n if (prev2.close > prev2.open && c.close < c.open && c.close < prev2.low)\n obs.push({ type: \"BEARISH\", price: prev2.close, time: prev2.timestamp });\n }\n return obs.slice(-3);\n}\n\nfunction detectFVGs(candles: any[]) {\n const fvgs: any[] = [];\n for (let i = 2; i < candles.length; i++) {\n const l = candles[i - 2], m = candles[i - 1], r = candles[i];\n if (l.low > r.high && m.low > r.high)\n fvgs.push({ type: \"BULLISH\", top: l.low, bottom: r.high, time: m.timestamp });\n if (l.high < r.low && m.high < r.low)\n fvgs.push({ type: \"BEARISH\", top: r.low, bottom: l.high, time: m.timestamp });\n }\n return fvgs.slice(-3);\n}\n\nfunction detectBOS(candles: any[]) {\n if (candles.length < 5) return [];\n const recent = candles.slice(-10);\n const prevHigh = Math.max(...recent.slice(0, -1).map((c: any) => c.high));\n const prevLow = Math.min(...recent.slice(0, -1).map((c: any) => c.low));\n const last = recent[recent.length - 1];\n const bos: any[] = [];\n if (last.close > prevHigh) bos.push({ type: \"BULLISH_BOS\", level: prevHigh });\n if (last.close < prevLow) bos.push({ type: \"BEARISH_BOS\", level: prevLow });\n return bos;\n}\n\nfunction detectCHoCH(candles: any[]) {\n if (candles.length < 20) return [];\n const mid = Math.floor(candles.length / 2);\n const fh = candles.slice(0, mid), sh = candles.slice(mid);\n const fhTrend = fh[fh.length - 1].close - fh[0].close;\n const shBreak = sh[sh.length - 1].close - sh[0].close;\n if (fhTrend > 0 && shBreak < -Math.abs(fhTrend) * 0.5)\n return [{ type: \"BEARISH_CHoCH\", description: \"Uptrend broken\" }];\n if (fhTrend < 0 && shBreak > Math.abs(fhTrend) * 0.5)\n return [{ type: \"BULLISH_CHoCH\", description: \"Downtrend broken\" }];\n return [];\n}\n\n// ── Multi-Timeframe Alignment ──\nexport function checkTimeframeAlignment(timeframes: any) {\n const { daily, h4, h1, m15 } = timeframes;\n if (!daily || !h4 || !h1 || !m15)\n return { aligned: false, setup: \"NEUTRAL\", reason: \"Missing timeframe data\", trends: {} };\n\n const getTrend = (candles: any[]) => {\n if (!candles || candles.length < 50) return \"NEUTRAL\";\n const e20 = candles.slice(-20).reduce((a: number, c: any) => a + c.close, 0) / 20;\n const e50 = candles.slice(-50).reduce((a: number, c: any) => a + c.close, 0) / 50;\n const last = candles[candles.length - 1].close;\n if (last > e20 && e20 > e50) return \"BULLISH\";\n if (last < e20 && e20 < e50) return \"BEARISH\";\n return \"NEUTRAL\";\n };\n\n const dT = getTrend(daily), h4T = getTrend(h4), h1T = getTrend(h1), m15T = getTrend(m15);\n const bull = [dT, h4T, h1T, m15T].filter((t) => t === \"BULLISH\").length;\n const bear = [dT, h4T, h1T, m15T].filter((t) => t === \"BEARISH\").length;\n\n if (bull >= 3) return { aligned: true, setup: \"BUY\", trends: { daily: dT, h4: h4T, h1: h1T, m15: m15T } };\n if (bear >= 3) return { aligned: true, setup: \"SELL\", trends: { daily: dT, h4: h4T, h1: h1T, m15: m15T } };\n return { aligned: false, setup: \"NEUTRAL\", reason: \"Timeframes mixed\", trends: { daily: dT, h4: h4T, h1: h1T, m15: m15T } };\n}\n",[],[130,174,199],"e2cd797b-c047-4ea3-8a6d-f1aaba0daaa8","filters.ts","4fc1ebe4-82fd-11f1-8d46-1607ee4eb77e",15,["D",1784416267132],"import { adx, atr } from \"./indicators.ts\";\n\n// ── Regime Detector ──\nexport function detectRegime(timeframes: any) {\n const h1 = timeframes.h1;\n if (!h1 || h1.length < 28) return { regime: \"UNKNOWN\" as const, trend: \"NEUTRAL\" as const };\n const { adx: a } = adx(h1, 14);\n const aVal = atr(h1, 14);\n const avgRange = h1.slice(-20).reduce((acc: number, c: any) => acc + (c.high - c.low), 0) / 20;\n const volatility = avgRange > 0 ? aVal / avgRange : 0;\n if (a > 30 && volatility < 1.5) return { regime: \"TRENDING\", trend: \"STRONG\" };\n if (a < 20 && volatility < 1.2) return { regime: \"RANGING\", trend: \"NEUTRAL\" };\n if (volatility > 2.0) return { regime: \"VOLATILE\", trend: \"CHAOTIC\" };\n return { regime: \"MIXED\", trend: \"UNCERTAIN\" };\n}\n\n// ── Quality Filter ──\nexport function qualityFilter(results: any[], regime: any) {\n const active = results.filter((r) => r.signal !== \"NEUTRAL\");\n if (active.length < 3) return { pass: false, reason: \"Insufficient confluence (<3 strategies)\" };\n const buy = active.filter((r) => r.signal === \"BUY\").length;\n const sell = active.filter((r) => r.signal === \"SELL\").length;\n const agreement = Math.max(buy, sell) / active.length;\n if (agreement < 0.6) return { pass: false, reason: \"Low directional agreement\" };\n if (regime.regime === \"VOLATILE\" && agreement < 0.75)\n return { pass: false, reason: \"Volatile regime requires higher agreement\" };\n const avgConf = active.reduce((a: number, r: any) => a + r.confidence, 0) / active.length;\n if (avgConf < 55) return { pass: false, reason: \"Average confidence too low\" };\n return { pass: true, agreement, avgConfidence: avgConf };\n}\n\n// ── Confluence Scorer ──\nexport function confluenceScore(results: any[]) {\n const active = results.filter((r) => r.signal !== \"NEUTRAL\");\n if (active.length === 0) return { confidence: 0, score: 0 };\n const buyScore = active.filter((r) => r.signal === \"BUY\").reduce((a: number, r: any) => a + r.score, 0);\n const sellScore = active.filter((r) => r.signal === \"SELL\").reduce((a: number, r: any) => a + r.score, 0);\n const net = Math.abs(buyScore - sellScore);\n const max = active.reduce((a: number, r: any) => a + r.score, 0);\n return { confidence: Math.round(max > 0 ? (net / max) * 100 : 0), score: net };\n}\n\n// ── Signal Strength ──\nexport function signalStrength(results: any[], regime: any) {\n const active = results.filter((r) => r.signal !== \"NEUTRAL\");\n const avg = active.length > 0 ? active.reduce((a: number, r: any) => a + r.score, 0) / active.length : 0;\n let strength = \"WEAK\";\n if (avg > 70) strength = \"STRONG\";\n else if (avg > 55) strength = \"MODERATE\";\n if (regime.regime === \"TRENDING\" && strength === \"MODERATE\") strength = \"STRONG\";\n return { strength: strength as \"STRONG\" | \"MODERATE\" | \"WEAK\", avgScore: avg };\n}\n",[],[130,174,207],"828a7d23-1d40-4e41-bddd-dcfb6ab9405f","engine.ts","a68ffe2a-82fd-11f1-936c-1607ee4eb77e",16,["D",1784416267146],"import { sqlite } from \"./db.ts\";\nimport { atr } from \"./indicators.ts\";\nimport { sendTelegram } from \"./telegram.ts\";\n\n// ── Risk Manager ──\nexport async function calculateRisk(entry: number, atrVal: number, direction: \"BUY\" | \"SELL\") {\n const result = await sqlite.execute(\"SELECT balance FROM paper_portfolio WHERE id = 1 LIMIT 1\");\n const balance = (result.rows[0]?.balance as number) || 100000;\n const riskAmount = balance * 0.01; // 1% risk\n const stopDist = atrVal * 1.5;\n const size = stopDist > 0 ? riskAmount / stopDist : 0;\n const stop = direction === \"BUY\" ? entry - stopDist : entry + stopDist;\n const target = direction === \"BUY\" ? entry + atrVal * 2.5 : entry - atrVal * 2.5;\n return {\n stop: Math.round(stop * 100) / 100,\n target: Math.round(target * 100) / 100,\n size: Math.floor(size * 100) / 100,\n riskPercent: 1,\n };\n}\n\n// ── Paper Trading ──\nexport async function getPortfolio() {\n const r = await sqlite.execute(\"SELECT balance, equity, open_pnl, total_trades FROM paper_portfolio WHERE id = 1\");\n const row = r.rows[0];\n return row || { balance: 100000, equity: 100000, open_pnl: 0, total_trades: 0 };\n}\n\nexport async function executePaperTrade(trade: any) {\n const portfolio = await getPortfolio();\n const slippage = 0.001 + Math.random() * 0.004;\n const execPrice = trade.direction === \"BUY\"\n ? trade.entry * (1 + slippage)\n : trade.entry * (1 - slippage);\n\n const id = crypto.randomUUID();\n await sqlite.execute({\n sql: `INSERT INTO paper_positions (id, strategy_id, direction, entry_price, quantity, stop_loss, take_profit, open_time)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [id, trade.strategyId || \"manual\", trade.direction, execPrice, trade.size, trade.stop, trade.target, Date.now()],\n });\n await sqlite.execute({\n sql: \"UPDATE paper_portfolio SET total_trades = total_trades + 1, updated_at = ? WHERE id = 1\",\n args: [Date.now()],\n });\n return { id, executedPrice: Math.round(execPrice * 100) / 100, slippage: Math.round(slippage * 10000) / 100 + \"%\" };\n}\n\nexport async function closePaperPosition(id: string, exitPrice: number) {\n const r = await sqlite.execute({ sql: \"SELECT * FROM paper_positions WHERE id = ?\", args: [id] });\n const pos = r.rows[0];\n if (!pos) return null;\n const pnl = pos.direction === \"BUY\"\n ? (exitPrice - pos.entry_price) * pos.quantity\n : (pos.entry_price - exitPrice) * pos.quantity;\n\n await sqlite.batch([\n { sql: \"DELETE FROM paper_positions WHERE id = ?\", args: [id] },\n { sql: \"UPDATE paper_portfolio SET balance = balance + ?, updated_at = ? WHERE id = 1\", args: [pnl, Date.now()] },\n ]);\n return { pnl: Math.round(pnl * 100) / 100 };\n}\n\nexport async function getOpenPositions() {\n const r = await sqlite.execute(\"SELECT * FROM paper_positions ORDER BY open_time DESC\");\n return r.rows;\n}\n\n// ── Journal ──\nexport async function saveTrade(trade: any) {\n const id = crypto.randomUUID();\n await sqlite.execute({\n sql: `INSERT INTO trades (id, timestamp, strategy_id, strategy_name, direction, entry_price, quantity, confidence, notes)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [id, Date.now(), trade.strategyId || \"manual\", trade.strategyName || \"Manual\",\n trade.direction, trade.entry, trade.size, trade.confidence || 50, trade.notes || \"\"],\n });\n await sendTelegram(`📝 Trade: ${trade.direction} @ ${trade.entry} | Size: ${trade.size}`);\n return id;\n}\n\nexport async function getTrades(limit = 50) {\n const r = await sqlite.execute({ sql: \"SELECT * FROM trades ORDER BY timestamp DESC LIMIT ?\", args: [limit] });\n return r.rows;\n}\n\n// ── Learning Engine ──\nexport async function adjustWeights(strategies: any[]): Promise> {\n const weights: Record = {};\n for (const s of strategies) {\n const r = await sqlite.execute({ sql: \"SELECT wins, losses FROM strategy_performance WHERE strategy_id = ?\", args: [s.id] });\n const perf = r.rows[0];\n if (!perf || ((perf.wins as number) + (perf.losses as number)) < 10) {\n weights[s.id] = 1.0;\n continue;\n }\n const winRate = (perf.wins as number) / ((perf.wins as number) + (perf.losses as number));\n weights[s.id] = 0.5 + winRate;\n }\n return weights;\n}\n\nexport async function recordStrategyResult(strategyId: string, pnl: number) {\n const win = pnl > 0 ? 1 : 0;\n const loss = pnl <= 0 ? 1 : 0;\n await sqlite.execute({\n sql: `INSERT INTO strategy_performance (strategy_id, wins, losses, pnl, updated_at)\n VALUES (?, ?, ?, ?, ?)\n ON CONFLICT(strategy_id) DO UPDATE SET wins = wins + ?, losses = losses + ?, pnl = pnl + ?, updated_at = ?`,\n args: [strategyId, win, loss, pnl, Date.now(), win, loss, pnl, Date.now()],\n });\n}\n\nexport async function getBestStrategies() {\n const r = await sqlite.execute(\"SELECT strategy_id, wins, losses, pnl FROM strategy_performance ORDER BY pnl DESC LIMIT 10\");\n return r.rows.map((row: any) => {\n const total = (row.wins || 0) + (row.losses || 0);\n return { ...row, winRate: total > 0 ? ((row.wins / total) * 100).toFixed(1) : 0 };\n });\n}\n\n// ── Performance Monitor ──\nexport async function getPerformanceMetrics() {\n const r = await sqlite.execute(\"SELECT pnl FROM trades WHERE exit_price IS NOT NULL AND pnl IS NOT NULL\");\n const trades = r.rows.map((row: any) => row.pnl || 0);\n const wins = trades.filter((p) => p > 0);\n const losses = trades.filter((p) => p <= 0);\n const totalPnl = trades.reduce((a, b) => a + b, 0);\n const grossProfit = wins.reduce((a, b) => a + b, 0);\n const grossLoss = Math.abs(losses.reduce((a, b) => a + b, 0));\n\n let peak = 0, maxDD = 0, running = 0;\n for (const p of trades) {\n running += p;\n if (running > peak) peak = running;\n const dd = peak - running;\n if (dd > maxDD) maxDD = dd;\n }\n\n return {\n totalTrades: trades.length,\n wins: wins.length,\n losses: losses.length,\n winRate: trades.length > 0 ? Math.round((wins.length / trades.length) * 1000) / 10 : 0,\n profitFactor: grossLoss > 0 ? Math.round((grossProfit / grossLoss) * 100) / 100 : 0,\n totalPnl: Math.round(totalPnl * 100) / 100,\n maxDrawdown: Math.round(maxDD * 100) / 100,\n };\n}\n\n// ── Marketplace ──\nexport async function getMarketplaceStrategies() {\n const existing = await sqlite.execute(\"SELECT 1 FROM marketplace_strategies LIMIT 1\");\n if (existing.rows.length === 0) {\n await sqlite.batch([\n { sql: \"INSERT INTO marketplace_strategies (id, name, description, price, seller) VALUES ('gold-trend-master', 'Gold Trend Master', 'EMA + ADX combo optimized for XAU/USD', 49.99, 'KingOfGold')\" },\n { sql: \"INSERT INTO marketplace_strategies (id, name, description, price, seller) VALUES ('ict-pro-pack', 'ICT Pro Pack', 'Order Block + FVG + BOS detection system', 99.99, 'SmartMoney')\" },\n { sql: \"INSERT INTO marketplace_strategies (id, name, description, price, seller) VALUES ('scalp-sniper', 'Scalp Sniper', 'Fast RSI + Stochastic for 1m scalping', 29.99, 'ScalperPro')\" },\n ]);\n }\n const r = await sqlite.execute(\"SELECT id, name, description, price, seller, purchases FROM marketplace_strategies\");\n return r.rows;\n}\n\nexport async function purchaseStrategy(userId: string, strategyId: string) {\n try {\n await sqlite.batch([\n { sql: \"INSERT INTO marketplace_purchases (user_id, strategy_id, purchased_at) VALUES (?, ?, ?)\", args: [userId, strategyId, Date.now()] },\n { sql: \"UPDATE marketplace_strategies SET purchases = purchases + 1 WHERE id = ?\", args: [strategyId] },\n ]);\n return true;\n } catch {\n return false;\n }\n}\n",[],[130,174,215],"b5cd9ee1-3d6d-4ad6-b5e7-c1c49a201b7a","db.ts","fc19b666-82fc-11f1-b702-1607ee4eb77e",3,["D",1784415849799],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nexport async function initDB() {\n await sqlite.batch([\n { sql: `CREATE TABLE IF NOT EXISTS api_keys (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n api_key TEXT UNIQUE NOT NULL,\n daily_limit INTEGER DEFAULT 800,\n used_today INTEGER DEFAULT 0,\n last_used INTEGER DEFAULT 0,\n is_active INTEGER DEFAULT 1,\n priority INTEGER DEFAULT 0\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS trades (\n id TEXT PRIMARY KEY,\n timestamp INTEGER,\n strategy_id TEXT,\n strategy_name TEXT,\n direction TEXT,\n entry_price REAL,\n exit_price REAL,\n quantity REAL,\n pnl REAL,\n pnl_percent REAL,\n confidence REAL,\n notes TEXT\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS strategy_performance (\n strategy_id TEXT PRIMARY KEY,\n wins INTEGER DEFAULT 0,\n losses INTEGER DEFAULT 0,\n pnl REAL DEFAULT 0,\n updated_at INTEGER\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS scanner_results (\n timestamp INTEGER PRIMARY KEY,\n scan_data TEXT\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS paper_portfolio (\n id INTEGER PRIMARY KEY CHECK (id = 1),\n balance REAL DEFAULT 100000,\n equity REAL DEFAULT 100000,\n open_pnl REAL DEFAULT 0,\n total_trades INTEGER DEFAULT 0,\n updated_at INTEGER\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS paper_positions (\n id TEXT PRIMARY KEY,\n strategy_id TEXT,\n direction TEXT,\n entry_price REAL,\n quantity REAL,\n stop_loss REAL,\n take_profit REAL,\n open_time INTEGER,\n pnl REAL DEFAULT 0\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS marketplace_strategies (\n id TEXT PRIMARY KEY,\n name TEXT,\n description TEXT,\n price REAL,\n seller TEXT,\n purchases INTEGER DEFAULT 0\n )` },\n { sql: `CREATE TABLE IF NOT EXISTS marketplace_purchases (\n user_id TEXT,\n strategy_id TEXT,\n purchased_at INTEGER,\n PRIMARY KEY (user_id, strategy_id)\n )` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_trades_ts ON trades(timestamp)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_trades_strat ON trades(strategy_id)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_perf_strat ON strategy_performance(strategy_id)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_positions_open ON paper_positions(open_time)` },\n ]);\n\n const existing = await sqlite.execute(\"SELECT 1 FROM paper_portfolio LIMIT 1\");\n if (existing.rows.length === 0) {\n await sqlite.execute({\n sql: \"INSERT INTO paper_portfolio (id, balance, equity, updated_at) VALUES (1, 100000, 100000, ?)\",\n args: [Date.now()],\n });\n }\n}\n\nexport { sqlite };\n",[],[130,174,223],"033486cf-ba5c-45e3-816b-e7d91dd875ae","api-key-manager.ts","06133890-82fd-11f1-9b13-1607ee4eb77e",["D",1784415866533],"import { sqlite } from \"./db.ts\";\n\nexport async function initKeysFromEnv() {\n const keys = Deno.env.get(\"TWELVE_DATA_API_KEYS\");\n if (!keys) return;\n for (const key of keys.split(\",\").map((k) => k.trim()).filter(Boolean)) {\n await sqlite.execute({\n sql: \"INSERT OR IGNORE INTO api_keys (api_key, daily_limit) VALUES (?, 800)\",\n args: [key],\n });\n }\n}\n\nexport async function getNextKey(): Promise {\n const now = Date.now();\n const dayStart = new Date().setHours(0, 0, 0, 0).getTime();\n\n // Reset daily counters\n await sqlite.execute({\n sql: \"UPDATE api_keys SET used_today = 0 WHERE last_used < ?\",\n args: [dayStart],\n });\n\n const result = await sqlite.execute(\n `SELECT api_key FROM api_keys WHERE is_active = 1 AND used_today < daily_limit ORDER BY used_today ASC, priority ASC LIMIT 1`,\n );\n if (result.rows.length === 0) return null;\n\n const key = result.rows[0].api_key as string;\n await sqlite.execute({\n sql: \"UPDATE api_keys SET used_today = used_today + 1, last_used = ? WHERE api_key = ?\",\n args: [now, key],\n });\n return key;\n}\n\nexport async function exhaustKey(key: string) {\n await sqlite.execute({\n sql: \"UPDATE api_keys SET used_today = daily_limit, last_used = ? WHERE api_key = ?\",\n args: [Date.now(), key],\n });\n}\n\nexport async function addApiKey(key: string, limit = 800) {\n await sqlite.execute({\n sql: \"INSERT OR IGNORE INTO api_keys (api_key, daily_limit) VALUES (?, ?)\",\n args: [key, limit],\n });\n}\n\nexport async function removeApiKey(key: string) {\n await sqlite.execute({ sql: \"DELETE FROM api_keys WHERE api_key = ?\", args: [key] });\n}\n\nexport async function getApiKeysStatus() {\n const result = await sqlite.execute(\n \"SELECT api_key, used_today, daily_limit, is_active FROM api_keys\",\n );\n return result.rows;\n}\n",[],[130,174,231],"6a05fdf6-4588-41cf-838b-4e9858bd95ad","analysis.ts","a6965022-82fd-11f1-8f28-1607ee4eb77e",14,["D",1784416263126],"import { fetchGoldData, generateSimCandles } from \"./market.ts\";\nimport { evaluateStrategies, STRATEGIES } from \"./strategies.ts\";\nimport { detectRegime, qualityFilter, confluenceScore, signalStrength } from \"./filters.ts\";\nimport { detectICT, checkTimeframeAlignment } from \"./ict-alignment.ts\";\nimport { calculateRisk, adjustWeights, saveTrade, executePaperTrade, recordStrategyResult } from \"./engine.ts\";\nimport { sendTelegram } from \"./telegram.ts\";\nimport { atr } from \"./indicators.ts\";\n\nfunction hasApiKey(): boolean {\n const keys = Deno.env.get(\"TWELVE_DATA_API_KEYS\");\n return !!(keys && keys.trim());\n}\n\nasync function fetchAllTimeframes() {\n if (!hasApiKey()) {\n // Simulated fallback — generate correlated candles across timeframes\n const base = 2350 + (Math.random() - 0.5) * 50;\n return {\n daily: generateSimCandles(100, base),\n h4: generateSimCandles(100, base + Math.random() * 10),\n h1: generateSimCandles(100, base + Math.random() * 5),\n m15: generateSimCandles(100, base + Math.random() * 3),\n simulated: true,\n };\n }\n const [daily, h4, h1, m15] = await Promise.all([\n fetchGoldData(\"1day\", 100),\n fetchGoldData(\"4h\", 100),\n fetchGoldData(\"1h\", 100),\n fetchGoldData(\"15min\", 100),\n ]);\n return { daily, h4, h1, m15, simulated: false };\n}\n\nexport async function runFullAnalysis() {\n const timeframes: any = await fetchAllTimeframes();\n\n // 1. Multi-timeframe alignment\n const alignment = checkTimeframeAlignment(timeframes);\n if (!alignment.aligned) {\n return {\n decision: \"REJECT\", reason: alignment.reason || \"Timeframes not aligned\",\n alignment, ict: null, trade: null, results: [], regime: null,\n coach: { summary: `Trade rejected: ${alignment.reason}. Timeframes not in agreement.`, confidence: 0, recommendation: \"WAIT\" },\n simulated: timeframes.simulated,\n };\n }\n\n // 2. Run strategies with AI-adjusted weights\n const weights = await adjustWeights(STRATEGIES);\n const results = evaluateStrategies(timeframes, weights);\n\n // 3. ICT concepts\n const ict = detectICT(timeframes);\n\n // 4. Filters\n const regime = detectRegime(timeframes);\n const quality = qualityFilter(results, regime);\n const confluence = confluenceScore(results);\n const strength = signalStrength(results, regime);\n\n // 5. Decision\n const decision = (quality.pass && confluence.confidence > 40 && strength.strength !== \"WEAK\" && regime.regime !== \"VOLATILE\")\n ? \"TAKE\" : \"REJECT\";\n\n // 6. AI Coach summary\n const topStrategy = results.sort((a, b) => b.score - a.score)[0];\n let coachSummary: string;\n if (decision === \"TAKE\") {\n coachSummary = `Signal: ${alignment.setup} with ${confluence.confidence}% confidence. Regime: ${regime.regime}. Top strategy: ${topStrategy?.name || \"None\"}. ICT: ${ict.bos.length} BOS, ${ict.orderBlocks.length} OBs detected.`;\n } else {\n coachSummary = `Trade rejected: ${quality.reason || \"Filters not passed\"}. Confluence: ${confluence.confidence}%. Strength: ${strength.strength}. Regime: ${regime.regime}.`;\n }\n\n // 7. Generate trade if TAKE\n let trade = null;\n if (decision === \"TAKE\") {\n const m15 = timeframes.m15;\n const entry = m15[m15.length - 1].close;\n const atrVal = atr(m15, 14);\n if (atrVal > 0) {\n const direction = alignment.setup as \"BUY\" | \"SELL\";\n const risk = await calculateRisk(entry, atrVal, direction);\n trade = { entry: Math.round(entry * 100) / 100, ...risk, direction, atr: Math.round(atrVal * 100) / 100 };\n }\n }\n\n return {\n decision, coach: { summary: coachSummary, confidence: confluence.confidence, recommendation: decision === \"TAKE\" ? \"EXECUTE\" : \"WAIT\" },\n alignment, ict, trade, results, regime, strength, confluence, simulated: timeframes.simulated,\n };\n}\n\nexport async function runPipeline() {\n try {\n const result = await runFullAnalysis();\n\n if (result.decision === \"TAKE\" && result.trade) {\n const executed = await executePaperTrade({\n strategyId: \"pipeline\",\n direction: result.trade.direction,\n entry: result.trade.entry,\n size: result.trade.size,\n stop: result.trade.stop,\n target: result.trade.target,\n confidence: result.coach.confidence,\n });\n\n await saveTrade({\n ...result.trade,\n strategyId: \"pipeline\",\n strategyName: \"Pipeline Auto\",\n notes: `ICT: ${result.ict?.bos?.length || 0} BOS. Regime: ${result.regime?.regime}`,\n });\n\n await sendTelegram(\n `📈 SIGNAL: ${result.trade.direction} XAU/USD\\n` +\n `Entry: ${result.trade.entry}\\nStop: ${result.trade.stop}\\nTarget: ${result.trade.target}\\n` +\n `Size: ${result.trade.size}\\nConfidence: ${result.coach.confidence}%`,\n );\n\n return { status: \"EXECUTED\", trade: result.trade, executed, coach: result.coach };\n }\n\n return { status: \"REJECTED\", reason: result.reason || result.coach.summary, coach: result.coach };\n } catch (e) {\n console.error(\"Pipeline error:\", e);\n await sendTelegram(`⚠️ Pipeline Error: ${(e as Error).message}`);\n throw e;\n }\n}\n\n// ── Scanner ──\nexport async function runScanner() {\n const timeframes: any = await fetchAllTimeframes();\n const m15 = timeframes.m15;\n const engine = evaluateStrategies(timeframes);\n const alignment = checkTimeframeAlignment(timeframes);\n\n const opportunities: any[] = [];\n const recentHigh = Math.max(...m15.slice(-20).map((c: any) => c.high));\n const recentLow = Math.min(...m15.slice(-20).map((c: any) => c.low));\n const lastClose = m15[m15.length - 1].close;\n\n if (lastClose > recentHigh * 0.998)\n opportunities.push({ type: \"BREAKOUT\", direction: \"BUY\", confidence: 60, level: recentHigh });\n if (lastClose < recentLow * 1.002)\n opportunities.push({ type: \"BREAKDOWN\", direction: \"SELL\", confidence: 60, level: recentLow });\n\n const buy = engine.filter((r) => r.signal === \"BUY\");\n const sell = engine.filter((r) => r.signal === \"SELL\");\n if (buy.length >= 3 && alignment.setup === \"BUY\")\n opportunities.push({ type: \"REVERSAL\", direction: \"BUY\", confidence: 65, strategies: buy.length });\n if (sell.length >= 3 && alignment.setup === \"SELL\")\n opportunities.push({ type: \"REVERSAL\", direction: \"SELL\", confidence: 65, strategies: sell.length });\n\n return { opportunities, strategySignals: engine, alignment, simulated: timeframes.simulated };\n}\n\n// ── Dashboard Data ──\nexport async function getLiveData() {\n const timeframes: any = await fetchAllTimeframes();\n const m15 = timeframes.m15;\n const price = m15[m15.length - 1].close;\n const change = m15.length > 1 ? ((price - m15[m15.length - 2].close) / m15[m15.length - 2].close) * 100 : 0;\n const { getPortfolio, getPerformanceMetrics } = await import(\"./engine.ts\");\n const [portfolio, metrics] = await Promise.all([getPortfolio(), getPerformanceMetrics()]);\n\n return {\n price: Math.round(price * 100) / 100,\n change: Math.round(change * 100) / 100,\n high24h: Math.max(...m15.map((c: any) => c.high)),\n low24h: Math.min(...m15.map((c: any) => c.low)),\n portfolio,\n metrics,\n timestamp: Date.now(),\n simulated: timeframes.simulated,\n };\n}\n",[],[130,174,238],"59a1f1be-0f9d-4ba0-8755-8b946c559a50",["D",1784415787311],[149,150,151,152,153,154,155,156,157,158],[130,174],["D",1784415787311],[148],[130],["D",1784414655544],["D",1789559472742],{"_16":17,"_87":83},{"_16":17,"_80":81,"_82":83,"_33":34,"_84":85,"_86":26},{"_68":69,"_20":70,"_18":71,"_72":19,"_73":-5,"_74":-5,"_75":-5,"_76":-5,"_77":-5,"_78":21,"_79":17},"ctx",{"_61":-5,"_108":290,"_291":292,"_293":294,"_295":26,"_296":26,"_297":26,"_298":38,"_299":-5,"_300":-7,"_301":-7,"_302":42,"_303":26,"_304":26,"_305":-5,"_306":26,"_307":26,"_308":26,"_309":-5},"ENV",{"_261":262,"_263":264,"_265":70,"_266":267,"_268":269,"_270":271,"_272":273,"_274":275,"_276":277,"_278":279,"_280":281,"_282":283,"_284":285,"_286":287,"_288":289},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","fdb67791413f4386b4dbf18f354029a617f6160f","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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