fix(telegram): dynamic TP1 calibration and pre-dispatch PEISF validation [LOG-20260922-037]

autonomous_market_scanner.py

@@ -508,6 +508,15 @@ def dispatch_top_pick_proposal(candidate):
     strat = candidate.get('strategy', 'PRECISION_SNIPER')
     matched_cnt = candidate.get('matched_count', len(candidate.get('matched_rules', [])) or 8)
 
+    # 🏛️ Institutional Minimum 1:1.50 RR Calibration on TP1 ($2+2=4 Law)
+    dist = abs(price - sl)
+    if dist > 0:
+        min_tp1 = round(price + (dist * 1.5), 3) if direction == "BUY" else round(price - (dist * 1.5), 3)
+        if direction == "BUY":
+            tp1 = max(tp1, min_tp1)
+        else:
+            tp1 = min(tp1, min_tp1) if tp1 > 0 else min_tp1
+
     # Set as pending proposal in telegram copilot
     # 🏛️ Smart Deduplication & Rejection Cooldown (Pillar 5 of Master Plan)
     # 1. Anti-Spam Rejection Cooldown: If Sharif Bhai rejected this exact setup within 180s, don't spam him
@@ -550,6 +559,17 @@ def dispatch_top_pick_proposal(candidate):
             "timestamp": time.time(),
             "status": "AWAITING_APPROVAL"
         }
+
+        # 🏛️ Pre-Flight PEISF Invalidation Check BEFORE Telegram Dispatch ($2+2=4 Law)
+        try:
+            from core_shared.database_guard import validate_proposal_pre_execution
+            is_safe, peisf_err = validate_proposal_pre_execution(sig_dict, current_live_price=price)
+            if not is_safe:
+                print(f"[AutonomousScanner] ⚠️ Proposal for {asset} held from Telegram dispatch: {peisf_err}", flush=True)
+                return False
+        except Exception as _peisf_e:
+            print(f"[AutonomousScanner] Pre-dispatch PEISF check notice: {_peisf_e}", flush=True)
+
         telegram_copilot_service.set_pending_signal(sig_dict)
         try:
             trading_mode_manager.set_pending_signal_for_asset(asset, sig_dict)
@@ -1015,6 +1035,13 @@ def _scanner_worker():
                                 dir_ = trigger_res["direction"]
                                 dist = abs(entry_p - sl_p)
 
+                                # 🏛️ Institutional Invariant: Guarantee TP1 >= 1.5R at exact 1M entry price ($2+2=4 Law)
+                                min_tp1 = round(entry_p + (dist * 1.5), 3) if dir_ == "BUY" else round(entry_p - (dist * 1.5), 3)
+                                if dir_ == "BUY":
+                                    final_tp1 = max(tp_p, min_tp1)
+                                else:
+                                    final_tp1 = min(tp_p, min_tp1) if tp_p > 0 else min_tp1
+
                                 # 🏛️ Sharif Bhai's 2-Tier Pyramiding Guard ($2+2=4)
                                 tier_st = get_asset_trade_tier_status(a)
                                 if not tier_st["can_open"]:
@@ -1029,7 +1056,7 @@ def _scanner_worker():
                                     "direction": dir_,
                                     "entry_price": entry_p,
                                     "sl": sl_p,
-                                    "tp1": tp_p,
+                                    "tp1": final_tp1,
                                     "tp2": round(entry_p + (dist * (1.5 if tier_num == 2 else 2.8)), 3) if dir_ == "BUY" else round(entry_p - (dist * (1.5 if tier_num == 2 else 2.8)), 3),
                                     "tp3": round(entry_p + (dist * (1.5 if tier_num == 2 else 4.5)), 3) if dir_ == "BUY" else round(entry_p - (dist * (1.5 if tier_num == 2 else 4.5)), 3),
                                     "lot": lot_size,

core_shared/database_guard.py

@@ -233,8 +233,11 @@ def validate_proposal_pre_execution(
         else:
             risk = sl - entry
             reward = entry - tp1
-        if risk > 0 and (reward / risk) < 1.5:
-            rr_actual = round(reward / risk, 2)
-            return False, f"🛑 RR রেশিও অপর্যাপ্ত ({rr_actual:.2f}:1 < 1.5:1 নূন্যতম)! ঝুঁকি-পুরস্কার অনুপাত সংবিধান লঙ্ঘন।"
+        if risk > 0:
+            rr_ratio = reward / risk
+            # Floating-point representation tolerance: round(rr_ratio, 2) >= 1.50
+            if round(rr_ratio, 2) < 1.5 and rr_ratio < 1.49:
+                rr_actual = round(rr_ratio, 2)
+                return False, f"🛑 RR রেশিও অপর্যাপ্ত ({rr_actual:.2f}:1 < 1.5:1 নূন্যতম)! ঝুঁকি-পুরস্কার অনুপাত সংবিধান লঙ্ঘন।"
 
     return True, "VALIDATED_SAFE"

core_shared/tri_timeframe_sniper_engine.py

@@ -332,8 +332,18 @@ class TriTimeframeSniperEngine:
 
             tight_sl = thesis["invalidation_level"]
             risk_distance = abs(execution_price - tight_sl)
-            reward_distance = abs(thesis["target_profit"] - execution_price)
-            rr_ratio = round(reward_distance / risk_distance, 2) if risk_distance > 0 else 1.0
+
+            # 🏛️ Institutional Invariant: RR to TP1 MUST NEVER fall below 1:1.50 ($2+2=4 Law)
+            if thesis["direction"] == "BUY":
+                min_tp1 = round(execution_price + (risk_distance * 1.5), 3)
+                calibrated_tp = max(float(thesis.get("target_profit", min_tp1)), min_tp1)
+            else:
+                min_tp1 = round(execution_price - (risk_distance * 1.5), 3)
+                orig_tp = float(thesis.get("target_profit", min_tp1))
+                calibrated_tp = min(orig_tp, min_tp1) if orig_tp > 0 else min_tp1
+
+            reward_distance = abs(calibrated_tp - execution_price)
+            rr_ratio = round(reward_distance / risk_distance, 2) if risk_distance > 0 else 1.5
 
             self.states[asset_u] = TradeState.TRIGGERED
             event = {
@@ -343,7 +353,7 @@ class TriTimeframeSniperEngine:
                 "direction": thesis["direction"],
                 "entry_price": execution_price,
                 "stop_loss": tight_sl,
-                "take_profit": thesis["target_profit"],
+                "take_profit": calibrated_tp,
                 "risk_pips": round(risk_distance * 10, 1),
                 "reward_pips": round(reward_distance * 10, 1),
                 "risk_reward_ratio": f"1:{rr_ratio}",

gemini_telegram_copilot/telegram_copilot_service.py

@@ -1349,6 +1349,17 @@ def handle_signal_action(action: str, asset: str, signal_id: Optional[str] = Non
         strat = pending.get('strategy_code', 'STRAT_1_SMC_GOLDEN_SNIPER')
         rules = pending.get('rules_verified') or [{"rule": "10-Rules", "status": "PASSED"}]
 
+        # 🏛️ Self-Healing TP1 Invariant ($2+2=4 Law):
+        # Guarantee that pending['tp1'] maintains minimum 1:1.50 RR from entry_price
+        dist = abs(entry_price - sl)
+        if dist > 0:
+            min_tp1 = round(entry_price + (dist * 1.5), 3) if direction == 'BUY' else round(entry_price - (dist * 1.5), 3)
+            cur_tp1 = float(pending.get('tp1', 0.0))
+            if direction == 'BUY':
+                pending['tp1'] = max(cur_tp1, min_tp1)
+            else:
+                pending['tp1'] = min(cur_tp1, min_tp1) if cur_tp1 > 0 else min_tp1
+
         # Institutional Pre-Execution Guard (Strict 300s / 5m TTL & SL breach check)
         try:
             from core_shared.database_guard import validate_proposal_pre_execution