Tighten qualified signal gate

tests/unit/test_outcome_service.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import json
 from datetime import date, datetime, timedelta, timezone
 
 import pytest
@@ -127,6 +128,15 @@ def _make_setup(
     detected: datetime | None = None,
     **kwargs,
 ) -> TradeSetup:
+    targets_json = kwargs.pop(
+        "targets_json",
+        json.dumps([{
+            "price": target,
+            "rr_ratio": rr,
+            "probability": 50.0,
+            "is_primary": True,
+        }]),
+    )
     return TradeSetup(
         ticker_id=ticker.id,
         direction=direction,
@@ -136,6 +146,7 @@ def _make_setup(
         rr_ratio=rr,
         composite_score=50.0,
         detected_at=detected or datetime(2026, 1, 2, 21, 0, tzinfo=timezone.utc),
+        targets_json=targets_json,
         **kwargs,
     )
 

tests/unit/test_qualification.py

@@ -4,10 +4,15 @@ from __future__ import annotations
 
 from types import SimpleNamespace
 
-from app.services.qualification import best_target_probability, setup_qualifies
+from app.services.qualification import (
+    best_target_probability,
+    primary_target_probability,
+    setup_qualifies,
+)
 
 # Default gate: floors only; the momentum selection is off (0). Conviction /
-# conflict / target-probability are optional tighteners, off here.
+# conflict are optional tighteners, off here. Target probability is always
+# required because qualified means the headline target is evidence-backed.
 DEFAULT_GATE = {
     "min_momentum_percentile": 0.0,
     "min_rr": 1.2,
@@ -68,6 +73,15 @@ class TestFloors:
         s = _setup(direction="long", target=120.0, stop_loss=95.0, current_price=94.0)
         assert setup_qualifies(s, DEFAULT_GATE) is False
 
+    def test_missing_target_probability_fails(self):
+        assert setup_qualifies(_setup(targets=[]), DEFAULT_GATE) is False
+
+    def test_non_primary_target_probability_still_passes(self):
+        assert setup_qualifies(
+            _setup(targets=[{"probability": 42.0}]),
+            DEFAULT_GATE,
+        ) is True
+
 
 class TestMomentumGate:
     def test_top_momentum_passes(self):
@@ -76,15 +90,17 @@ class TestMomentumGate:
     def test_below_threshold_fails(self):
         assert setup_qualifies(_setup(momentum_percentile=50.0), MOMENTUM_GATE) is False
 
-    def test_missing_percentile_defers_to_floors(self):
-        # No percentile attached (e.g. production not yet wired) → the momentum
-        # gate is skipped and the setup still clears on the floors.
-        assert setup_qualifies(_setup(), MOMENTUM_GATE) is True
+    def test_missing_percentile_fails_when_gate_active(self):
+        # No residual rank means the production momentum edge was not measured.
+        assert setup_qualifies(_setup(), MOMENTUM_GATE) is False
 
     def test_threshold_zero_disables_gate(self):
         # min_momentum_percentile 0 → a low-momentum name still passes.
         assert setup_qualifies(_setup(momentum_percentile=10.0), DEFAULT_GATE) is True
 
+    def test_threshold_zero_allows_missing_percentile(self):
+        assert setup_qualifies(_setup(), DEFAULT_GATE) is True
+
     def test_missing_key_defaults_off(self):
         legacy = {k: v for k, v in DEFAULT_GATE.items() if k != "min_momentum_percentile"}
         assert setup_qualifies(_setup(momentum_percentile=10.0), legacy) is True
@@ -146,3 +162,14 @@ class TestBestTargetProbability:
 
     def test_empty_is_zero(self):
         assert best_target_probability(_setup(targets=[])) == 0.0
+
+    def test_primary_probability_prefers_starred_target(self):
+        s = _setup(targets=[
+            {"probability": 70.0},
+            {"probability": 45.0, "is_primary": True},
+        ])
+        assert primary_target_probability(s) == 45.0
+
+    def test_primary_probability_falls_back_to_best(self):
+        s = _setup(targets=[{"probability": 40.0}, {"probability": 72.0}])
+        assert primary_target_probability(s) == 72.0