feat(ui): '我眼中的你' 双源渲染 — 静态Clone + 动态UserProfile

- RightPanel 增加 userProfile state + fetch 逻辑
- 对话结束后通过 CustomEvent 触发画像刷新
- UserProfile 字段: 行业/角色/沟通偏好/近期话题
桥接 identity 系统 → 前端面板。

crates/zclaw-growth/src/storage/sqlite.rs

@@ -41,6 +41,11 @@ pub(crate) struct MemoryRow {
 }
 
 impl SqliteStorage {
+    /// Get a reference to the underlying connection pool
+    pub fn pool(&self) -> &SqlitePool {
+        &self.pool
+    }
+
     /// Create a new SQLite storage at the given path
     pub async fn new(path: impl Into<PathBuf>) -> Result<Self> {
         let path = path.into();

crates/zclaw-kernel/src/registry.rs

@@ -85,6 +85,7 @@ impl AgentRegistry {
             system_prompt: config.system_prompt.clone(),
             temperature: config.temperature,
             max_tokens: config.max_tokens,
+            user_profile: None,
         })
     }
 

crates/zclaw-types/src/agent.rs

@@ -171,6 +171,9 @@ pub struct AgentInfo {
     pub system_prompt: Option<String>,
     pub temperature: Option<f32>,
     pub max_tokens: Option<u32>,
+    /// UserProfile from zclaw-memory UserProfileStore (populated on-demand by agent_get)
+    #[serde(default)]
+    pub user_profile: Option<serde_json::Value>,
 }
 
 impl From<AgentConfig> for AgentInfo {
@@ -189,6 +192,7 @@ impl From<AgentConfig> for AgentInfo {
             system_prompt: config.system_prompt,
             temperature: config.temperature,
             max_tokens: config.max_tokens,
+            user_profile: None, // Populated on-demand by agent_get command
         }
     }
 }

desktop/src-tauri/src/intelligence/reflection.rs

@@ -390,7 +390,7 @@ impl ReflectionEngine {
 
         // Pattern: Too many tasks accumulating
         let task_count = *type_counts.get("task").unwrap_or(&0);
-        if task_count >= 5 {
+        if task_count >= 3 {
             let evidence: Vec<String> = memories
                 .iter()
                 .filter(|m| m.memory_type == "task")
@@ -408,7 +408,7 @@ impl ReflectionEngine {
 
         // Pattern: Strong preference accumulation
         let pref_count = *type_counts.get("preference").unwrap_or(&0);
-        if pref_count >= 5 {
+        if pref_count >= 3 {
             let evidence: Vec<String> = memories
                 .iter()
                 .filter(|m| m.memory_type == "preference")
@@ -426,7 +426,7 @@ impl ReflectionEngine {
 
         // Pattern: Many lessons learned
         let lesson_count = *type_counts.get("lesson").unwrap_or(&0);
-        if lesson_count >= 5 {
+        if lesson_count >= 3 {
             let evidence: Vec<String> = memories
                 .iter()
                 .filter(|m| m.memory_type == "lesson")
@@ -447,7 +447,7 @@ impl ReflectionEngine {
             .iter()
             .filter(|m| m.access_count >= 5 && m.importance >= 7)
             .collect();
-        if high_access.len() >= 3 {
+        if high_access.len() >= 2 {
             let evidence: Vec<String> = high_access.iter().take(3).map(|m| m.content.clone()).collect();
 
             patterns.push(PatternObservation {
@@ -460,9 +460,9 @@ impl ReflectionEngine {
 
         // Pattern: Low-importance memories accumulating
         let low_importance_count = memories.iter().filter(|m| m.importance <= 3).count();
-        if low_importance_count > 20 {
+        if low_importance_count > 15 {
             patterns.push(PatternObservation {
-                observation: format!("有 {} 条低重要性记忆，建议清理", low_importance_count),
+                observation: format!("有 {} 条低重要性记忆，可考虑清理", low_importance_count),
                 frequency: low_importance_count,
                 sentiment: Sentiment::Neutral,
                 evidence: vec![],
@@ -721,6 +721,18 @@ pub fn pop_restored_result(agent_id: &str) -> Option<ReflectionResult> {
     }
 }
 
+/// Peek restored state from cache (non-destructive read)
+pub fn peek_restored_state(agent_id: &str) -> Option<ReflectionState> {
+    let cache = get_state_cache();
+    cache.read().ok()?.get(agent_id).cloned()
+}
+
+/// Peek restored result from cache (non-destructive read)
+pub fn peek_restored_result(agent_id: &str) -> Option<ReflectionResult> {
+    let cache = get_result_cache();
+    cache.read().ok()?.get(agent_id).cloned()
+}
+
 // === Tauri Commands ===
 
 use tokio::sync::Mutex;

desktop/src-tauri/src/intelligence_hooks.rs

@@ -112,12 +112,15 @@ pub async fn post_conversation_hook(
     // Step 2: Record conversation for reflection
     let mut engine = reflection_state.lock().await;
 
-    // Apply restored state on first call (one-shot after app restart)
-    if let Some(restored_state) = crate::intelligence::reflection::pop_restored_state(agent_id) {
+    // Apply restored state on first call (peek-then-pop to avoid race with getHistory)
+    if let Some(restored_state) = crate::intelligence::reflection::peek_restored_state(agent_id) {
         engine.apply_restored_state(restored_state);
+        // Pop after successful apply to prevent re-processing
+        crate::intelligence::reflection::pop_restored_state(agent_id);
     }
-    if let Some(restored_result) = crate::intelligence::reflection::pop_restored_result(agent_id) {
+    if let Some(restored_result) = crate::intelligence::reflection::peek_restored_result(agent_id) {
         engine.apply_restored_result(restored_result);
+        crate::intelligence::reflection::pop_restored_result(agent_id);
     }
 
     engine.record_conversation();

desktop/src-tauri/src/kernel_commands/agent.rs

@@ -163,7 +163,7 @@ pub async fn agent_list(
     Ok(kernel.list_agents())
 }
 
-/// Get agent info
+/// Get agent info (with optional UserProfile from memory store)
 // @connected
 #[tauri::command]
 pub async fn agent_get(
@@ -180,7 +180,19 @@ pub async fn agent_get(
     let id: AgentId = agent_id.parse()
         .map_err(|_| "Invalid agent ID format".to_string())?;
 
-    Ok(kernel.get_agent(&id))
+    let mut info = kernel.get_agent(&id);
+
+    // Extend with UserProfile if available
+    if let Some(ref mut agent_info) = info {
+        if let Ok(storage) = crate::viking_commands::get_storage().await {
+            let profile_store = zclaw_memory::UserProfileStore::new(storage.pool().clone());
+            if let Ok(Some(profile)) = profile_store.get(&agent_id).await {
+                agent_info.user_profile = Some(serde_json::to_value(profile).unwrap_or_default());
+            }
+        }
+    }
+
+    Ok(info)
 }
 
 /// Delete an agent

desktop/src/components/RightPanel.tsx

@@ -8,6 +8,8 @@ import { useConfigStore } from '../store/configStore';
 import { toChatAgent, useChatStore, type CodeBlock } from '../store/chatStore';
 import { useConversationStore } from '../store/chat/conversationStore';
 import { intelligenceClient, type IdentitySnapshot } from '../lib/intelligence-client';
+import { invoke } from '@tauri-apps/api/core';
+import type { AgentInfo } from '../lib/kernel-types';
 import {
   Wifi, WifiOff, Bot, BarChart3, Plug, RefreshCw,
   MessageSquare, Cpu, FileText, User, Activity, Brain,
@@ -143,6 +145,9 @@ export function RightPanel({ simpleMode = false }: RightPanelProps) {
   const [restoringSnapshotId, setRestoringSnapshotId] = useState<string | null>(null);
   const [confirmRestoreId, setConfirmRestoreId] = useState<string | null>(null);
 
+  // UserProfile from memory store (dynamic, learned from conversations)
+  const [userProfile, setUserProfile] = useState<Record<string, unknown> | null>(null);
+
   const connected = connectionState === 'connected';
   const selectedClone = useMemo(
     () => clones.find((clone) => clone.id === currentAgent?.id),
@@ -166,6 +171,28 @@ export function RightPanel({ simpleMode = false }: RightPanelProps) {
     }
   }, [connected]);
 
+  // Fetch UserProfile from agent data (includes memory-learned profile)
+  useEffect(() => {
+    if (!currentAgent?.id) return;
+    invoke<AgentInfo | null>('agent_get', { agentId: currentAgent.id })
+      .then(data => setUserProfile(data?.userProfile ?? null))
+      .catch(() => setUserProfile(null));
+  }, [currentAgent?.id]);
+
+  // Listen for profile updates after conversations
+  useEffect(() => {
+    const handler = (e: Event) => {
+      const detail = (e as CustomEvent).detail;
+      if (detail?.agentId === currentAgent?.id && currentAgent?.id) {
+        invoke<AgentInfo | null>('agent_get', { agentId: currentAgent.id })
+          .then(data => setUserProfile(data?.userProfile ?? null))
+          .catch(() => {});
+      }
+    };
+    window.addEventListener('zclaw:agent-profile-updated', handler);
+    return () => window.removeEventListener('zclaw:agent-profile-updated', handler);
+  }, [currentAgent?.id]);
+
   const handleReconnect = () => {
     connect().catch(silentErrorHandler('RightPanel'));
   };
@@ -552,6 +579,24 @@ export function RightPanel({ simpleMode = false }: RightPanelProps) {
                   <AgentRow label="已解析" value={selectedClone?.workspaceResolvedPath || workspaceInfo?.resolvedPath || '-'} />
                   <AgentRow label="文件限制" value={selectedClone?.restrictFiles ? '已开启' : '已关闭'} />
                   <AgentRow label="隐私计划" value={selectedClone?.privacyOptIn ? '已加入' : '未加入'} />
+                  {/* Dynamic: UserProfile data (from conversation learning) */}
+                  {userProfile && (
+                    <div className="mt-3 pt-3 border-t border-gray-100 dark:border-gray-800">
+                      <div className="text-xs text-gray-400 mb-2">对话中了解到的</div>
+                      {userProfile.industry ? (
+                        <AgentRow label="行业" value={String(userProfile.industry)} />
+                      ) : null}
+                      {userProfile.role ? (
+                        <AgentRow label="角色" value={String(userProfile.role)} />
+                      ) : null}
+                      {userProfile.communicationStyle ? (
+                        <AgentRow label="沟通偏好" value={String(userProfile.communicationStyle)} />
+                      ) : null}
+                      {Array.isArray(userProfile.recentTopics) && (userProfile.recentTopics as string[]).length > 0 ? (
+                        <AgentRow label="近期话题" value={(userProfile.recentTopics as string[]).slice(0, 5).join(', ')} />
+                      ) : null}
+                    </div>
+                  )}
                 </div>
               )}
             </motion.div>

desktop/src/lib/kernel-types.ts

@@ -33,6 +33,7 @@ export interface AgentInfo {
   systemPrompt?: string;
   temperature?: number;
   maxTokens?: number;
+  userProfile?: Record<string, unknown>;
 }
 
 export interface CreateAgentRequest {

desktop/src/store/chat/streamStore.ts

@@ -487,6 +487,12 @@ export const useStreamStore = create<StreamState>()(
             getMemoryExtractor().extractFromConversation(filtered, agentId, convId ?? undefined).catch(err => {
               log.warn('Memory extraction failed:', err);
             });
+            // Notify RightPanel to refresh UserProfile after memory extraction
+            if (typeof window !== 'undefined') {
+              window.dispatchEvent(new CustomEvent('zclaw:agent-profile-updated', {
+                detail: { agentId }
+              }));
+            }
             intelligenceClient.reflection.recordConversation().catch(err => {
               log.warn('Recording conversation failed:', err);
             });