feat: Sprint 2 - 概率语义 + 轻量快照 + 数据库约束

P0-05: confidence → subjective_confidence 改名(15 文件)
       LLM 主观置信度与概率分离
P0-02: predictions 增加 cutoff_at + input_hash(轻量快照)
       MatchContext 暴露 match_dt
       单/多 Agent 路径均记录快照元数据
P2-05: 数据库 CHECK 约束
       - pred_home_goals >= 0
       - pred_away_goals >= 0
       - subjective_confidence 0~1
       - pred_1x2 IN (1,X,2)
       - mode IN (single,multi)
P2-06: limit 分页约束(ge=1, le=200)
P2-01: 新增 /health/ready 就绪检查

src/llm/agents/base.py

@@ -48,7 +48,7 @@ class AgentReport:
     data_sufficiency: str = "medium"              # high | medium | low | none
     analysis: str = ""
     home_edge: float | None = None                # -1.0 ~ 1.0, 正=利主队
-    confidence: float | None = None               # 0.0 ~ 1.0
+    subjective_confidence: float | None = None               # 0.0 ~ 1.0
     key_evidence: list[str] = field(default_factory=list)
     # xg agent 专属
     exp_home_goals: float | None = None
@@ -67,7 +67,7 @@ class AgentReport:
             "data_sufficiency": self.data_sufficiency,
             "analysis": self.analysis,
             "home_edge": self.home_edge,
-            "confidence": self.confidence,
+            "subjective_confidence": self.subjective_confidence,
             "key_evidence": self.key_evidence,
             "exp_home_goals": self.exp_home_goals,
             "exp_away_goals": self.exp_away_goals,
@@ -122,7 +122,7 @@ def _parse_report(agent: str, parsed: dict, resp: LLMResponse, model: str) -> Ag
         data_sufficiency=validated.data_sufficiency,
         analysis=validated.analysis,
         home_edge=validated.home_edge,
-        confidence=validated.confidence,
+        subjective_confidence=validated.subjective_confidence,
         key_evidence=validated.key_evidence,
         exp_home_goals=validated.exp_home_goals,
         exp_away_goals=validated.exp_away_goals,