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

desktop/src-tauri/src/viking_commands.rs

@@ -602,9 +602,11 @@ fn parse_uri(uri: &str) -> Result<(String, MemoryType, String), String> {
 
 /// Configure embedding for semantic memory search
 /// Configures SqliteStorage (VikingStorage) embedding for FTS5 + semantic search.
+/// Also propagates to Kernel's skill router and memory retriever.
 // @connected
 #[tauri::command]
 pub async fn viking_configure_embedding(
+    kernel_state: tauri::State<'_, crate::kernel_commands::KernelState>,
     provider: String,
     api_key: String,
     model: Option<String>,
@@ -621,12 +623,23 @@ pub async fn viking_configure_embedding(
 
     let client_viking = crate::llm::EmbeddingClient::new(config_viking);
     let adapter = crate::embedding_adapter::TauriEmbeddingAdapter::new(client_viking);
+    let arc_adapter = std::sync::Arc::new(adapter);
 
+    // 1. Configure SqliteStorage (existing behavior)
     storage
-        .configure_embedding(std::sync::Arc::new(adapter))
+        .configure_embedding(arc_adapter.clone())
         .await
         .map_err(|e| format!("Failed to configure embedding: {}", e))?;
 
+    // 2. Propagate to Kernel for skill router + memory retriever
+    {
+        let mut kernel_lock = kernel_state.lock().await;
+        if let Some(ref mut k) = *kernel_lock {
+            k.set_embedding_client(arc_adapter);
+            tracing::info!("[VikingCommands] Embedding propagated to Kernel skill router + memory retriever");
+        }
+    }
+
     tracing::info!("[VikingCommands] Embedding configured with provider: {}", provider);
 
     Ok(EmbeddingConfigResult {