feat(growth,kernel,runtime): Embedding 接通 + 自学习自动化 — A线+B线 6 项实现

A线 Embedding 接通:
- A1: MemoryRetriever.set_embedding_client() + GrowthIntegration.configure_embedding()
  + Kernel.set_embedding_client() + viking_configure_embedding 传播到 Kernel
- A2: Skill 路由替换 new_tf_idf_only() 为 EmbeddingAdapter + LlmSkillFallback

B线 自学习自动化:
- B1: evolution_bridge.rs — candidate_to_manifest() (PromptOnly, disabled by default)
- B2: Kernel::generate_and_register_skill() 全链路 (LLM→parse→QualityGate→manifest→persist)
- B3: EvolutionMiddleware 双模式 (auto_mode 跳过注入, 留给 kernel 自动处理)
- B4: QualityGate 加固 (body ≥100字符 + 必须含标题 + 置信度上限 1.0)

验证: 934 tests PASS, 0 failures

crates/zclaw-growth/src/evolution_engine.rs

@@ -295,7 +295,7 @@ mod tests {
             industry_context: None,
         };
 
-        let json = r##"{"name":"报表技能","description":"生成报表","triggers":["报表","日报"],"tools":["researcher"],"body_markdown":"# 报表\n步骤","confidence":0.9}"##;
+        let json = r##"{"name":"报表技能","description":"生成报表","triggers":["报表","日报"],"tools":["researcher"],"body_markdown":"# 报表生成技能\n\n## 步骤一\n收集数据源并验证完整性。\n\n## 步骤二\n按模板格式化输出报表。\n\n## 步骤三\n发送至相关接收人。","confidence":0.9}"##;
         let (candidate, report) = engine
             .validate_skill_candidate(json, &pattern, vec!["搜索".to_string()])
             .unwrap();