feat(longbridge): 602315 mainland CN geo-block bypass + stock_t通用脚本

- SKILL.md: 加 602315 bypass 章节(三件套 LONGBRIDGE_REGION + proxychains + Clash HK)
- longbridge-python-sdk/SKILL.md: Python SDK 路径同样需要 bypass
- references/longbridge-602315-bypass.md: 完整方案+验证步骤
- references/longbridge-cn-vs-com-endpoint.md: cn vs com 域名区别
- references/clash-node-switching.md: Clash 切香港节点操作
- references/stock-t-trading-workflow.md: 通用持仓脚本用法
- intraday-trading/SKILL.md: 同步 602315 限制说明
- scripts/{daily_t_analysis,t_monitor}.py: 之前漏提交,补上

验证: 2026-07-09 下单 RGTI 15股@15.50 订单ID 1259547163696824320 成功
背景: longport SDK 通过 is_cn() 自动探测 geotest.lbkrs.com 选 cn/com endpoint
     net_mode下 cn 域(阿里云深圳)被拒,com 域(AWS香港)需绕
     唯一可行: LONGBRIDGE_REGION=ap 强制走 com + proxychains + Clash 香港出口

Co-Authored-By: Claude <noreply@anthropic.com>

longbridge-cli/scripts/daily_t_analysis.py

@@ -0,0 +1,180 @@
+#!/usr/bin/env python3
+"""
+每日持仓做T分析 - 交易日早盘前推送
+分析持仓股票的技术面，给出做T建议+性价比（含真实手续费）
+用法: python3 daily_t_analysis.py
+输出: 持仓分析报告（含支撑/阻力/ATR/做T方案/性价比评级）
+"""
+import os, sys, json, math
+from datetime import datetime
+
+# Load LongPort creds from bashrc
+with open(os.path.expanduser('~/.bashrc')) as f:
+    for line in f:
+        line = line.strip()
+        if line.startswith('export LONGPORT_') or line.startswith('export LONGBRIDGE_'):
+            parts = line.replace('export ', '').split('=', 1)
+            if len(parts) == 2:
+                os.environ[parts[0]] = parts[1]
+
+from longport import openapi
+
+def F(val, dec=2):
+    return f'{val:.{dec}f}'
+
+def calc_hk_fee(amount):
+    """港股手续费：佣金0.03%(min3) + 印花税0.1%(整数) + 征费0.00278% + 交收费0.002%(min2,max100)"""
+    commission = max(3, amount * 0.0003)
+    stamp = math.ceil(amount * 0.001)
+    levy = amount * 0.0000278
+    trading_fee = amount * 0.0000565
+    settle = max(2, min(100, amount * 0.00002))
+    return commission + stamp + levy + trading_fee + settle
+
+def calc_us_fee(amount, qty):
+    """美股手续费：佣金$0 + SEC费0.00278%(卖) + FINRA $0.000166/股(卖)"""
+    sec_fee = amount * 0.0000278
+    finra = max(0.01, qty * 0.000166)
+    return sec_fee + finra
+
+def analyze():
+    cfg = openapi.Config.from_env()
+    trade_ctx = openapi.TradeContext(config=cfg)
+    quote_ctx = openapi.QuoteContext(config=cfg)
+
+    positions = []
+    symbols_list = []
+    resp = trade_ctx.stock_positions()
+    for ch in resp.channels:
+        for pos in ch.positions:
+            if int(pos.quantity) > 0:
+                positions.append({
+                    'symbol': pos.symbol,
+                    'qty': int(pos.quantity),
+                    'avail': int(pos.available_quantity),
+                    'cost': float(pos.cost_price),
+                })
+                symbols_list.append(pos.symbol)
+
+    if not positions:
+        return "📊 无持仓，无需做T分析"
+
+    # Get lot sizes
+    lot_sizes = {}
+    try:
+        infos = quote_ctx.static_info(symbols_list)
+        for info in infos:
+            lot_sizes[info.symbol] = info.lot_size
+    except:
+        for s in symbols_list:
+            lot_sizes[s] = 1
+
+    lines = [f"📊 每日做T分析 | {datetime.now().strftime('%Y-%m-%d')}\n"]
+
+    for p in positions:
+        sym = p['symbol']
+        lot_size = lot_sizes.get(sym, 1)
+        try:
+            candles = quote_ctx.candlesticks(sym, openapi.Period.Day, 20, openapi.AdjustType.NoAdjust)
+            closes = [float(c.close) for c in candles]
+            highs = [float(c.high) for c in candles]
+            lows = [float(c.low) for c in candles]
+
+            sma5 = sum(closes[-5:]) / 5
+            sma10 = sum(closes[-10:]) / 10
+            sma20 = sum(closes) / len(closes)
+            current = closes[-1]
+
+            atr_sum = 0
+            for i in range(1, min(15, len(candles))):
+                tr = max(highs[-i]-lows[-i], abs(highs[-i]-closes[-i-1]), abs(lows[-i]-closes[-i-1]))
+                atr_sum += tr
+            atr = atr_sum / min(14, len(candles)-1)
+
+            support = min(lows[-5:])
+            resistance = max(highs[-5:])
+
+            cost = p['cost']
+            qty = p['qty']
+            avail = p['avail']
+            pnl_pct = (current - cost) / cost * 100
+            pnl_emoji = '🟢' if pnl_pct >= 0 else '🔴'
+
+            if current > sma5 > sma10 > sma20:
+                trend = "📈多头"
+            elif current < sma5 < sma10 < sma20:
+                trend = "📉空头"
+            elif current > sma10:
+                trend = "↗️偏多"
+            else:
+                trend = "↘️偏弱"
+
+            atr_pct = atr / current * 100
+            is_worth = atr_pct > 1.5
+
+            is_hk = '.HK' in sym
+            ccy = 'HKD' if is_hk else 'USD'
+            d = 3 if is_hk else 2
+
+            buy_zone = min(support, sma20) + atr * 0.2
+            sell_zone = max(resistance, sma10) - atr * 0.2
+            t_profit_per_share = sell_zone - buy_zone
+
+            raw_t_qty = max(1, int(avail * 0.2))
+            t_qty = max(lot_size, (raw_t_qty // lot_size) * lot_size)
+            if t_qty > avail:
+                t_qty = (avail // lot_size) * lot_size
+
+            capital_used = buy_zone * t_qty
+            expected_profit = t_profit_per_share * t_qty
+            return_rate = (expected_profit / capital_used * 100) if capital_used > 0 else 0
+
+            stop_loss = current - atr * 1.5
+            risk_per_share = buy_zone - stop_loss
+            risk_total = risk_per_share * t_qty
+            rr = (expected_profit / risk_total) if risk_total > 0 else 0
+
+            if is_hk:
+                buy_fee = calc_hk_fee(buy_zone * t_qty)
+                sell_fee = calc_hk_fee(sell_zone * t_qty)
+            else:
+                buy_fee = calc_us_fee(buy_zone * t_qty, t_qty)
+                sell_fee = calc_us_fee(sell_zone * t_qty, t_qty)
+            fee = buy_fee + sell_fee
+            net_profit = expected_profit - fee
+
+            if rr >= 3 and return_rate >= 1.5:
+                rating = "⭐⭐⭐ 高"
+            elif rr >= 2 and return_rate >= 1:
+                rating = "⭐⭐ 中"
+            elif rr >= 1.5 and return_rate >= 0.5:
+                rating = "⭐ 低"
+            else:
+                rating = "❌ 不建议"
+
+            lines.append(f"{'━' * 30}")
+            lines.append(f"📌 {sym} | {qty}股({qty//lot_size}手) | 成本{F(cost, d)}{ccy}")
+            lines.append(f"现价{F(current, d)} | {pnl_emoji}{pnl_pct:+.1f}% | {trend} | ATR{F(atr, d)}({atr_pct:.1f}%)")
+            lines.append(f"支撑{F(support, d)} | 阻力{F(resistance, d)}")
+
+            if is_worth and t_qty >= lot_size:
+                lines.append(f"🎯 低吸{F(buy_zone, d)} → 高抛{F(sell_zone, d)} | {t_qty}股({t_qty//lot_size}手)")
+                lines.append(f"📐 性价比: {rating}")
+                lines.append(f"• 预期利润: {F(net_profit, 1)}{ccy} | 收益率: {return_rate:.1f}%")
+                lines.append(f"• 盈亏比: {rr:.1f}:1 | 手续费: {F(fee, 1)}{ccy}(买{F(buy_fee,1)}+卖{F(sell_fee,1)})")
+                lines.append(f"• 止损: {F(stop_loss, d)} | 最大亏损: {F(risk_total, 1)}{ccy}")
+            elif not is_worth:
+                lines.append(f"💡 波动太小，暂不建议做T | 性价比: {rating}")
+            else:
+                lines.append(f"⚠️ 不足1手({lot_size}股)，无法做T")
+
+        except Exception as e:
+            lines.append(f"❌ {sym}: {e}")
+
+    lines.append(f"\n⏰ 港股9:30-16:00 | 美股21:30-04:00 (北京时间)")
+    return '\n'.join(lines)
+
+
+if __name__ == '__main__':
+    result = analyze()
+    print(result)