fix(audit): 修复深度审计发现的 P0/P1 问题 (8项)

基于 DEEP_AUDIT_REPORT.md 修复 2 CRITICAL + 4 HIGH + 1 MEDIUM 问题:

- C1: PromptOnly 技能集成 LLM 调用 — 定义 LlmCompleter trait，
  通过 LlmDriverAdapter 桥接 zclaw_runtime::LlmDriver，
  PromptOnlySkill.execute() 现在调用 LLM 生成内容
- C2: 反思引擎空记忆 bug — 新增 query_memories_for_reflection()
  从 VikingStorage 查询真实记忆传入 reflect()
- H7: Agent Store 接口适配 — KernelClient 添加 listClones/createClone/
  deleteClone/updateClone 方法，映射到 agent_* 命令
- H8: Hand 审批检查 — hand_execute 执行前检查 needs_approval，
  需审批返回 pending_approval 状态
- M1: 幽灵命令注册 — 注册 hand_get/hand_run_status/hand_run_list
  三个 Tauri 桩命令
- H1/H2: SpeechHand/TwitterHand 添加 demo 标签
- H5: 归档过时 VERIFICATION_REPORT

文档更新: DEEP_AUDIT_REPORT.md 标记修复状态，README.md 更新
关键指标和变更历史。整体完成度从 ~50% 提升至 ~58%。

crates/zclaw-kernel/src/kernel.rs

@@ -1,5 +1,6 @@
 //! Kernel - central coordinator
 
+use std::pin::Pin;
 use std::sync::Arc;
 use tokio::sync::{broadcast, mpsc, Mutex};
 use zclaw_types::{AgentConfig, AgentId, AgentInfo, Event, Result};
@@ -13,16 +14,53 @@ use crate::config::KernelConfig;
 use zclaw_memory::MemoryStore;
 use zclaw_runtime::{AgentLoop, LlmDriver, ToolRegistry, tool::SkillExecutor};
 use zclaw_skills::SkillRegistry;
+use zclaw_skills::LlmCompleter;
 use zclaw_hands::{HandRegistry, HandContext, HandResult, hands::{BrowserHand, SlideshowHand, SpeechHand, QuizHand, WhiteboardHand, ResearcherHand, CollectorHand, ClipHand, TwitterHand, quiz::LlmQuizGenerator}};
 
+/// Adapter that bridges `zclaw_runtime::LlmDriver` → `zclaw_skills::LlmCompleter`
+struct LlmDriverAdapter {
+    driver: Arc<dyn LlmDriver>,
+}
+
+impl zclaw_skills::LlmCompleter for LlmDriverAdapter {
+    fn complete(
+        &self,
+        prompt: &str,
+    ) -> Pin<Box<dyn std::future::Future<Output = std::result::Result<String, String>> + Send + '_>> {
+        let driver = self.driver.clone();
+        let prompt = prompt.to_string();
+        Box::pin(async move {
+            let request = zclaw_runtime::CompletionRequest {
+                messages: vec![zclaw_types::Message::user(prompt)],
+                max_tokens: Some(4096),
+                temperature: Some(0.7),
+                ..Default::default()
+            };
+            let response = driver.complete(request).await
+                .map_err(|e| format!("LLM completion error: {}", e))?;
+            // Extract text from content blocks
+            let text: String = response.content.iter()
+                .filter_map(|block| match block {
+                    zclaw_runtime::ContentBlock::Text { text } => Some(text.as_str()),
+                    _ => None,
+                })
+                .collect::<Vec<_>>()
+                .join("");
+            Ok(text)
+        })
+    }
+}
+
 /// Skill executor implementation for Kernel
 pub struct KernelSkillExecutor {
     skills: Arc<SkillRegistry>,
+    llm: Arc<dyn LlmCompleter>,
 }
 
 impl KernelSkillExecutor {
-    pub fn new(skills: Arc<SkillRegistry>) -> Self {
-        Self { skills }
+    pub fn new(skills: Arc<SkillRegistry>, driver: Arc<dyn LlmDriver>) -> Self {
+        let llm: Arc<dyn zclaw_skills::LlmCompleter> = Arc::new(LlmDriverAdapter { driver });
+        Self { skills, llm }
     }
 }
 
@@ -38,6 +76,7 @@ impl SkillExecutor for KernelSkillExecutor {
         let context = zclaw_skills::SkillContext {
             agent_id: agent_id.to_string(),
             session_id: session_id.to_string(),
+            llm: Some(self.llm.clone()),
             ..Default::default()
         };
         let result = self.skills.execute(&zclaw_types::SkillId::new(skill_id), &context, input).await?;
@@ -53,6 +92,7 @@ pub struct Kernel {
     events: EventBus,
     memory: Arc<MemoryStore>,
     driver: Arc<dyn LlmDriver>,
+    llm_completer: Arc<dyn zclaw_skills::LlmCompleter>,
     skills: Arc<SkillRegistry>,
     skill_executor: Arc<KernelSkillExecutor>,
     hands: Arc<HandRegistry>,
@@ -99,7 +139,11 @@ impl Kernel {
         hands.register(Arc::new(TwitterHand::new())).await;
 
         // Create skill executor
-        let skill_executor = Arc::new(KernelSkillExecutor::new(skills.clone()));
+        let skill_executor = Arc::new(KernelSkillExecutor::new(skills.clone(), driver.clone()));
+
+        // Create LLM completer for skill system (shared with skill_executor)
+        let llm_completer: Arc<dyn zclaw_skills::LlmCompleter> =
+            Arc::new(LlmDriverAdapter { driver: driver.clone() });
 
         // Initialize trigger manager
         let trigger_manager = crate::trigger_manager::TriggerManager::new(hands.clone());
@@ -117,6 +161,7 @@ impl Kernel {
             events,
             memory,
             driver,
+            llm_completer,
             skills,
             skill_executor,
             hands,
@@ -426,7 +471,12 @@ impl Kernel {
         context: zclaw_skills::SkillContext,
         input: serde_json::Value,
     ) -> Result<zclaw_skills::SkillResult> {
-        self.skills.execute(&zclaw_types::SkillId::new(id), &context, input).await
+        // Inject LLM completer into context for PromptOnly skills
+        let mut ctx = context;
+        if ctx.llm.is_none() {
+            ctx.llm = Some(self.llm_completer.clone());
+        }
+        self.skills.execute(&zclaw_types::SkillId::new(id), &ctx, input).await
     }
 
     /// Get the hands registry