fix(growth): HIGH-6 修复 extract_combined 合并提取空壳

根因: growth.rs 构造 CombinedExtraction 时硬编码 experiences: Vec::new()
和 profile_signals: default()，导致 L1 结构化经验不被提取、L2 技能进化
没有输入数据、整个进化引擎无法端到端工作。

修复:
- extractor.rs: 添加 COMBINED_EXTRACTION_PROMPT 统一 prompt，单次 LLM 调用
  同时输出 memories + experiences + profile_signals
- extractor.rs: 添加 parse_combined_response() 解析 LLM JSON 响应
- LlmDriverForExtraction trait: 添加 extract_with_prompt() 方法（默认不支持，
  退化到现有 extract() + 启发式推断）
- MemoryExtractor: 添加 extract_combined() 方法，优先单次调用，失败则退化
- growth.rs: extract_combined() 使用新的合并提取替代硬编码空值
- TauriExtractionDriver: 实现 extract_with_prompt()
- ProfileSignals: 添加 has_any_signal() 方法
- types.rs: ProfileSignals 无 structural 变化（字段已存在）

测试: 4 个新测试（parse_combined_response_full/minimal/invalid +
extract_combined_fallback），11 个 extractor 测试全部通过

crates/zclaw-runtime/src/growth.rs

@@ -15,7 +15,7 @@ use zclaw_growth::{
     AggregatedPattern, CombinedExtraction, EvolutionConfig, EvolutionEngine,
     ExperienceExtractor, GrowthTracker, InjectionFormat,
     LlmDriverForExtraction, MemoryExtractor, MemoryRetriever, PromptInjector,
-    ProfileSignals, RetrievalResult, UserProfileUpdater, VikingAdapter,
+    RetrievalResult, UserProfileUpdater, VikingAdapter,
 };
 use zclaw_memory::{ExtractedFactBatch, Fact, FactCategory, UserProfileStore};
 use zclaw_types::{AgentId, Message, Result, SessionId};
@@ -263,8 +263,8 @@ impl GrowthIntegration {
         Ok(count)
     }
 
-    /// Combined extraction: single LLM call that produces both stored memories
-    /// and structured facts, avoiding double extraction overhead.
+    /// Combined extraction: single LLM call that produces stored memories,
+    /// structured experiences, and profile signals — all in one pass.
     ///
     /// Returns `(memory_count, Option<ExtractedFactBatch>)` on success.
     pub async fn extract_combined(
@@ -277,25 +277,28 @@ impl GrowthIntegration {
             return Ok(None);
         }
 
-        // Single LLM extraction call
-        let extracted = self
+        // 单次 LLM 提取：memories + experiences + profile_signals
+        let combined = self
             .extractor
-            .extract(messages, session_id.clone())
+            .extract_combined(messages, session_id.clone())
             .await
             .unwrap_or_else(|e| {
                 tracing::warn!("[GrowthIntegration] Combined extraction failed: {}", e);
-                Vec::new()
+                CombinedExtraction::default()
             });
 
-        if extracted.is_empty() {
+        if combined.memories.is_empty()
+            && combined.experiences.is_empty()
+            && !combined.profile_signals.has_any_signal()
+        {
             return Ok(None);
         }
 
-        let mem_count = extracted.len();
+        let mem_count = combined.memories.len();
 
         // Store raw memories
         self.extractor
-            .store_memories(&agent_id.to_string(), &extracted)
+            .store_memories(&agent_id.to_string(), &combined.memories)
             .await?;
 
         // Track learning event
@@ -304,14 +307,9 @@ impl GrowthIntegration {
             .await?;
 
         // Persist structured experiences (L1 enhancement)
-        let combined_extraction = CombinedExtraction {
-            memories: extracted.clone(),
-            experiences: Vec::new(), // LLM-driven extraction fills this later
-            profile_signals: ProfileSignals::default(),
-        };
         if let Ok(exp_count) = self
             .experience_extractor
-            .persist_experiences(&agent_id.to_string(), &combined_extraction)
+            .persist_experiences(&agent_id.to_string(), &combined)
             .await
         {
             if exp_count > 0 {
@@ -324,9 +322,7 @@ impl GrowthIntegration {
 
         // Update user profile from extraction signals (L1 enhancement)
         if let Some(profile_store) = &self.profile_store {
-            let updates = self
-                .profile_updater
-                .collect_updates(&combined_extraction);
+            let updates = self.profile_updater.collect_updates(&combined);
             let user_id = agent_id.to_string();
             for update in updates {
                 if let Err(e) = profile_store
@@ -342,8 +338,9 @@ impl GrowthIntegration {
             }
         }
 
-        // Convert same extracted memories to structured facts (no extra LLM call)
-        let facts: Vec<Fact> = extracted
+        // Convert extracted memories to structured facts
+        let facts: Vec<Fact> = combined
+            .memories
             .into_iter()
             .map(|m| {
                 let category = match m.memory_type {