Add blue-sky projected targets and played-out setup UX

Fixes stale below-price setups showing as current recommendations. Three
distinct causes share the symptom (get_trade_setups returns the latest stored
setup per direction and never expires it):

- Genuine blue-sky (no overhead S/R): scanner + TargetGenerator now project a
  measured-move target (entry +/- 3*ATR, ~2:1 R:R), flagged projected with a
  low sr_strength probability haircut. Overhead check keys on level tag OR price
  so it never projects through a straddling resistance cluster.
- Projected targets clear a stricter activation bar (long-only, momentum >= 90,
  confidence >= min+10), independent of the general momentum gate. Mirrored in
  frontend qualification.ts.
- Played-out UX (fixes the reported TTWO case, which is R:R-starved under a
  resistance cluster, not blue-sky): when price is at/past target or through the
  stop, RecommendationPanel shows a "No current setup" state and softens the
  stale ticker-level header/reasoning, instead of a stale actionable card.

No migration: the projected flag rides in existing targets_json. 504 backend
unit tests pass; frontend typechecks.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/services/rr_scanner_service.py

@@ -29,6 +29,7 @@ from app.models.trade_setup import TradeSetup
 from app.services.indicator_service import _extract_ohlcv, compute_atr
 from app.services.price_service import query_ohlcv
 from app.services.recommendation_service import (
+    PROJECTED_TARGET_ATR_MULTIPLE,
     _risk_level_from_conflicts,
     build_recommendation_snapshot,
     enhance_trade_setup,
@@ -67,6 +68,16 @@ def _compute_quality_score(
     return w_rr * norm_rr + w_strength * norm_strength + w_proximity * norm_proximity
 
 
+def _projected_target(direction: str, entry_price: float, atr_value: float) -> float:
+    """Measured-move target for a blue-sky direction (no overhead S/R).
+
+    Mirrors the projection in recommendation_service so the scanner's emission
+    decision and the enhanced target agree.
+    """
+    move = PROJECTED_TARGET_ATR_MULTIPLE * atr_value
+    return entry_price + move if direction == "long" else entry_price - move
+
+
 async def _get_dimension_scores(db: AsyncSession, ticker_id: int) -> dict[str, float]:
     result = await db.execute(
         select(DimensionScore).where(DimensionScore.ticker_id == ticker_id)
@@ -428,13 +439,13 @@ async def scan_ticker(
     now = datetime.now(timezone.utc)
     setups: list[TradeSetup] = []
 
-    if levels_above:
-        stop = entry_price - (atr_value * atr_multiplier)
-        risk = entry_price - stop
-        if risk > 0:
+    stop = entry_price - (atr_value * atr_multiplier)
+    risk = entry_price - stop
+    if risk > 0:
+        best_candidate_rr = 0.0
+        best_candidate_target = 0.0
+        if levels_above:
             best_quality = 0.0
-            best_candidate_rr = 0.0
-            best_candidate_target = 0.0
             for lv in levels_above:
                 reward = lv.price_level - entry_price
                 if reward <= 0:
@@ -448,21 +459,29 @@ async def scan_ticker(
                     best_quality = quality
                     best_candidate_rr = rr
                     best_candidate_target = lv.price_level
+        else:
+            # Blue-sky: no resistance overhead. Project a measured-move target so
+            # a breakout name still yields a setup (it faces a stricter gate).
+            projected = _projected_target("long", entry_price, atr_value)
+            projected_rr = (projected - entry_price) / risk
+            if projected_rr >= rr_threshold:
+                best_candidate_rr = projected_rr
+                best_candidate_target = projected
 
-            if best_candidate_rr > 0:
-                setups.append(TradeSetup(
-                    ticker_id=ticker.id,
-                    direction="long",
-                    entry_price=round(entry_price, 4),
-                    stop_loss=round(stop, 4),
-                    target=round(best_candidate_target, 4),
-                    rr_ratio=round(best_candidate_rr, 4),
-                    composite_score=round(composite_score, 4),
-                    detected_at=now,
-                    momentum_percentile=momentum_percentile,
-                    strategy_rank=strategy_rank,
-                    volatility_percentile=volatility_percentile,
-                ))
+        if best_candidate_rr > 0:
+            setups.append(TradeSetup(
+                ticker_id=ticker.id,
+                direction="long",
+                entry_price=round(entry_price, 4),
+                stop_loss=round(stop, 4),
+                target=round(best_candidate_target, 4),
+                rr_ratio=round(best_candidate_rr, 4),
+                composite_score=round(composite_score, 4),
+                detected_at=now,
+                momentum_percentile=momentum_percentile,
+                strategy_rank=strategy_rank,
+                volatility_percentile=volatility_percentile,
+            ))
 
     if levels_below:
         stop = entry_price + (atr_value * atr_multiplier)