feat(quant-engine): 10개 고전 기술전략 갭분석 후 7개 보조신호 채택

사용자 제시 10개 고전 기술전략(골든크로스/모멘텀/52주신고가/연속상승하락/이격도/돌파실패/
강한종가/변동성확장/평균회귀/추세필터)을 기존 엔진과 대조한 갭분석 결과:
- 이미 구현됨: 모멘텀(VELOCITY_V1/RS_MOMENTUM_V1), 이격도·평균회귀(MEAN_REVERSION_GATE_V1)
- 신규 채택 7개: GOLDEN_CROSS_SIGNAL_V1, STRONG_CLOSE_SIGNAL_V1,
  VOLATILITY_EXPANSION_BREAKOUT_V1, FIFTY_TWO_WEEK_HIGH_TRIGGER_V1, CONSECUTIVE_STREAK_V1,
  BREAKOUT_FAILURE_STOP_V1, TREND_FILTER_GATE_V1

AGENTS.md 하드룰(추격매수 방지, anti-late-entry gate 필수통과)에 따라 BUY 방향 신호 전부를
STRATEGY_SCORING의 보조신호로만 편입 — BREAKOUT_QUALITY_GATE_V2/FOLLOW_THROUGH_DAY_CONFIRM_V1/
ANTI_LATE_ENTRY_GATE_V2 게이트 체인을 우회하는 독립 BUY 트리거로는 사용하지 않음.

검증: validate_specs/validate_golden_coverage_100(100%)/validate_calibration_registry_v1/
validate_schema_model_generation_v1/validate_agents_shrink_v1 전부 PASS. golden test 22/22 PASS.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/quant_engine/models/generated/consecutive_streak_v1_schema.py

@@ -0,0 +1,33 @@
+"""Auto-generated schema model descriptor."""
+from __future__ import annotations
+
+from dataclasses import dataclass
+import json
+from pathlib import Path
+from typing import Any
+
+SCHEMA_TITLE = 'CONSECUTIVE_STREAK_V1'
+SCHEMA_ID = 'schema://formula/CONSECUTIVE_STREAK_V1'
+SCHEMA_PATH = 'schemas/generated/consecutive_streak_v1.schema.json'
+SCHEMA_PROPERTIES = ['formula_id', 'owner', 'status', 'inputs', 'outputs']
+SCHEMA_REQUIRED = ['formula_id', 'owner', 'status', 'inputs', 'outputs']
+
+@dataclass(frozen=True)
+class SchemaModel:
+    title: str
+    schema_id: str
+    path: str
+    properties: list[str]
+    required: list[str]
+
+def load_schema() -> dict[str, Any]:
+    return json.loads(Path(__file__).with_suffix('.schema.json').read_text(encoding='utf-8'))
+
+def describe() -> SchemaModel:
+    return SchemaModel(
+        title=SCHEMA_TITLE,
+        schema_id=SCHEMA_ID,
+        path=SCHEMA_PATH,
+        properties=list(SCHEMA_PROPERTIES),
+        required=list(SCHEMA_REQUIRED),
+    )