Fix sidebar username, Signals filter clarity and layout

- JWT now carries a username claim; sidebar shows "Signed in as <name>"
  instead of the bare user id (sub). Re-login required for the new claim.
- Signals: Min R:R / Min Confidence inputs reflect the effective filter —
  auto-filled from the activation gate when "Qualified only" is on, reset
  to 0 when off (no more misleading 0 while the gate is active).
- Signals layout: Run Scanner moved to its own action row (it's a job
  trigger, not a filter); qualified toggle grouped with the refinement
  filters under one Filters panel.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

app/schemas/trade_setup.py

@@ -16,6 +16,7 @@ class TradeTargetResponse(BaseModel):
     classification: str
     sr_level_id: int
     sr_strength: float
+    is_primary: bool = False
 
 
 class RecommendationSummaryResponse(BaseModel):

app/services/auth_service.py

@@ -59,6 +59,7 @@ async def login(db: AsyncSession, username: str, password: str) -> str:
 
     payload = {
         "sub": str(user.id),
+        "username": user.username,
         "role": user.role,
         "exp": datetime.now(timezone.utc) + timedelta(minutes=settings.jwt_expiry_minutes),
     }

app/services/recommendation_service.py

@@ -443,6 +443,29 @@ def _build_reasoning(
     )
 
 
+PRIMARY_TARGET_MIN_RR = 1.5
+
+
+def _select_primary_target(targets: list[dict], min_rr: float = PRIMARY_TARGET_MIN_RR) -> dict | None:
+    """Primary = the most LIKELY target that still offers real asymmetry.
+
+    Among targets clearing a minimal R:R floor, pick the highest probability
+    (tie-break by R:R). This fixes the old pick, which ignored probability and
+    could land on the furthest, least-likely 'lottery' level. Stronger-reward
+    levels remain in the table as stretch targets. Falls back to the highest-R:R
+    target if nothing clears the floor.
+    """
+    if not targets:
+        return None
+
+    worthwhile = [t for t in targets if float(t.get("rr_ratio", 0.0)) >= min_rr]
+    pool = worthwhile or targets
+    return max(
+        pool,
+        key=lambda t: (float(t.get("probability", 0.0)), float(t.get("rr_ratio", 0.0))),
+    )
+
+
 async def enhance_trade_setup(
     db: AsyncSession,
     ticker: Ticker,
@@ -494,6 +517,17 @@ async def enhance_trade_setup(
             config=config,
         )
 
+    # Primary target = most-likely target with real asymmetry (see
+    # _select_primary_target), not the old quality-score pick that ignored
+    # probability. Sync the setup's headline target/rr_ratio so the chart, gate
+    # and outcome eval all agree with the table's starred row.
+    primary = _select_primary_target(targets)
+    if primary is not None:
+        for target in targets:
+            target["is_primary"] = target is primary
+        setup.target = round(float(primary["price"]), 4)
+        setup.rr_ratio = round(float(primary["rr_ratio"]), 4)
+
     # Per-setup conflicts (target availability is specific to this setup)
     setup_conflicts = list(conflicts)
     if len(targets) < 3: