fix(安全): 修复HTML导出中的XSS漏洞并清理调试日志

refactor(日志): 替换console.log为tracing日志系统
style(代码): 移除未使用的代码和依赖项

feat(测试): 添加端到端测试文档和CI工作流
docs(变更日志): 更新CHANGELOG.md记录0.1.0版本变更

perf(构建): 更新依赖版本并优化CI流程

desktop/src/store/activeLearningStore.ts

@@ -1,425 +0,0 @@
-/**
- * ActiveLearningStore - 主动学习状态管理
- *
- * 猡久学习事件和学习模式，学习建议的状态。
- */
-
-import { create } from 'zustand';
-import { persist } from 'zustand/middleware';
-import {
-  type LearningEvent,
-  type LearningPattern,
-  type LearningSuggestion,
-  type LearningEventType,
-  type LearningConfig,
-} from '../types/active-learning';
-
-// === Types ===
-
-interface ActiveLearningState {
-  events: LearningEvent[];
-  patterns: LearningPattern[];
-  suggestions: LearningSuggestion[];
-  config: LearningConfig;
-  isLoading: boolean;
-  error: string | null;
-}
-
-interface ActiveLearningActions {
-  recordEvent: (event: Omit<LearningEvent, 'id' | 'timestamp' | 'acknowledged'>) => Promise<LearningEvent>;
-  recordFeedback: (agentId: string, messageId: string, feedback: string, context?: string) => Promise<LearningEvent | null>;
-  acknowledgeEvent: (eventId: string) => void;
-  getPatterns: (agentId: string) => LearningPattern[];
-  getSuggestions: (agentId: string) => LearningSuggestion[];
-  applySuggestion: (suggestionId: string) => void;
-  dismissSuggestion: (suggestionId: string) => void;
-  getStats: (agentId: string) => ActiveLearningStats;
-  setConfig: (config: Partial<LearningConfig>) => void;
-  clearEvents: (agentId: string) => void;
-  exportLearningData: (agentId: string) => Promise<string>;
-  importLearningData: (agentId: string, data: string) => Promise<void>;
-}
-
-interface ActiveLearningStats {
-  totalEvents: number;
-  eventsByType: Record<LearningEventType, number>;
-  totalPatterns: number;
-  avgConfidence: number;
-}
-
-export type ActiveLearningStore = ActiveLearningState & ActiveLearningActions;
-
-const STORAGE_KEY = 'zclaw-active-learning';
-const MAX_EVENTS = 1000;
-
-// === Helper Functions ===
-
-function generateEventId(): string {
-  return `le-${Date.now()}-${Math.random().toString(36).slice(2)}`;
-}
-
-function analyzeSentiment(text: string): 'positive' | 'negative' | 'neutral' {
-  const positive = ['好的', '很棒', '谢谢', '完美', 'excellent', '喜欢', '爱了', 'good', 'great', 'nice', '满意'];
-  const negative = ['不好', '差', '糟糕', '错误', 'wrong', 'bad', '不喜欢', '讨厌', '问题', '失败', 'fail', 'error'];
-
-  const lowerText = text.toLowerCase();
-
-  if (positive.some(w => lowerText.includes(w))) return 'positive';
-  if (negative.some(w => lowerText.includes(w))) return 'negative';
-  return 'neutral';
-}
-
-function analyzeEventType(text: string): LearningEventType {
-  const lowerText = text.toLowerCase();
-
-  if (lowerText.includes('纠正') || lowerText.includes('不对') || lowerText.includes('修改')) {
-    return 'correction';
-  }
-  if (lowerText.includes('喜欢') || lowerText.includes('偏好') || lowerText.includes('风格')) {
-    return 'preference';
-  }
-  if (lowerText.includes('场景') || lowerText.includes('上下文') || lowerText.includes('情况')) {
-    return 'context';
-  }
-  if (lowerText.includes('总是') || lowerText.includes('经常') || lowerText.includes('习惯')) {
-    return 'behavior';
-  }
-  return 'feedback';
-}
-
-function inferPreference(feedback: string, sentiment: string): string {
-  if (sentiment === 'positive') {
-    if (feedback.includes('简洁')) return '用户偏好简洁的回复';
-    if (feedback.includes('详细')) return '用户偏好详细的回复';
-    if (feedback.includes('快速')) return '用户偏好快速响应';
-    return '用户对当前回复风格满意';
-  }
-  if (sentiment === 'negative') {
-    if (feedback.includes('太长')) return '用户偏好更短的回复';
-    if (feedback.includes('太短')) return '用户偏好更详细的回复';
-    if (feedback.includes('不准确')) return '用户偏好更准确的信息';
-    return '用户对当前回复风格不满意';
-  }
-  return '用户反馈中性';
-}
-
-// === Store ===
-
-export const useActiveLearningStore = create<ActiveLearningStore>()(
-  persist(
-    (set, get) => ({
-      events: [],
-      patterns: [],
-      suggestions: [],
-      config: {
-        enabled: true,
-        minConfidence: 0.5,
-        maxEvents: MAX_EVENTS,
-        suggestionCooldown: 2,
-      },
-      isLoading: false,
-      error: null,
-
-      recordEvent: async (event) => {
-        const { events, config } = get();
-        if (!config.enabled) throw new Error('Learning is disabled');
-
-        // 检查重复事件
-        const existing = events.find(e =>
-          e.agentId === event.agentId &&
-          e.messageId === event.messageId &&
-          e.type === event.type
-        );
-
-        if (existing) {
-          // 更新现有事件
-          const updated = events.map(e =>
-            e.id === existing.id
-              ? {
-                  ...e,
-                  observation: e.observation + ' | ' + event.observation,
-                  confidence: (e.confidence + event.confidence) / 2,
-                  appliedCount: e.appliedCount + 1,
-                }
-              : e
-          );
-          set({ events: updated });
-          return existing;
-        }
-
-        // 创建新事件
-        const newEvent: LearningEvent = {
-          ...event,
-          id: generateEventId(),
-          timestamp: Date.now(),
-          acknowledged: false,
-          appliedCount: 0,
-        };
-
-        // 提取模式
-        const newPatterns = extractPatterns(newEvent, get().patterns);
-        const newSuggestions = generateSuggestions(newEvent, newPatterns);
-
-        // 保持事件数量限制
-        const updatedEvents = [newEvent, ...events].slice(0, config.maxEvents);
-
-        set({
-          events: updatedEvents,
-          patterns: [...get().patterns, ...newPatterns],
-          suggestions: [...get().suggestions, ...newSuggestions],
-        });
-
-        return newEvent;
-      },
-
-      recordFeedback: async (agentId, messageId, feedback, context) => {
-        const { config } = get();
-        if (!config.enabled) return null;
-
-        const sentiment = analyzeSentiment(feedback);
-        const type = analyzeEventType(feedback);
-
-        return get().recordEvent({
-          type,
-          agentId,
-          messageId,
-          trigger: context || 'User feedback',
-          observation: feedback,
-          context,
-          inferredPreference: inferPreference(feedback, sentiment),
-          confidence: sentiment === 'positive' ? 0.8 : sentiment === 'negative' ? 0.5 : 0.3,
-          appliedCount: 0,
-        });
-      },
-
-      acknowledgeEvent: (eventId) => {
-        const { events } = get();
-        set({
-          events: events.map(e =>
-            e.id === eventId ? { ...e, acknowledged: true } : e
-          ),
-        });
-      },
-
-      getPatterns: (agentId) => {
-        return get().patterns.filter(p => p.agentId === agentId);
-      },
-
-      getSuggestions: (agentId) => {
-        const now = Date.now();
-        return get().suggestions.filter(s =>
-          s.agentId === agentId &&
-          !s.dismissed &&
-          (!s.expiresAt || s.expiresAt.getTime() > now)
-        );
-      },
-
-      applySuggestion: (suggestionId) => {
-        const { suggestions, patterns } = get();
-        const suggestion = suggestions.find(s => s.id === suggestionId);
-
-        if (suggestion) {
-          // 更新模式置信度
-          const updatedPatterns = patterns.map(p =>
-            p.pattern === suggestion.pattern
-              ? { ...p, confidence: Math.min(1, p.confidence + 0.1) }
-              : p
-          );
-
-          set({
-            suggestions: suggestions.map(s =>
-              s.id === suggestionId ? { ...s, dismissed: false } : s
-            ),
-            patterns: updatedPatterns,
-          });
-        }
-      },
-
-      dismissSuggestion: (suggestionId) => {
-        const { suggestions } = get();
-        set({
-          suggestions: suggestions.map(s =>
-            s.id === suggestionId ? { ...s, dismissed: true } : s
-          ),
-        });
-      },
-
-      getStats: (agentId) => {
-        const { events, patterns } = get();
-        const agentEvents = events.filter(e => e.agentId === agentId);
-        const agentPatterns = patterns.filter(p => p.agentId === agentId);
-
-        const eventsByType: Record<LearningEventType, number> = {
-          preference: 0,
-          correction: 0,
-          context: 0,
-          feedback: 0,
-          behavior: 0,
-          implicit: 0,
-        };
-
-        for (const event of agentEvents) {
-          eventsByType[event.type]++;
-        }
-
-        return {
-          totalEvents: agentEvents.length,
-          eventsByType,
-          totalPatterns: agentPatterns.length,
-          avgConfidence: agentPatterns.length > 0
-            ? agentPatterns.reduce((sum, p) => sum + p.confidence, 0) / agentPatterns.length
-            : 0,
-        };
-      },
-
-      setConfig: (config) => {
-        set(state => ({
-          config: { ...state.config, ...config },
-        }));
-      },
-
-      clearEvents: (agentId) => {
-        const { events, patterns, suggestions } = get();
-        set({
-          events: events.filter(e => e.agentId !== agentId),
-          patterns: patterns.filter(p => p.agentId !== agentId),
-          suggestions: suggestions.filter(s => s.agentId !== agentId),
-        });
-      },
-
-      exportLearningData: async (agentId) => {
-        const { events, patterns, config } = get();
-        const data = {
-          events: events.filter(e => e.agentId === agentId),
-          patterns: patterns.filter(p => p.agentId === agentId),
-          config,
-          exportedAt: new Date().toISOString(),
-        };
-        return JSON.stringify(data, null, 2);
-      },
-
-      importLearningData: async (agentId, data) => {
-        try {
-          const parsed = JSON.parse(data);
-          const { events, patterns } = get();
-
-          // 合并导入的数据
-          const mergedEvents = [
-            ...events,
-            ...parsed.events.map((e: LearningEvent) => ({
-              ...e,
-              id: generateEventId(),
-              agentId,
-            })),
-          ].slice(0, MAX_EVENTS);
-
-          const mergedPatterns = [
-            ...patterns,
-            ...parsed.patterns.map((p: LearningPattern) => ({
-              ...p,
-              agentId,
-            })),
-          ];
-
-          set({
-            events: mergedEvents,
-            patterns: mergedPatterns,
-          });
-        } catch (err) {
-          throw new Error(`Failed to import learning data: ${err}`);
-        }
-      },
-    }),
-    {
-      name: STORAGE_KEY,
-    }
-  )
-);
-
-// === Pattern Extraction ===
-
-function extractPatterns(
-  event: LearningEvent,
-  existingPatterns: LearningPattern[]
-): LearningPattern[] {
-  const patterns: LearningPattern[] = [];
-
-  // 偏好模式
-  if (event.observation.includes('谢谢') || event.observation.includes('好的')) {
-    patterns.push({
-      type: 'preference',
-      pattern: 'positive_response_preference',
-      description: '用户偏好正面回复风格',
-      examples: [event.observation],
-      confidence: 0.8,
-      agentId: event.agentId,
-    });
-  }
-
-  // 精确性模式
-  if (event.type === 'correction') {
-    patterns.push({
-      type: 'rule',
-      pattern: 'precision_preference',
-      description: '用户对精确性有更高要求',
-      examples: [event.observation],
-      confidence: 0.9,
-      agentId: event.agentId,
-    });
-  }
-
-  // 上下文模式
-  if (event.context) {
-    patterns.push({
-      type: 'context',
-      pattern: 'context_aware',
-      description: 'Agent 需要关注上下文',
-      examples: [event.context],
-      confidence: 0.6,
-      agentId: event.agentId,
-    });
-  }
-
-  return patterns.filter(p =>
-    !existingPatterns.some(ep => ep.pattern === p.pattern && ep.agentId === p.agentId)
-  );
-}
-
-// === Suggestion Generation ===
-
-function generateSuggestions(
-  event: LearningEvent,
-  patterns: LearningPattern[]
-): LearningSuggestion[] {
-  const suggestions: LearningSuggestion[] = [];
-  const now = Date.now();
-
-  for (const pattern of patterns) {
-    const template = SUGGESTION_TEMPLATES[pattern.pattern];
-
-    if (template) {
-      suggestions.push({
-        id: `sug-${Date.now()}-${Math.random().toString(36).slice(2)}`,
-        agentId: event.agentId,
-        type: pattern.type,
-        pattern: pattern.pattern,
-        suggestion: template,
-        confidence: pattern.confidence,
-        createdAt: now,
-        expiresAt: new Date(now + 7 * 24 * 60 * 60 * 1000),
-        dismissed: false,
-      });
-    }
-  }
-
-  return suggestions;
-}
-
-const SUGGESTION_TEMPLATES: Record<string, string> = {
-  positive_response_preference:
-    '用户似乎偏好正面回复。建议在回复时保持积极和确认的语气。',
-  precision_preference:
-    '用户对精确性有更高要求。建议在提供信息时更加详细和准确。',
-  context_aware:
-    'Agent 需要关注上下文。建议在回复时考虑对话的背景和历史。',
-};

desktop/src/store/chatStore.ts

@@ -8,6 +8,9 @@ import { getAgentSwarm } from '../lib/agent-swarm';
 import { getSkillDiscovery } from '../lib/skill-discovery';
 import { useOfflineStore, isOffline } from './offlineStore';
 import { useConnectionStore } from './connectionStore';
+import { createLogger } from '../lib/logger';
+
+const log = createLogger('ChatStore');
 
 export interface MessageFile {
   name: string;
@@ -307,7 +310,7 @@ export const useChatStore = create<ChatState>()(
     if (isOffline()) {
       const { queueMessage } = useOfflineStore.getState();
       const queueId = queueMessage(content, effectiveAgentId, effectiveSessionKey);
-      console.log(`[Chat] Offline - message queued: ${queueId}`);
+      log.debug(`Offline - message queued: ${queueId}`);
 
       // Show a system message about offline queueing
       const systemMsg: Message = {
@@ -334,7 +337,7 @@ export const useChatStore = create<ChatState>()(
       const messages = get().messages.map(m => ({ role: m.role, content: m.content }));
       const check = await intelligenceClient.compactor.checkThreshold(messages);
       if (check.should_compact) {
-        console.log(`[Chat] Context compaction triggered (${check.urgency}): ${check.current_tokens} tokens`);
+        log.debug(`Context compaction triggered (${check.urgency}): ${check.current_tokens} tokens`);
         const result = await intelligenceClient.compactor.compact(
           get().messages.map(m => ({
             role: m.role,
@@ -355,7 +358,7 @@ export const useChatStore = create<ChatState>()(
         set({ messages: compactedMsgs });
       }
     } catch (err) {
-      console.warn('[Chat] Context compaction check failed:', err);
+      log.warn('Context compaction check failed:', err);
     }
 
     // Build memory-enhanced content
@@ -375,7 +378,7 @@ export const useChatStore = create<ChatState>()(
         enhancedContent = `<context>\n${systemPrompt}\n</context>\n\n${content}`;
       }
     } catch (err) {
-      console.warn('[Chat] Memory enhancement failed, proceeding without:', err);
+      log.warn('Memory enhancement failed, proceeding without:', err);
     }
 
     // Add user message (original content for display)
@@ -477,16 +480,16 @@ export const useChatStore = create<ChatState>()(
               .filter(m => m.role === 'user' || m.role === 'assistant')
               .map(m => ({ role: m.role, content: m.content }));
             getMemoryExtractor().extractFromConversation(msgs, agentId, get().currentConversationId ?? undefined).catch(err => {
-              console.warn('[Chat] Memory extraction failed:', err);
+              log.warn('Memory extraction failed:', err);
             });
             // Track conversation for reflection trigger
             intelligenceClient.reflection.recordConversation().catch(err => {
-              console.warn('[Chat] Recording conversation failed:', err);
+              log.warn('Recording conversation failed:', err);
             });
             intelligenceClient.reflection.shouldReflect().then(shouldReflect => {
               if (shouldReflect) {
                 intelligenceClient.reflection.reflect(agentId, []).catch(err => {
-                  console.warn('[Chat] Reflection failed:', err);
+                  log.warn('Reflection failed:', err);
                 });
               }
             });
@@ -570,7 +573,7 @@ export const useChatStore = create<ChatState>()(
 
       return result.task.id;
     } catch (err) {
-      console.warn('[Chat] Swarm dispatch failed:', err);
+      log.warn('Swarm dispatch failed:', err);
       return null;
     }
   },

desktop/src/store/connectionStore.ts

@@ -27,6 +27,9 @@ import {
   type HealthStatus,
 } from '../lib/health-check';
 import { useConfigStore } from './configStore';
+import { createLogger } from '../lib/logger';
+
+const log = createLogger('ConnectionStore');
 
 // === Mode Selection ===
 // IMPORTANT: Check isTauriRuntime() at RUNTIME (inside functions), not at module load time.
@@ -57,7 +60,7 @@ function loadCustomModels(): CustomModel[] {
       return JSON.parse(stored);
     }
   } catch (err) {
-    console.error('[connectionStore] Failed to parse models:', err);
+    log.error('Failed to parse models:', err);
   }
   return [];
 }
@@ -88,7 +91,7 @@ export function getDefaultModelConfig(): { provider: string; model: string; apiK
         }
       }
     } catch (err) {
-      console.warn('[connectionStore] Failed to read chatStore:', err);
+      log.warn('Failed to read chatStore:', err);
     }
   }
 
@@ -213,10 +216,10 @@ export const useConnectionStore = create<ConnectionStore>((set, get) => {
         // === Internal Kernel Mode (Tauri) ===
         // Check at RUNTIME, not at module load time, to ensure __TAURI_INTERNALS__ is available
         const useInternalKernel = isTauriRuntime();
-        console.log('[ConnectionStore] isTauriRuntime():', useInternalKernel);
+        log.debug('isTauriRuntime():', useInternalKernel);
 
         if (useInternalKernel) {
-          console.log('[ConnectionStore] Using internal ZCLAW Kernel (no external process needed)');
+          log.debug('Using internal ZCLAW Kernel (no external process needed)');
           const kernelClient = getKernelClient();
 
           // Get model config from custom models settings
@@ -230,7 +233,7 @@ export const useConnectionStore = create<ConnectionStore>((set, get) => {
             throw new Error(`模型 ${modelConfig.model} 未配置 API Key，请在"模型与 API"设置页面配置`);
           }
 
-          console.log('[ConnectionStore] Model config:', {
+          log.debug('Model config:', {
             provider: modelConfig.provider,
             model: modelConfig.model,
             hasApiKey: !!modelConfig.apiKey,
@@ -269,9 +272,9 @@ export const useConnectionStore = create<ConnectionStore>((set, get) => {
           await kernelClient.connect();
 
           // Set version
-          set({ gatewayVersion: '0.2.0-internal' });
+          set({ gatewayVersion: '0.1.0-internal' });
 
-          console.log('[ConnectionStore] Connected to internal ZCLAW Kernel');
+          log.debug('Connected to internal ZCLAW Kernel');
           return;
         }
 
@@ -312,7 +315,7 @@ export const useConnectionStore = create<ConnectionStore>((set, get) => {
 
         // Resolve effective token
         const effectiveToken = token || useConfigStore.getState().quickConfig?.gatewayToken || getStoredGatewayToken();
-        console.log('[ConnectionStore] Connecting with token:', effectiveToken ? '[REDACTED]' : '(empty)');
+        log.debug('Connecting with token:', effectiveToken ? '[REDACTED]' : '(empty)');
 
         const candidateUrls = await resolveCandidates();
         let lastError: unknown = null;
@@ -351,7 +354,7 @@ export const useConnectionStore = create<ConnectionStore>((set, get) => {
           set({ gatewayVersion: health?.version });
         } catch { /* health may not return version */ }
 
-        console.log('[ConnectionStore] Connected to:', connectedUrl);
+        log.debug('Connected to:', connectedUrl);
       } catch (err: unknown) {
         const errorMessage = err instanceof Error ? err.message : String(err);
         set({ error: errorMessage });

desktop/src/store/index.ts

@@ -35,8 +35,6 @@ export type { SessionStore, SessionStateSlice, SessionActionsSlice, Session, Ses
 export { useMemoryGraphStore } from './memoryGraphStore';
 export type { MemoryGraphStore, GraphNode, GraphEdge, GraphFilter, GraphLayout } from './memoryGraphStore';
 
-export { useActiveLearningStore } from './activeLearningStore';
-export type { ActiveLearningStore } from './activeLearningStore';
 
 // === Browser Hand Store ===
 export { useBrowserHandStore } from './browserHandStore';

desktop/src/store/meshStore.ts

@@ -1,161 +0,0 @@
-/**
- * Mesh Store - State management for Adaptive Intelligence Mesh
- *
- * Manages workflow recommendations and behavior patterns.
- */
-
-import { create } from 'zustand';
-import { invoke } from '@tauri-apps/api/core';
-import type {
-  WorkflowRecommendation,
-  BehaviorPattern,
-  MeshConfig,
-  MeshAnalysisResult,
-  PatternContext,
-  ActivityType,
-} from '../lib/intelligence-client';
-
-// === Types ===
-
-export interface MeshState {
-  // State
-  recommendations: WorkflowRecommendation[];
-  patterns: BehaviorPattern[];
-  config: MeshConfig;
-  isLoading: boolean;
-  error: string | null;
-  lastAnalysis: string | null;
-
-  // Actions
-  analyze: () => Promise<void>;
-  acceptRecommendation: (recommendationId: string) => Promise<void>;
-  dismissRecommendation: (recommendationId: string) => Promise<void>;
-  recordActivity: (activity: ActivityType, context: PatternContext) => Promise<void>;
-  getPatterns: () => Promise<void>;
-  updateConfig: (config: Partial<MeshConfig>) => Promise<void>;
-  decayPatterns: () => Promise<void>;
-  clearError: () => void;
-}
-
-// === Store ===
-
-export const useMeshStore = create<MeshState>((set, get) => ({
-  // Initial state
-  recommendations: [],
-  patterns: [],
-  config: {
-    enabled: true,
-    min_confidence: 0.6,
-    max_recommendations: 5,
-    analysis_window_hours: 24,
-  },
-  isLoading: false,
-  error: null,
-  lastAnalysis: null,
-
-  // Actions
-  analyze: async () => {
-    set({ isLoading: true, error: null });
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      const result = await invoke<MeshAnalysisResult>('mesh_analyze', { agentId });
-
-      set({
-        recommendations: result.recommendations,
-        patterns: [], // Will be populated by getPatterns
-        lastAnalysis: result.timestamp,
-        isLoading: false,
-      });
-
-      // Also fetch patterns
-      await get().getPatterns();
-    } catch (err) {
-      set({
-        error: err instanceof Error ? err.message : String(err),
-        isLoading: false,
-      });
-    }
-  },
-
-  acceptRecommendation: async (recommendationId: string) => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      await invoke('mesh_accept_recommendation', { agentId, recommendationId });
-
-      // Remove from local state
-      set((state) => ({
-        recommendations: state.recommendations.filter((r) => r.id !== recommendationId),
-      }));
-    } catch (err) {
-      set({ error: err instanceof Error ? err.message : String(err) });
-    }
-  },
-
-  dismissRecommendation: async (recommendationId: string) => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      await invoke('mesh_dismiss_recommendation', { agentId, recommendationId });
-
-      // Remove from local state
-      set((state) => ({
-        recommendations: state.recommendations.filter((r) => r.id !== recommendationId),
-      }));
-    } catch (err) {
-      set({ error: err instanceof Error ? err.message : String(err) });
-    }
-  },
-
-  recordActivity: async (activity: ActivityType, context: PatternContext) => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      await invoke('mesh_record_activity', { agentId, activityType: activity, context });
-    } catch (err) {
-      console.error('Failed to record activity:', err);
-    }
-  },
-
-  getPatterns: async () => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      const patterns = await invoke<BehaviorPattern[]>('mesh_get_patterns', { agentId });
-      set({ patterns });
-    } catch (err) {
-      console.error('Failed to get patterns:', err);
-    }
-  },
-
-  updateConfig: async (config: Partial<MeshConfig>) => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      const newConfig = { ...get().config, ...config };
-      await invoke('mesh_update_config', { agentId, config: newConfig });
-      set({ config: newConfig });
-    } catch (err) {
-      set({ error: err instanceof Error ? err.message : String(err) });
-    }
-  },
-
-  decayPatterns: async () => {
-    try {
-      const agentId = localStorage.getItem('currentAgentId') || 'default';
-      await invoke('mesh_decay_patterns', { agentId });
-      // Refresh patterns after decay
-      await get().getPatterns();
-    } catch (err) {
-      console.error('Failed to decay patterns:', err);
-    }
-  },
-
-  clearError: () => set({ error: null }),
-}));
-
-// === Types for intelligence-client ===
-
-export type {
-  WorkflowRecommendation,
-  BehaviorPattern,
-  MeshConfig,
-  MeshAnalysisResult,
-  PatternContext,
-  ActivityType,
-};

desktop/src/store/personaStore.ts

@@ -1,195 +0,0 @@
-/**
- * Persona Evolution Store
- *
- * Manages persona evolution state and proposals.
- */
-
-import { create } from 'zustand';
-import { invoke } from '@tauri-apps/api/core';
-import type {
-  EvolutionResult,
-  EvolutionProposal,
-  PersonaEvolverConfig,
-  PersonaEvolverState,
-  MemoryEntryForAnalysis,
-} from '../lib/intelligence-client';
-
-export interface PersonaEvolutionStore {
-  // State
-  currentAgentId: string;
-  proposals: EvolutionProposal[];
-  history: EvolutionResult[];
-  isLoading: boolean;
-  error: string | null;
-  config: PersonaEvolverConfig | null;
-  state: PersonaEvolverState | null;
-  showProposalsPanel: boolean;
-
-  // Actions
-  setCurrentAgentId: (agentId: string) => void;
-  setShowProposalsPanel: (show: boolean) => void;
-
-  // Evolution Actions
-  runEvolution: (memories: MemoryEntryForAnalysis[]) => Promise<EvolutionResult | null>;
-  loadEvolutionHistory: (limit?: number) => Promise<void>;
-  loadEvolverState: () => Promise<void>;
-  loadEvolverConfig: () => Promise<void>;
-  updateConfig: (config: Partial<PersonaEvolverConfig>) => Promise<void>;
-
-  // Proposal Actions
-  getPendingProposals: () => EvolutionProposal[];
-  applyProposal: (proposal: EvolutionProposal) => Promise<boolean>;
-  dismissProposal: (proposalId: string) => void;
-  clearProposals: () => void;
-}
-
-export const usePersonaEvolutionStore = create<PersonaEvolutionStore>((set, get) => ({
-  // Initial State
-  currentAgentId: '',
-  proposals: [],
-  history: [],
-  isLoading: false,
-  error: null,
-  config: null,
-  state: null,
-  showProposalsPanel: false,
-
-  // Setters
-  setCurrentAgentId: (agentId: string) => set({ currentAgentId: agentId }),
-  setShowProposalsPanel: (show: boolean) => set({ showProposalsPanel: show }),
-
-  // Run evolution cycle for current agent
-  runEvolution: async (memories: MemoryEntryForAnalysis[]) => {
-    const { currentAgentId } = get();
-    if (!currentAgentId) {
-      set({ error: 'No agent selected' });
-      return null;
-    }
-
-    set({ isLoading: true, error: null });
-
-    try {
-      const result = await invoke<EvolutionResult>('persona_evolve', {
-        agentId: currentAgentId,
-        memories,
-      });
-
-      // Update state with results
-      set((state) => ({
-        history: [result, ...state.history].slice(0, 20),
-        proposals: [...result.proposals, ...state.proposals],
-        isLoading: false,
-        showProposalsPanel: result.proposals.length > 0,
-      }));
-
-      return result;
-    } catch (err) {
-      const errorMsg = err instanceof Error ? err.message : String(err);
-      set({ error: errorMsg, isLoading: false });
-      return null;
-    }
-  },
-
-  // Load evolution history
-  loadEvolutionHistory: async (limit = 10) => {
-    set({ isLoading: true, error: null });
-
-    try {
-      const history = await invoke<EvolutionResult[]>('persona_evolution_history', {
-        limit,
-      });
-      set({ history, isLoading: false });
-    } catch (err) {
-      const errorMsg = err instanceof Error ? err.message : String(err);
-      set({ error: errorMsg, isLoading: false });
-    }
-  },
-
-  // Load evolver state
-  loadEvolverState: async () => {
-    try {
-      const state = await invoke<PersonaEvolverState>('persona_evolver_state');
-      set({ state });
-    } catch (err) {
-      console.error('[PersonaStore] Failed to load evolver state:', err);
-    }
-  },
-
-  // Load evolver config
-  loadEvolverConfig: async () => {
-    try {
-      const config = await invoke<PersonaEvolverConfig>('persona_evolver_config');
-      set({ config });
-    } catch (err) {
-      console.error('[PersonaStore] Failed to load evolver config:', err);
-    }
-  },
-
-  // Update evolver config
-  updateConfig: async (newConfig: Partial<PersonaEvolverConfig>) => {
-    const { config } = get();
-    if (!config) return;
-
-    const updatedConfig = { ...config, ...newConfig };
-
-    try {
-      await invoke('persona_evolver_update_config', { config: updatedConfig });
-      set({ config: updatedConfig });
-    } catch (err) {
-      const errorMsg = err instanceof Error ? err.message : String(err);
-      set({ error: errorMsg });
-    }
-  },
-
-  // Get pending proposals sorted by confidence
-  getPendingProposals: () => {
-    const { proposals } = get();
-    return proposals
-      .filter((p) => p.status === 'pending')
-      .sort((a, b) => b.confidence - a.confidence);
-  },
-
-  // Apply a proposal (approve)
-  applyProposal: async (proposal: EvolutionProposal) => {
-    set({ isLoading: true, error: null });
-
-    try {
-      await invoke('persona_apply_proposal', { proposal });
-
-      // Remove from pending list
-      set((state) => ({
-        proposals: state.proposals.filter((p) => p.id !== proposal.id),
-        isLoading: false,
-      }));
-
-      return true;
-    } catch (err) {
-      const errorMsg = err instanceof Error ? err.message : String(err);
-      set({ error: errorMsg, isLoading: false });
-      return false;
-    }
-  },
-
-  // Dismiss a proposal (reject)
-  dismissProposal: (proposalId: string) => {
-    set((state) => ({
-      proposals: state.proposals.filter((p) => p.id !== proposalId),
-    }));
-  },
-
-  // Clear all proposals
-  clearProposals: () => set({ proposals: [] }),
-}));
-
-// Export convenience hooks
-export const usePendingProposals = () =>
-  usePersonaEvolutionStore((state) => state.getPendingProposals());
-
-export const useEvolutionHistory = () =>
-  usePersonaEvolutionStore((state) => state.history);
-
-export const useEvolverConfig = () =>
-  usePersonaEvolutionStore((state) => state.config);
-
-export const useEvolverState = () =>
-  usePersonaEvolutionStore((state) => state.state);

desktop/src/store/skillMarketStore.ts

@@ -1,360 +0,0 @@
-/**
- * * skillMarketStore.ts - 技能市场状态管理
- *
- * * 猛攻状态管理技能浏览、搜索、安装/卸载等功能
- */
-
-import { create } from 'zustand';
-import { persist } from 'zustand/middleware';
-import type { Skill, SkillReview, SkillMarketState } from '../types/skill-market';
-
-// === 存储键 ===
-const STORAGE_KEY = 'zclaw-skill-market';
-const INSTALLED_KEY = 'zclaw-installed-skills';
-
-// === 默认状态 ===
-const initialState: SkillMarketState = {
-  skills: [],
-  installedSkills: [],
-  searchResults: [],
-  selectedSkill: null,
-  searchQuery: '',
-  categoryFilter: 'all',
-  isLoading: false,
-  error: null,
-};
-
-// === Store 定义 ===
-interface SkillMarketActions {
-  // 技能加载
-  loadSkills: () => Promise<void>;
-  // 技能搜索
-  searchSkills: (query: string) => void;
-  // 分类过滤
-  filterByCategory: (category: string) => void;
-  // 选择技能
-  selectSkill: (skill: Skill | null) => void;
-  // 安装技能
-  installSkill: (skillId: string) => Promise<boolean>;
-  // 卸载技能
-  uninstallSkill: (skillId: string) => Promise<boolean>;
-  // 获取技能详情
-  getSkillDetails: (skillId: string) => Promise<Skill | null>;
-  // 加载评论
-  loadReviews: (skillId: string) => Promise<SkillReview[]>;
-  // 添加评论
-  addReview: (skillId: string, review: Omit<SkillReview, 'id' | 'skillId' | 'createdAt'>) => Promise<void>;
-  // 刷新技能列表
-  refreshSkills: () => Promise<void>;
-  // 清除错误
-  clearError: () => void;
-  // 重置状态
-  reset: () => void;
-}
-
-// === Store 创建 ===
-export const useSkillMarketStore = create<SkillMarketState & SkillMarketActions>()(
-  persist({
-    key: STORAGE_KEY,
-    storage: localStorage,
-    partialize: (state) => ({
-      installedSkills: state.installedSkills,
-      categoryFilter: state.categoryFilter,
-    }),
-  }),
-  initialState,
-  {
-    // === 技能加载 ===
-    loadSkills: async () => {
-      set({ isLoading: true, error: null });
-      try {
-        // 扫描 skills 目录获取可用技能
-        const skills = await scanSkillsDirectory();
-        // 从 localStorage 恢复安装状态
-        const stored = localStorage.getItem(INSTALLED_KEY);
-        const installedSkills: string[] = stored ? JSON.parse(stored) : [];
-        // 更新技能的安装状态
-        const updatedSkills = skills.map(skill => ({
-          ...skill,
-          installed: installedSkills.includes(skill.id),
-        })));
-        set({
-          skills: updatedSkills,
-          installedSkills,
-          isLoading: false,
-        });
-      } catch (err) {
-        set({
-          isLoading: false,
-          error: err instanceof Error ? err.message : '加载技能失败',
-        });
-      }
-    },
-    // === 技能搜索 ===
-    searchSkills: (query: string) => {
-      const { skills } = get();
-      set({ searchQuery: query });
-      if (!query.trim()) {
-        set({ searchResults: [] });
-        return;
-      }
-      const queryLower = query.toLowerCase();
-      const results = skills.filter(skill => {
-        return (
-          skill.name.toLowerCase().includes(queryLower) ||
-          skill.description.toLowerCase().includes(queryLower) ||
-          skill.triggers.some(t => t.toLowerCase().includes(queryLower)) ||
-          skill.capabilities.some(c => c.toLowerCase().includes(queryLower)) ||
-          skill.tags?.some(t => t.toLowerCase().includes(queryLower))
-        );
-      });
-      set({ searchResults: results });
-    },
-    // === 分类过滤 ===
-    filterByCategory: (category: string) => {
-      set({ categoryFilter: category });
-    },
-    // === 选择技能 ===
-    selectSkill: (skill: Skill | null) => {
-      set({ selectedSkill: skill });
-    },
-    // === 安装技能 ===
-    installSkill: async (skillId: string) => {
-      const { skills, installedSkills } = get();
-      const skill = skills.find(s => s.id === skillId);
-      if (!skill) return false;
-      try {
-        // 更新安装状态
-        const newInstalledSkills = [...installedSkills, skillId];
-        const updatedSkills = skills.map(s => ({
-          ...s,
-          installed: s.id === skillId ? true : s.installed,
-          installedAt: s.id === skillId ? new Date().toISOString() : s.installedAt,
-        }));
-        // 持久化安装列表
-        localStorage.setItem(INSTALLED_KEY, JSON.stringify(newInstalledSkills));
-        set({
-          skills: updatedSkills,
-          installedSkills: newInstalledSkills,
-        });
-        return true;
-      } catch (err) {
-        set({
-          error: err instanceof Error ? err.message : '安装技能失败',
-        });
-        return false;
-      }
-    },
-    // === 卸载技能 ===
-    uninstallSkill: async (skillId: string) => {
-      const { skills, installedSkills } = get();
-      try {
-        // 更新安装状态
-        const newInstalledSkills = installedSkills.filter(id => id !== skillId);
-        const updatedSkills = skills.map(s => ({
-          ...s,
-          installed: s.id === skillId ? false : s.installed,
-          installedAt: s.id === skillId ? undefined : s.installedAt,
-        }));
-        // 持久化安装列表
-        localStorage.setItem(INSTALLED_KEY, JSON.stringify(newInstalledSkills));
-        set({
-          skills: updatedSkills,
-          installedSkills: newInstalledSkills,
-        });
-        return true;
-      } catch (err) {
-        set({
-          error: err instanceof Error ? err.message : '卸载技能失败',
-        });
-        return false;
-      }
-    },
-    // === 获取技能详情 ===
-    getSkillDetails: async (skillId: string) => {
-      const { skills } = get();
-      return skills.find(s => s.id === skillId) || null;
-    },
-    // === 加载评论 ===
-    loadReviews: async (skillId: string) => {
-      // MVP: 从 localStorage 模拟加载评论
-      const reviewsKey = `zclaw-skill-reviews-${skillId}`;
-      const stored = localStorage.getItem(reviewsKey);
-      const reviews: SkillReview[] = stored ? JSON.parse(stored) : [];
-      return reviews;
-    },
-    // === 添加评论 ===
-    addReview: async (skillId: string, review: Omit<SkillReview, 'id' | 'skillId' | 'createdAt'>) => {
-      const reviews = await get().loadReviews(skillId);
-      const newReview: SkillReview = {
-        ...review,
-        id: `review-${Date.now()}`,
-        skillId,
-        createdAt: new Date().toISOString(),
-      };
-      const updatedReviews = [...reviews, newReview];
-      // 更新技能的评分和评论数
-      const { skills } = get();
-      const updatedSkills = skills.map(s => {
-        if (s.id === skillId) {
-          const totalRating = updatedReviews.reduce((sum, r) => sum + r.rating, 0);
-          const avgRating = totalRating / updatedReviews.length;
-          return {
-            ...s,
-            rating: Math.round(avgRating * 10) / 10,
-            reviewCount: updatedReviews.length,
-          };
-        }
-        return s;
-      });
-      // 持久化评论
- const reviewsKey = `zclaw-skill-reviews-${skillId}`;
-      localStorage.setItem(reviewsKey, JSON.stringify(updatedReviews));
-      set({ skills: updatedSkills });
-    },
-    // === 刷新技能列表 ===
-    refreshSkills: async () => {
-      // 清除缓存并重新加载
-      localStorage.removeItem(STORAGE_KEY);
-      await get().loadSkills();
-    },
-    // === 清除错误 ===
-    clearError: () => {
-      set({ error: null });
-    },
-    // === 重置状态 ===
-    reset: () => {
-      localStorage.removeItem(STORAGE_KEY);
-      localStorage.removeItem(INSTALLED_KEY);
-      set(initialState);
-    },
-  }
-);
-
-// === 辅助函数 ===
-
-/**
- * 扫描 skills 目录获取可用技能
- * 从后端获取技能列表
- */
-async function scanSkillsDirectory(): Promise<Skill[]> {
-  try {
-    // 动态导入 invoke 以避免循环依赖
-    const { invoke } = await import('@tauri-apps/api/core');
-
-    // 调用后端 skill_list 命令
-    interface BackendSkill {
-    id: string;
-    name: string;
-    description: string;
-    version: string;
-    capabilities: string[];
-    tags: string[];
-  mode: string;
-  enabled: boolean;
-    }
-
-    const backendSkills = await invoke<BackendSkill[]>('skill_list');
-
-    // 转换为前端 Skill 格式
-    const skills: Skill[] = backendSkills.map((s): Skill => ({
-      id: s.id,
-      name: s.name,
-      description: s.description,
-      triggers: s.tags, // 使用 tags 作为触发器
-      capabilities: s.capabilities,
-      toolDeps: [], // 后端暂不提供 toolDeps
-      category: 'discovered', // 后端发现的技能
-      installed: s.enabled,
-      tags: s.tags,
-    }));
-
-    return skills;
-  } catch (err) {
-    console.warn('[skillMarketStore] Failed to load skills from backend, using fallback:', err);
-    // 如果后端调用失败，返回空数组而不是模拟数据
-    return [];
-  }
-}
-      tags: ['文件', '目录', '读写'],
-    },
-    {
-      id: 'security-engineer',
-      name: '安全工程师',
-      description: '安全工程师 - 负责安全审计、漏洞检测、合规检查',
-      triggers: ['安全审计', '漏洞检测', '安全检查', 'security', '渗透测试'],
-      capabilities: ['漏洞扫描', '合规检查', '安全加固', '威胁建模'],
-      toolDeps: ['read', 'grep', 'shell'],
-      category: 'security',
-      installed: false,
-      tags: ['安全', '审计', '漏洞'],
-    },
-    {
-      id: 'ai-engineer',
-      name: 'AI 工程师',
-      description: 'AI/ML 工程师 - 专注机器学习模型开发、LLM 集成和生产系统部署',
-      triggers: ['AI工程师', '机器学习', 'ML模型', 'LLM集成', '深度学习', '模型训练'],
-      capabilities: ['ML 框架', 'LLM 集成', 'RAG 系统', '向量数据库'],
-      toolDeps: ['bash', 'read', 'write', 'grep', 'glob'],
-      category: 'development',
-      installed: false,
-      tags: ['AI', 'ML', 'LLM'],
-    },
-    {
-      id: 'senior-developer',
-      name: '高级开发',
-      description: '高级开发工程师 - 端到端功能实现、复杂问题解决',
-      triggers: ['高级开发', 'senior developer', '端到端', '复杂功能', '架构实现'],
-      capabilities: ['端到端实现', '架构设计', '性能优化', '代码重构'],
-      toolDeps: ['bash', 'read', 'write', 'grep', 'glob'],
-      category: 'development',
-      installed: false,
-      tags: ['开发', '架构', '实现'],
-    },
-    {
-      id: 'frontend-developer',
-      name: '前端开发',
-      description: '前端开发专家 - 擅长 React/Vue/CSS/TypeScript',
-      triggers: ['前端开发', '页面开发', 'UI开发', 'React', 'Vue', 'CSS'],
-      capabilities: ['组件开发', '样式调整', '性能优化', '响应式设计'],
-      toolDeps: ['read', 'write', 'shell'],
-      category: 'development',
-      installed: false,
-      types: ['前端', 'UI', '组件'],
-    },
-    {
-      id: 'backend-architect',
-      name: '后端架构',
-      description: '后端架构设计、API设计、数据库建模',
-      triggers: ['后端架构', 'API设计', '数据库设计', '系统架构', '微服务'],
-      capabilities: ['架构设计', 'API规范', '数据库建模', '性能优化'],
-      toolDeps: ['read', 'write', 'shell'],
-      category: 'development',
-      installed: false,
-      tags: ['后端', '架构', 'API'],
-    },
-    {
-      id: 'devops-automator',
-      name: 'DevOps 自动化',
-      description: 'CI/CD、Docker、K8s、自动化部署',
-      triggers: ['DevOps', 'CI/CD', 'Docker', '部署', '自动化', 'K8s'],
-      capabilities: ['CI/CD配置', '容器化', '自动化部署', '监控告警'],
-      toolDeps: ['shell', 'read', 'write'],
-      category: 'ops',
-      installed: false,
-      tags: ['DevOps', 'Docker', 'CI/CD'],
-    },
-    {
-      id: 'senior-pm',
-      name: '高级PM',
-      description: '项目管理、需求分析、迭代规划',
-      triggers: ['项目管理', '需求分析', '迭代规划', '产品设计', 'PRD'],
-      capabilities: ['需求拆解', '迭代排期', '风险评估', '文档撰写'],
-      toolDeps: ['read', 'write'],
-      category: 'management',
-      installed: false,
-      tags: ['PM', '需求', '迭代'],
-    },
-  ];
-  return skills;
-}