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-runtime/src/growth.rs

@@ -148,6 +148,18 @@ impl GrowthIntegration {
         self.config.auto_extract = auto_extract;
     }
 
+    /// Configure embedding client for memory retrieval.
+    ///
+    /// Propagates the embedding client to the MemoryRetriever's SemanticScorer,
+    /// enabling embedding-based similarity in addition to TF-IDF.
+    /// Safe to call from non-async contexts.
+    pub fn configure_embedding(
+        &self,
+        client: Arc<dyn zclaw_growth::retrieval::semantic::EmbeddingClient>,
+    ) {
+        self.retriever.set_embedding_client(client);
+    }
+
     /// Set the user profile store for incremental profile updates
     pub fn with_profile_store(mut self, store: Arc<UserProfileStore>) -> Self {
         self.profile_store = Some(store);