feat: ai功能的初次提交

electron/services/aiAgentService.ts

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+import http from 'http'
+import https from 'https'
+import { randomUUID } from 'crypto'
+import { URL } from 'url'
+import { ConfigService } from './config'
+import { aiAnalysisService, type AiAnalysisRunEvent } from './aiAnalysisService'
+
+export interface TokenUsage {
+  promptTokens?: number
+  completionTokens?: number
+  totalTokens?: number
+}
+
+export interface AgentRuntimeStatus {
+  phase: 'idle' | 'thinking' | 'tool_running' | 'responding' | 'completed' | 'error' | 'aborted'
+  round?: number
+  currentTool?: string
+  toolsUsed?: number
+  updatedAt: number
+  totalUsage?: TokenUsage
+}
+
+export interface AgentStreamChunk {
+  runId: string
+  conversationId?: string
+  type: 'content' | 'think' | 'tool_start' | 'tool_result' | 'status' | 'done' | 'error'
+  content?: string
+  thinkTag?: string
+  thinkDurationMs?: number
+  toolName?: string
+  toolParams?: Record<string, unknown>
+  toolResult?: unknown
+  error?: string
+  isFinished?: boolean
+  usage?: TokenUsage
+  status?: AgentRuntimeStatus
+}
+
+export interface AgentRunPayload {
+  mode?: 'chat' | 'sql'
+  conversationId?: string
+  userInput: string
+  assistantId?: string
+  activeSkillId?: string
+  chatScope?: 'group' | 'private'
+  sqlContext?: {
+    schemaText?: string
+    targetHint?: string
+  }
+}
+
+interface ActiveAgentRun {
+  runId: string
+  mode: 'chat' | 'sql'
+  conversationId?: string
+  innerRunId?: string
+  aborted: boolean
+}
+
+function normalizeText(value: unknown, fallback = ''): string {
+  const text = String(value ?? '').trim()
+  return text || fallback
+}
+
+function buildApiUrl(baseUrl: string, path: string): string {
+  const base = baseUrl.replace(/\/+$/, '')
+  const suffix = path.startsWith('/') ? path : `/${path}`
+  return `${base}${suffix}`
+}
+
+function extractSqlText(raw: string): string {
+  const text = normalizeText(raw)
+  if (!text) return ''
+  const fenced = text.match(/```(?:sql)?\s*([\s\S]*?)```/i)
+  if (fenced?.[1]) return fenced[1].trim()
+  return text
+}
+
+class AiAgentService {
+  private readonly config = ConfigService.getInstance()
+  private readonly runs = new Map<string, ActiveAgentRun>()
+
+  private getSharedModelConfig(): { apiBaseUrl: string; apiKey: string; model: string } {
+    return {
+      apiBaseUrl: normalizeText(this.config.get('aiModelApiBaseUrl')),
+      apiKey: normalizeText(this.config.get('aiModelApiKey')),
+      model: normalizeText(this.config.get('aiModelApiModel'), 'gpt-4o-mini')
+    }
+  }
+
+  private emitStatus(
+    run: ActiveAgentRun,
+    onChunk: (chunk: AgentStreamChunk) => void,
+    phase: AgentRuntimeStatus['phase'],
+    extra?: Partial<AgentRuntimeStatus>
+  ): void {
+    onChunk({
+      runId: run.runId,
+      conversationId: run.conversationId,
+      type: 'status',
+      status: {
+        phase,
+        updatedAt: Date.now(),
+        ...extra
+      }
+    })
+  }
+
+  private mapRunEventToChunk(
+    run: ActiveAgentRun,
+    event: AiAnalysisRunEvent
+  ): AgentStreamChunk | null {
+    run.innerRunId = event.runId
+    run.conversationId = event.conversationId || run.conversationId
+    if (event.stage === 'llm_round_started') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'think',
+        content: event.message,
+        thinkTag: 'round'
+      }
+    }
+    if (event.stage === 'tool_start') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'tool_start',
+        toolName: event.toolName,
+        toolParams: (event.data || {}) as Record<string, unknown>
+      }
+    }
+    if (event.stage === 'tool_done' || event.stage === 'tool_error') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'tool_result',
+        toolName: event.toolName,
+        toolResult: event.data || { status: event.status, durationMs: event.durationMs }
+      }
+    }
+    if (event.stage === 'completed') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'status',
+        status: { phase: 'completed', updatedAt: Date.now() }
+      }
+    }
+    if (event.stage === 'aborted') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'status',
+        status: { phase: 'aborted', updatedAt: Date.now() }
+      }
+    }
+    if (event.stage === 'error') {
+      return {
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'status',
+        status: { phase: 'error', updatedAt: Date.now() }
+      }
+    }
+    return null
+  }
+
+  private async callModel(payload: any, apiBaseUrl: string, apiKey: string): Promise<any> {
+    const endpoint = buildApiUrl(apiBaseUrl, '/chat/completions')
+    const body = JSON.stringify(payload)
+    const urlObj = new URL(endpoint)
+    return new Promise((resolve, reject) => {
+      const requestFn = urlObj.protocol === 'https:' ? https.request : http.request
+      const req = requestFn({
+        hostname: urlObj.hostname,
+        port: urlObj.port || (urlObj.protocol === 'https:' ? 443 : 80),
+        path: urlObj.pathname + urlObj.search,
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+          'Content-Length': Buffer.byteLength(body).toString(),
+          Authorization: `Bearer ${apiKey}`
+        }
+      }, (res) => {
+        let data = ''
+        res.on('data', (chunk) => { data += String(chunk) })
+        res.on('end', () => {
+          try {
+            resolve(JSON.parse(data || '{}'))
+          } catch (error) {
+            reject(new Error(`AI 响应解析失败: ${String(error)}`))
+          }
+        })
+      })
+      req.setTimeout(45_000, () => {
+        req.destroy()
+        reject(new Error('AI 请求超时'))
+      })
+      req.on('error', reject)
+      req.write(body)
+      req.end()
+    })
+  }
+
+  async runStream(
+    payload: AgentRunPayload,
+    runtime: {
+      onChunk: (chunk: AgentStreamChunk) => void
+      onFinished?: (result: { success: boolean; runId: string; conversationId?: string; error?: string }) => void
+    }
+  ): Promise<{ success: boolean; runId: string }> {
+    const runId = randomUUID()
+    const mode = payload.mode === 'sql' ? 'sql' : 'chat'
+    const run: ActiveAgentRun = {
+      runId,
+      mode,
+      conversationId: normalizeText(payload.conversationId) || undefined,
+      aborted: false
+    }
+    this.runs.set(runId, run)
+
+    this.execute(run, payload, runtime).catch((error) => {
+      runtime.onChunk({
+        runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: String((error as Error)?.message || error),
+        isFinished: true
+      })
+      runtime.onFinished?.({
+        success: false,
+        runId,
+        conversationId: run.conversationId,
+        error: String((error as Error)?.message || error)
+      })
+      this.runs.delete(runId)
+    })
+
+    return { success: true, runId }
+  }
+
+  private async execute(
+    run: ActiveAgentRun,
+    payload: AgentRunPayload,
+    runtime: {
+      onChunk: (chunk: AgentStreamChunk) => void
+      onFinished?: (result: { success: boolean; runId: string; conversationId?: string; error?: string }) => void
+    }
+  ): Promise<void> {
+    if (run.mode === 'sql') {
+      await this.executeSqlMode(run, payload, runtime)
+      return
+    }
+    this.emitStatus(run, runtime.onChunk, 'thinking')
+    const result = await aiAnalysisService.sendMessage(
+      normalizeText(payload.conversationId),
+      normalizeText(payload.userInput),
+      {
+        assistantId: normalizeText(payload.assistantId),
+        activeSkillId: normalizeText(payload.activeSkillId),
+        chatScope: payload.chatScope === 'group' ? 'group' : 'private'
+      },
+      {
+        onRunEvent: (event) => {
+          const mapped = this.mapRunEventToChunk(run, event)
+          if (mapped) runtime.onChunk(mapped)
+        }
+      }
+    )
+    if (run.aborted) {
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: '任务已取消',
+        isFinished: true
+      })
+      runtime.onFinished?.({
+        success: false,
+        runId: run.runId,
+        conversationId: run.conversationId,
+        error: '任务已取消'
+      })
+      this.runs.delete(run.runId)
+      return
+    }
+    if (!result.success || !result.result) {
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: result.error || '执行失败',
+        isFinished: true
+      })
+      runtime.onFinished?.({
+        success: false,
+        runId: run.runId,
+        conversationId: run.conversationId,
+        error: result.error || '执行失败'
+      })
+      this.runs.delete(run.runId)
+      return
+    }
+
+    run.conversationId = result.result.conversationId || run.conversationId
+    runtime.onChunk({
+      runId: run.runId,
+      conversationId: run.conversationId,
+      type: 'content',
+      content: result.result.assistantText
+    })
+    runtime.onChunk({
+      runId: run.runId,
+      conversationId: run.conversationId,
+      type: 'done',
+      usage: result.result.usage,
+      isFinished: true
+    })
+    runtime.onFinished?.({ success: true, runId: run.runId, conversationId: run.conversationId })
+    this.runs.delete(run.runId)
+  }
+
+  private async executeSqlMode(
+    run: ActiveAgentRun,
+    payload: AgentRunPayload,
+    runtime: {
+      onChunk: (chunk: AgentStreamChunk) => void
+      onFinished?: (result: { success: boolean; runId: string; conversationId?: string; error?: string }) => void
+    }
+  ): Promise<void> {
+    const { apiBaseUrl, apiKey, model } = this.getSharedModelConfig()
+    if (!apiBaseUrl || !apiKey) {
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: '请先在设置 > AI 通用中配置模型',
+        isFinished: true
+      })
+      runtime.onFinished?.({ success: false, runId: run.runId, conversationId: run.conversationId, error: '模型未配置' })
+      this.runs.delete(run.runId)
+      return
+    }
+    this.emitStatus(run, runtime.onChunk, 'thinking')
+    const schemaText = normalizeText(payload.sqlContext?.schemaText)
+    const targetHint = normalizeText(payload.sqlContext?.targetHint)
+    const systemPrompt = [
+      '你是 WeFlow SQL Lab 助手。',
+      '只输出一段只读 SQL。',
+      '禁止输出解释、Markdown、注释、DML、DDL。'
+    ].join('\n')
+    const userPrompt = [
+      targetHint ? `目标数据源: ${targetHint}` : '',
+      schemaText ? `可用 Schema:\n${schemaText}` : '',
+      `需求: ${normalizeText(payload.userInput)}`
+    ].filter(Boolean).join('\n\n')
+
+    const res = await this.callModel({
+      model,
+      messages: [
+        { role: 'system', content: systemPrompt },
+        { role: 'user', content: userPrompt }
+      ],
+      temperature: 0.1,
+      stream: false
+    }, apiBaseUrl, apiKey)
+
+    if (run.aborted) {
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: '任务已取消',
+        isFinished: true
+      })
+      runtime.onFinished?.({ success: false, runId: run.runId, conversationId: run.conversationId, error: '任务已取消' })
+      this.runs.delete(run.runId)
+      return
+    }
+
+    const rawContent = normalizeText(res?.choices?.[0]?.message?.content)
+    const sql = extractSqlText(rawContent)
+    const usage: TokenUsage = {
+      promptTokens: Number(res?.usage?.prompt_tokens || 0),
+      completionTokens: Number(res?.usage?.completion_tokens || 0),
+      totalTokens: Number(res?.usage?.total_tokens || 0)
+    }
+    if (!sql) {
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'error',
+        error: 'SQL 生成失败',
+        isFinished: true
+      })
+      runtime.onFinished?.({ success: false, runId: run.runId, conversationId: run.conversationId, error: 'SQL 生成失败' })
+      this.runs.delete(run.runId)
+      return
+    }
+    for (let i = 0; i < sql.length; i += 36) {
+      if (run.aborted) break
+      runtime.onChunk({
+        runId: run.runId,
+        conversationId: run.conversationId,
+        type: 'content',
+        content: sql.slice(i, i + 36)
+      })
+    }
+    runtime.onChunk({
+      runId: run.runId,
+      conversationId: run.conversationId,
+      type: 'done',
+      usage,
+      isFinished: true
+    })
+    runtime.onFinished?.({ success: true, runId: run.runId, conversationId: run.conversationId })
+    this.runs.delete(run.runId)
+  }
+
+  async abort(payload: { runId?: string; conversationId?: string }): Promise<{ success: boolean }> {
+    const runId = normalizeText(payload.runId)
+    const conversationId = normalizeText(payload.conversationId)
+    if (runId) {
+      const run = this.runs.get(runId)
+      if (run) {
+        run.aborted = true
+        if (run.mode === 'chat') {
+          await aiAnalysisService.abortRun({ runId: run.innerRunId, conversationId: run.conversationId })
+        }
+      }
+      return { success: true }
+    }
+
+    if (conversationId) {
+      for (const run of this.runs.values()) {
+        if (run.conversationId !== conversationId) continue
+        run.aborted = true
+        if (run.mode === 'chat') {
+          await aiAnalysisService.abortRun({ runId: run.innerRunId, conversationId: run.conversationId })
+        }
+      }
+      return { success: true }
+    }
+    return { success: true }
+  }
+}
+
+export const aiAgentService = new AiAgentService()
+

electron/services/aiAnalysisSkills/base.md

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+你是 WeFlow 的 AI 分析助手。
+
+目标：
+- 精准完成用户在聊天数据上的查询、总结、分析、回忆任务。
+- 优先使用本地工具获取证据，禁止猜测或捏造。
+- 默认输出简洁中文，先给结论，再给关键依据。
+
+工作原则：
+- Token 节约优先：默认只请求必要字段，只有用户明确需要或证据不足时再升级 detailLevel。
+- 先范围后细节：优先定位会话/时间范围，再拉取具体时间轴或消息。
+- 可解释性：最终结论尽量附带来源范围与统计口径。
+- 语音消息不能臆测：必须先拿语音 ID，再点名转写，再总结。
+- 联系人排行题（“谁聊得最多/最常联系”）命中 ai_query_top_contacts 后，必须直接给出“前N名+消息数”。
+- 除非用户明确要求，联系人排行默认不包含群聊和公众号。
+- 用户提到“最近/近期/lately/recent”但未给时间窗时，默认按近30天口径统计并写明口径。
+- 用户提到联系人简称（如“lr”）时，先把它当联系人缩写处理，优先命中个人会话，不要默认落到群聊。
+- 用户问“我和X聊了什么”时必须交付“主题总结”，不要贴原始逐条聊天流水。
+
+Agent执行要求：
+- 用户输入直接进入推理，本地不做关键词分流，你自主决定工具计划。
+- 当用户说“今天凌晨/昨晚/某段时间的聊天”，优先调用 ai_query_time_window_activity。
+- 拿到活跃会话后，调用 ai_query_session_glimpse 对多个会话逐个抽样阅读，不要只读一个会话就停止。
+- 如果初步探索后用户目标仍模糊，主动提出 1 个关键澄清问题继续多轮对话。
+- 仅当你确认任务完成时，输出结束标记 `[[WF_DONE]]`，并紧跟 `<final_answer>...</final_answer>`。
+- 若还未完成，不要输出结束标记，继续调用工具。
+
+语音处理硬规则：
+- 当用户涉及“语音内容”时，先调用 ai_list_voice_messages。
+- 让系统返回候选 ID 后，再调用 ai_transcribe_voice_messages 指定 ID。
+- 未转写成功的语音不可作为事实依据。

electron/services/aiAnalysisSkills/context_compression.md

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+你会收到 conversation_summary（历史压缩摘要）。
+
+使用方式：
+- 默认把摘要作为历史背景，不逐字复述。
+- 若摘要与最近消息冲突，以最近消息为准。
+- 若用户追问很久之前的细节，优先重新调用工具检索，不依赖旧记忆。

electron/services/aiAnalysisSkills/tool_message_briefs.md

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+工具：ai_fetch_message_briefs
+
+何时用：
+- 需要核对少量关键消息原文，避免全量展开。
+
+调用建议：
+- 只传必要 items（sessionId + localId），每次少量（<=20）。
+- 默认 minimal；需要上下文再用 standard/full。

electron/services/aiAnalysisSkills/tool_session_candidates.md

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+工具：ai_query_session_candidates
+
+何时用：
+- 用户未明确具体会话，但给了关键词/关系词（如“老婆”“买车”）。
+
+调用建议：
+- 首次调用 detailLevel=minimal。
+- 默认 limit 8~12，避免拉太多候选。
+- 当候选歧义较大时再升级 detailLevel=standard/full。

electron/services/aiAnalysisSkills/tool_session_glimpse.md

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+工具：ai_query_session_glimpse
+
+何时用：
+- 已确定候选会话，需要“先看一点”理解上下文。
+
+Agent策略：
+- 每个候选会话先抽样 6~20 条，按时间顺序阅读。
+- 不要只读一个会话就结束；优先覆盖多会话后再总结。
+- 如果出现明显分歧场景（工作/家庭/感情）需主动向用户确认分析目标。

electron/services/aiAnalysisSkills/tool_source_refs.md

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+工具：ai_query_source_refs
+
+何时用：
+- 输出总结或分析后，用于来源说明与可解释卡片。
+
+调用建议：
+- 默认 minimal 即可，输出 range/session_count/message_count/db_refs。
+- 只有排错或审计时再请求 full。

electron/services/aiAnalysisSkills/tool_time_window_activity.md

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+工具：ai_query_time_window_activity
+
+何时用：
+- 用户提到“今天凌晨/昨晚/某个时间段”的聊天分析。
+
+Agent策略：
+- 第一步必须先扫时间窗活跃会话，不要直接下结论。
+- 拿到活跃会话后，再调用 ai_query_session_glimpse 逐个会话抽样阅读。
+- 若用户目标仍不清晰，先追问 1 个关键澄清问题再继续。

electron/services/aiAnalysisSkills/tool_timeline.md

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+工具：ai_query_timeline
+
+何时用：
+- 回忆事件经过、梳理时间线、提取关键节点。
+
+调用建议：
+- 默认 detailLevel=minimal。
+- 先小批次 limit（40~120），不够再分页 offset。
+- 需要引用原文证据时，可搭配 ai_fetch_message_briefs。

electron/services/aiAnalysisSkills/tool_top_contacts.md

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+工具：ai_query_top_contacts
+
+何时用：
+- 用户问“谁联系最密切”“谁聊得最多”“最常联系的是谁”。
+
+调用建议：
+- 该问题优先调用本工具，而不是先跑时间轴。
+- 默认 detailLevel=minimal，limit 5~10。
+- 需要区分群聊时再设置 includeGroups=true。

electron/services/aiAnalysisSkills/tool_topic_stats.md

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+工具：ai_query_topic_stats
+
+何时用：
+- 用户问“多少、占比、趋势、对比”。
+
+调用建议：
+- 仅在统计问题时调用，避免无谓聚合。
+- 默认 detailLevel=minimal；有统计追问再升到 standard/full。

electron/services/aiAnalysisSkills/tool_voice_list.md

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+工具：ai_list_voice_messages
+
+何时用：
+- 用户提到“语音里说了什么”。
+
+调用建议：
+- 第一步先拿 ID 清单，默认 detailLevel=minimal（仅 IDs）。
+- 如用户需要挑选依据，再用 standard/full 查看更多元数据。

electron/services/aiAnalysisSkills/tool_voice_transcribe.md

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+工具：ai_transcribe_voice_messages
+
+何时用：
+- 已明确拿到语音 ID，且用户需要读取语音内容。
+
+调用建议：
+- 必须显式传 ids 或 items。
+- 单次控制在小批次（建议 <=5），失败可重试。
+- 转写成功后再参与总结；失败项单独标注，不混入结论。

electron/services/aiAssistantService.ts

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+import { randomUUID } from 'crypto'
+import { existsSync } from 'fs'
+import { mkdir, readdir, readFile, rm, writeFile } from 'fs/promises'
+import { join } from 'path'
+import { ConfigService } from './config'
+
+export type AssistantChatType = 'group' | 'private'
+export type AssistantToolCategory = 'core' | 'analysis'
+
+export interface AssistantSummary {
+  id: string
+  name: string
+  systemPrompt: string
+  presetQuestions: string[]
+  allowedBuiltinTools?: string[]
+  builtinId?: string
+  applicableChatTypes?: AssistantChatType[]
+  supportedLocales?: string[]
+}
+
+export interface AssistantConfigFull extends AssistantSummary {}
+
+export interface BuiltinAssistantInfo {
+  id: string
+  name: string
+  systemPrompt: string
+  applicableChatTypes?: AssistantChatType[]
+  supportedLocales?: string[]
+  imported: boolean
+}
+
+const GENERAL_CN_MD = `---
+id: general_cn
+name: 通用分析助手
+supportedLocales:
+  - zh
+presetQuestions:
+  - 最近都在聊什么？
+  - 谁是最活跃的人？
+  - 帮我总结一下最近一周的重要聊天
+  - 帮我找一下关于“旅游”的讨论
+allowedBuiltinTools:
+  - ai_query_time_window_activity
+  - ai_query_session_candidates
+  - ai_query_session_glimpse
+  - ai_query_timeline
+  - ai_fetch_message_briefs
+  - ai_list_voice_messages
+  - ai_transcribe_voice_messages
+  - ai_query_topic_stats
+  - ai_query_source_refs
+  - ai_query_top_contacts
+---
+
+你是 WeFlow 的全局聊天分析助手。请使用工具获取证据，给出简洁、准确、可执行的结论。
+
+输出要求：
+1. 先结论，再证据。
+2. 若证据不足，明确说明不足并建议下一步。
+3. 涉及语音内容时，必须先列语音 ID，再按 ID 转写。
+4. 默认中文输出，除非用户明确指定其他语言。`
+
+const GENERAL_EN_MD = `---
+id: general_en
+name: General Analysis Assistant
+supportedLocales:
+  - en
+presetQuestions:
+  - What have people been discussing recently?
+  - Who are the most active contacts?
+  - Summarize my key chat topics this week
+allowedBuiltinTools:
+  - ai_query_time_window_activity
+  - ai_query_session_candidates
+  - ai_query_session_glimpse
+  - ai_query_timeline
+  - ai_fetch_message_briefs
+  - ai_list_voice_messages
+  - ai_transcribe_voice_messages
+  - ai_query_topic_stats
+  - ai_query_source_refs
+  - ai_query_top_contacts
+---
+
+You are WeFlow's global chat analysis assistant.
+Always ground your answers in tool evidence, stay concise, and clearly call out uncertainty when data is insufficient.`
+
+const GENERAL_JA_MD = `---
+id: general_ja
+name: 汎用分析アシスタント
+supportedLocales:
+  - ja
+presetQuestions:
+  - 最近どんな話題が多い？
+  - 一番アクティブな相手は誰？
+  - 今週の重要な会話を要約して
+allowedBuiltinTools:
+  - ai_query_time_window_activity
+  - ai_query_session_candidates
+  - ai_query_session_glimpse
+  - ai_query_timeline
+  - ai_fetch_message_briefs
+  - ai_list_voice_messages
+  - ai_transcribe_voice_messages
+  - ai_query_topic_stats
+  - ai_query_source_refs
+  - ai_query_top_contacts
+---
+
+あなたは WeFlow のグローバルチャット分析アシスタントです。
+ツールから得た根拠に基づき、簡潔かつ正確に回答してください。`
+
+const BUILTIN_ASSISTANTS = [
+  { id: 'general_cn', raw: GENERAL_CN_MD },
+  { id: 'general_en', raw: GENERAL_EN_MD },
+  { id: 'general_ja', raw: GENERAL_JA_MD }
+] as const
+
+function normalizeText(value: unknown, fallback = ''): string {
+  const text = String(value ?? '').trim()
+  return text || fallback
+}
+
+function parseInlineList(text: string): string[] {
+  const raw = normalizeText(text)
+  if (!raw) return []
+  return raw
+    .split(',')
+    .map((item) => item.trim())
+    .filter(Boolean)
+}
+
+function splitFrontmatter(raw: string): { frontmatter: string; body: string } {
+  const normalized = String(raw || '')
+  if (!normalized.startsWith('---')) {
+    return { frontmatter: '', body: normalized.trim() }
+  }
+  const end = normalized.indexOf('\n---', 3)
+  if (end < 0) return { frontmatter: '', body: normalized.trim() }
+  return {
+    frontmatter: normalized.slice(3, end).trim(),
+    body: normalized.slice(end + 4).trim()
+  }
+}
+
+function parseAssistantMarkdown(raw: string): AssistantConfigFull {
+  const { frontmatter, body } = splitFrontmatter(raw)
+  const lines = frontmatter ? frontmatter.split('\n') : []
+  const data: Record<string, unknown> = {}
+  let currentArrayKey = ''
+  for (const line of lines) {
+    const trimmed = line.trim()
+    if (!trimmed) continue
+    const kv = trimmed.match(/^([A-Za-z0-9_]+)\s*:\s*(.*)$/)
+    if (kv) {
+      const key = kv[1]
+      const value = kv[2]
+      if (!value) {
+        data[key] = []
+        currentArrayKey = key
+      } else {
+        data[key] = value
+        currentArrayKey = ''
+      }
+      continue
+    }
+    const arr = trimmed.match(/^- (.+)$/)
+    if (arr && currentArrayKey) {
+      const next = Array.isArray(data[currentArrayKey]) ? data[currentArrayKey] as string[] : []
+      next.push(arr[1].trim())
+      data[currentArrayKey] = next
+    }
+  }
+
+  const id = normalizeText(data.id)
+  const name = normalizeText(data.name, id || 'assistant')
+  const applicableChatTypes = Array.isArray(data.applicableChatTypes)
+    ? (data.applicableChatTypes as string[]).filter((item): item is AssistantChatType => item === 'group' || item === 'private')
+    : parseInlineList(String(data.applicableChatTypes || '')).filter((item): item is AssistantChatType => item === 'group' || item === 'private')
+  const supportedLocales = Array.isArray(data.supportedLocales)
+    ? (data.supportedLocales as string[]).map((item) => item.trim()).filter(Boolean)
+    : parseInlineList(String(data.supportedLocales || ''))
+  const presetQuestions = Array.isArray(data.presetQuestions)
+    ? (data.presetQuestions as string[]).map((item) => item.trim()).filter(Boolean)
+    : parseInlineList(String(data.presetQuestions || ''))
+  const allowedBuiltinTools = Array.isArray(data.allowedBuiltinTools)
+    ? (data.allowedBuiltinTools as string[]).map((item) => item.trim()).filter(Boolean)
+    : parseInlineList(String(data.allowedBuiltinTools || ''))
+  const builtinId = normalizeText(data.builtinId)
+
+  return {
+    id,
+    name,
+    systemPrompt: body,
+    presetQuestions,
+    allowedBuiltinTools,
+    builtinId: builtinId || undefined,
+    applicableChatTypes,
+    supportedLocales
+  }
+}
+
+function toMarkdown(config: AssistantConfigFull): string {
+  const lines = [
+    '---',
+    `id: ${config.id}`,
+    `name: ${config.name}`
+  ]
+  if (config.builtinId) lines.push(`builtinId: ${config.builtinId}`)
+  if (config.supportedLocales && config.supportedLocales.length > 0) {
+    lines.push('supportedLocales:')
+    config.supportedLocales.forEach((item) => lines.push(`  - ${item}`))
+  }
+  if (config.applicableChatTypes && config.applicableChatTypes.length > 0) {
+    lines.push('applicableChatTypes:')
+    config.applicableChatTypes.forEach((item) => lines.push(`  - ${item}`))
+  }
+  if (config.presetQuestions && config.presetQuestions.length > 0) {
+    lines.push('presetQuestions:')
+    config.presetQuestions.forEach((item) => lines.push(`  - ${item}`))
+  }
+  if (config.allowedBuiltinTools && config.allowedBuiltinTools.length > 0) {
+    lines.push('allowedBuiltinTools:')
+    config.allowedBuiltinTools.forEach((item) => lines.push(`  - ${item}`))
+  }
+  lines.push('---')
+  lines.push('')
+  lines.push(config.systemPrompt || '')
+  return lines.join('\n')
+}
+
+function defaultBuiltinToolCatalog(): Array<{ name: string; category: AssistantToolCategory }> {
+  return [
+    { name: 'ai_query_time_window_activity', category: 'core' },
+    { name: 'ai_query_session_candidates', category: 'core' },
+    { name: 'ai_query_session_glimpse', category: 'core' },
+    { name: 'ai_query_timeline', category: 'core' },
+    { name: 'ai_fetch_message_briefs', category: 'core' },
+    { name: 'ai_list_voice_messages', category: 'core' },
+    { name: 'ai_transcribe_voice_messages', category: 'core' },
+    { name: 'ai_query_topic_stats', category: 'analysis' },
+    { name: 'ai_query_source_refs', category: 'analysis' },
+    { name: 'ai_query_top_contacts', category: 'analysis' },
+    { name: 'activate_skill', category: 'analysis' }
+  ]
+}
+
+class AiAssistantService {
+  private readonly config = ConfigService.getInstance()
+  private initialized = false
+  private readonly cache = new Map<string, AssistantConfigFull>()
+
+  private getRootDirCandidates(): string[] {
+    const dbPath = normalizeText(this.config.get('dbPath'))
+    const wxid = normalizeText(this.config.get('myWxid'))
+    const roots: string[] = []
+    if (dbPath && wxid) {
+      roots.push(join(dbPath, wxid, 'db_storage', 'wf_ai_v2'))
+      roots.push(join(dbPath, wxid, 'db_storage', 'wf_ai'))
+    }
+    roots.push(join(process.cwd(), 'data', 'wf_ai_v2'))
+    return roots
+  }
+
+  private async getRootDir(): Promise<string> {
+    const roots = this.getRootDirCandidates()
+    const dir = roots[0]
+    await mkdir(dir, { recursive: true })
+    return dir
+  }
+
+  private async getAssistantsDir(): Promise<string> {
+    const root = await this.getRootDir()
+    const dir = join(root, 'assistants')
+    await mkdir(dir, { recursive: true })
+    return dir
+  }
+
+  private async ensureInitialized(): Promise<void> {
+    if (this.initialized) return
+    const dir = await this.getAssistantsDir()
+
+    for (const builtin of BUILTIN_ASSISTANTS) {
+      const filePath = join(dir, `${builtin.id}.md`)
+      if (!existsSync(filePath)) {
+        const parsed = parseAssistantMarkdown(builtin.raw)
+        const config: AssistantConfigFull = {
+          ...parsed,
+          builtinId: parsed.id
+        }
+        await writeFile(filePath, toMarkdown(config), 'utf8')
+      }
+    }
+
+    this.cache.clear()
+    const files = await readdir(dir)
+    for (const fileName of files) {
+      if (!fileName.endsWith('.md')) continue
+      const filePath = join(dir, fileName)
+      try {
+        const raw = await readFile(filePath, 'utf8')
+        const parsed = parseAssistantMarkdown(raw)
+        if (!parsed.id) continue
+        this.cache.set(parsed.id, parsed)
+      } catch {
+        // ignore broken file
+      }
+    }
+    this.initialized = true
+  }
+
+  async getAll(): Promise<AssistantSummary[]> {
+    await this.ensureInitialized()
+    return Array.from(this.cache.values())
+      .sort((a, b) => a.name.localeCompare(b.name, 'zh-Hans-CN'))
+      .map((assistant) => ({ ...assistant }))
+  }
+
+  async getConfig(id: string): Promise<AssistantConfigFull | null> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const config = this.cache.get(key)
+    return config ? { ...config } : null
+  }
+
+  async create(
+    payload: Omit<AssistantConfigFull, 'id'> & { id?: string }
+  ): Promise<{ success: boolean; id?: string; error?: string }> {
+    await this.ensureInitialized()
+    const id = normalizeText(payload.id, `custom_${randomUUID().replace(/-/g, '').slice(0, 12)}`)
+    if (this.cache.has(id)) return { success: false, error: '助手 ID 已存在' }
+    const config: AssistantConfigFull = {
+      id,
+      name: normalizeText(payload.name, '新助手'),
+      systemPrompt: normalizeText(payload.systemPrompt),
+      presetQuestions: Array.isArray(payload.presetQuestions) ? payload.presetQuestions.map((item) => normalizeText(item)).filter(Boolean) : [],
+      allowedBuiltinTools: Array.isArray(payload.allowedBuiltinTools) ? payload.allowedBuiltinTools.map((item) => normalizeText(item)).filter(Boolean) : [],
+      builtinId: normalizeText(payload.builtinId) || undefined,
+      applicableChatTypes: Array.isArray(payload.applicableChatTypes) ? payload.applicableChatTypes : [],
+      supportedLocales: Array.isArray(payload.supportedLocales) ? payload.supportedLocales.map((item) => normalizeText(item)).filter(Boolean) : []
+    }
+    const dir = await this.getAssistantsDir()
+    await writeFile(join(dir, `${id}.md`), toMarkdown(config), 'utf8')
+    this.cache.set(id, config)
+    return { success: true, id }
+  }
+
+  async update(
+    id: string,
+    updates: Partial<AssistantConfigFull>
+  ): Promise<{ success: boolean; error?: string }> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const existing = this.cache.get(key)
+    if (!existing) return { success: false, error: '助手不存在' }
+    const next: AssistantConfigFull = {
+      ...existing,
+      ...updates,
+      id: key,
+      name: normalizeText(updates.name, existing.name),
+      systemPrompt: updates.systemPrompt == null ? existing.systemPrompt : normalizeText(updates.systemPrompt),
+      presetQuestions: Array.isArray(updates.presetQuestions) ? updates.presetQuestions.map((item) => normalizeText(item)).filter(Boolean) : existing.presetQuestions,
+      allowedBuiltinTools: Array.isArray(updates.allowedBuiltinTools) ? updates.allowedBuiltinTools.map((item) => normalizeText(item)).filter(Boolean) : existing.allowedBuiltinTools,
+      applicableChatTypes: Array.isArray(updates.applicableChatTypes) ? updates.applicableChatTypes : existing.applicableChatTypes,
+      supportedLocales: Array.isArray(updates.supportedLocales) ? updates.supportedLocales.map((item) => normalizeText(item)).filter(Boolean) : existing.supportedLocales
+    }
+    const dir = await this.getAssistantsDir()
+    await writeFile(join(dir, `${key}.md`), toMarkdown(next), 'utf8')
+    this.cache.set(key, next)
+    return { success: true }
+  }
+
+  async delete(id: string): Promise<{ success: boolean; error?: string }> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    if (key === 'general_cn' || key === 'general_en' || key === 'general_ja') {
+      return { success: false, error: '默认助手不可删除' }
+    }
+    const dir = await this.getAssistantsDir()
+    const filePath = join(dir, `${key}.md`)
+    if (existsSync(filePath)) {
+      await rm(filePath, { force: true })
+    }
+    this.cache.delete(key)
+    return { success: true }
+  }
+
+  async reset(id: string): Promise<{ success: boolean; error?: string }> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const existing = this.cache.get(key)
+    if (!existing?.builtinId) {
+      return { success: false, error: '该助手不支持重置' }
+    }
+    const builtin = BUILTIN_ASSISTANTS.find((item) => item.id === existing.builtinId)
+    if (!builtin) return { success: false, error: '内置模板不存在' }
+    const parsed = parseAssistantMarkdown(builtin.raw)
+    const config: AssistantConfigFull = {
+      ...parsed,
+      id: key,
+      builtinId: existing.builtinId
+    }
+    const dir = await this.getAssistantsDir()
+    await writeFile(join(dir, `${key}.md`), toMarkdown(config), 'utf8')
+    this.cache.set(key, config)
+    return { success: true }
+  }
+
+  async getBuiltinCatalog(): Promise<BuiltinAssistantInfo[]> {
+    await this.ensureInitialized()
+    return BUILTIN_ASSISTANTS.map((builtin) => {
+      const parsed = parseAssistantMarkdown(builtin.raw)
+      const imported = Array.from(this.cache.values()).some((config) => config.builtinId === builtin.id || config.id === builtin.id)
+      return {
+        id: parsed.id,
+        name: parsed.name,
+        systemPrompt: parsed.systemPrompt,
+        applicableChatTypes: parsed.applicableChatTypes,
+        supportedLocales: parsed.supportedLocales,
+        imported
+      }
+    })
+  }
+
+  async getBuiltinToolCatalog(): Promise<Array<{ name: string; category: AssistantToolCategory }>> {
+    return defaultBuiltinToolCatalog()
+  }
+
+  async importFromMd(rawMd: string): Promise<{ success: boolean; id?: string; error?: string }> {
+    try {
+      const parsed = parseAssistantMarkdown(rawMd)
+      if (!parsed.id) return { success: false, error: '缺少 id' }
+      if (this.cache.has(parsed.id)) return { success: false, error: '助手 ID 已存在' }
+      const dir = await this.getAssistantsDir()
+      await writeFile(join(dir, `${parsed.id}.md`), toMarkdown(parsed), 'utf8')
+      this.cache.set(parsed.id, parsed)
+      return { success: true, id: parsed.id }
+    } catch (error) {
+      return { success: false, error: String((error as Error)?.message || error) }
+    }
+  }
+}
+
+export const aiAssistantService = new AiAssistantService()

electron/services/aiSkillService.ts

@@ -0,0 +1,395 @@
+import { existsSync } from 'fs'
+import { mkdir, readdir, readFile, rm, writeFile } from 'fs/promises'
+import { join } from 'path'
+import { ConfigService } from './config'
+
+export type SkillChatScope = 'all' | 'group' | 'private'
+
+export interface SkillSummary {
+  id: string
+  name: string
+  description: string
+  tags: string[]
+  chatScope: SkillChatScope
+  tools: string[]
+  builtinId?: string
+}
+
+export interface SkillDef extends SkillSummary {
+  prompt: string
+}
+
+export interface BuiltinSkillInfo extends SkillSummary {
+  imported: boolean
+}
+
+const SKILL_DEEP_TIMELINE_MD = `---
+id: deep_timeline
+name: 深度时间线追踪
+description: 适合还原某段时间内发生了什么，强调事件顺序与证据引用。
+tags:
+  - timeline
+  - evidence
+chatScope: all
+tools:
+  - ai_query_time_window_activity
+  - ai_query_session_candidates
+  - ai_query_session_glimpse
+  - ai_query_timeline
+  - ai_fetch_message_briefs
+  - ai_query_source_refs
+---
+你是“深度时间线追踪”技能。
+执行步骤：
+1. 先按时间窗扫描活跃会话，必要时补关键词筛选候选会话。
+2. 对候选会话先抽样，再拉取时间轴。
+3. 对关键节点用 ai_fetch_message_briefs 校对原文。
+4. 最后输出“结论 + 关键节点 + 来源范围”。`
+
+const SKILL_CONTACT_FOCUS_MD = `---
+id: contact_focus
+name: 联系人关系聚焦
+description: 用于“我和谁聊得最多/关系变化”这类问题，强调联系人维度。
+tags:
+  - contacts
+  - relation
+chatScope: private
+tools:
+  - ai_query_top_contacts
+  - ai_query_topic_stats
+  - ai_query_session_glimpse
+  - ai_query_timeline
+  - ai_query_source_refs
+---
+你是“联系人关系聚焦”技能。
+执行步骤：
+1. 优先调用 ai_query_top_contacts 得到候选联系人排名。
+2. 针对 Top 联系人读取抽样消息并补充时间轴。
+3. 如果用户问题涉及“变化趋势”，补 ai_query_topic_stats。
+4. 输出时必须给出对比口径（时间窗、样本范围、消息数量）。`
+
+const SKILL_VOICE_AUDIT_MD = `---
+id: voice_audit
+name: 语音证据审计
+description: 对语音消息进行“先列ID再转写再总结”的合规分析。
+tags:
+  - voice
+  - audit
+chatScope: all
+tools:
+  - ai_list_voice_messages
+  - ai_transcribe_voice_messages
+  - ai_query_source_refs
+---
+你是“语音证据审计”技能。
+硬规则：
+1. 必须先调用 ai_list_voice_messages 获取语音 ID 清单。
+2. 仅能转写用户明确指定的 ID，单轮最多 5 条。
+3. 未转写成功的语音不得作为事实。
+4. 输出包含“已转写 / 失败 / 待确认”三段。`
+
+const BUILTIN_SKILLS = [
+  { id: 'deep_timeline', raw: SKILL_DEEP_TIMELINE_MD },
+  { id: 'contact_focus', raw: SKILL_CONTACT_FOCUS_MD },
+  { id: 'voice_audit', raw: SKILL_VOICE_AUDIT_MD }
+] as const
+
+function normalizeText(value: unknown, fallback = ''): string {
+  const text = String(value ?? '').trim()
+  return text || fallback
+}
+
+function parseInlineList(text: string): string[] {
+  const raw = normalizeText(text)
+  if (!raw) return []
+  return raw
+    .split(',')
+    .map((item) => item.trim())
+    .filter(Boolean)
+}
+
+function splitFrontmatter(raw: string): { frontmatter: string; body: string } {
+  const normalized = String(raw || '')
+  if (!normalized.startsWith('---')) {
+    return { frontmatter: '', body: normalized.trim() }
+  }
+  const end = normalized.indexOf('\n---', 3)
+  if (end < 0) return { frontmatter: '', body: normalized.trim() }
+  return {
+    frontmatter: normalized.slice(3, end).trim(),
+    body: normalized.slice(end + 4).trim()
+  }
+}
+
+function normalizeChatScope(value: unknown): SkillChatScope {
+  const scope = normalizeText(value).toLowerCase()
+  if (scope === 'group' || scope === 'private') return scope
+  return 'all'
+}
+
+function parseSkillMarkdown(raw: string): SkillDef {
+  const { frontmatter, body } = splitFrontmatter(raw)
+  const lines = frontmatter ? frontmatter.split('\n') : []
+  const data: Record<string, unknown> = {}
+  let currentArrayKey = ''
+  for (const line of lines) {
+    const trimmed = line.trim()
+    if (!trimmed) continue
+    const kv = trimmed.match(/^([A-Za-z0-9_]+)\s*:\s*(.*)$/)
+    if (kv) {
+      const key = kv[1]
+      const value = kv[2]
+      if (!value) {
+        data[key] = []
+        currentArrayKey = key
+      } else {
+        data[key] = value
+        currentArrayKey = ''
+      }
+      continue
+    }
+    const arr = trimmed.match(/^- (.+)$/)
+    if (arr && currentArrayKey) {
+      const next = Array.isArray(data[currentArrayKey]) ? data[currentArrayKey] as string[] : []
+      next.push(arr[1].trim())
+      data[currentArrayKey] = next
+    }
+  }
+
+  const id = normalizeText(data.id)
+  const name = normalizeText(data.name, id || 'skill')
+  const description = normalizeText(data.description)
+  const tags = Array.isArray(data.tags)
+    ? (data.tags as string[]).map((item) => item.trim()).filter(Boolean)
+    : parseInlineList(String(data.tags || ''))
+  const tools = Array.isArray(data.tools)
+    ? (data.tools as string[]).map((item) => item.trim()).filter(Boolean)
+    : parseInlineList(String(data.tools || ''))
+  const chatScope = normalizeChatScope(data.chatScope)
+  const builtinId = normalizeText(data.builtinId)
+
+  return {
+    id,
+    name,
+    description,
+    tags,
+    chatScope,
+    tools,
+    prompt: body,
+    builtinId: builtinId || undefined
+  }
+}
+
+function serializeSkillMarkdown(skill: SkillDef): string {
+  const lines = [
+    '---',
+    `id: ${skill.id}`,
+    `name: ${skill.name}`,
+    `description: ${skill.description}`,
+    `chatScope: ${skill.chatScope}`
+  ]
+  if (skill.builtinId) lines.push(`builtinId: ${skill.builtinId}`)
+  if (skill.tags.length > 0) {
+    lines.push('tags:')
+    skill.tags.forEach((tag) => lines.push(`  - ${tag}`))
+  }
+  if (skill.tools.length > 0) {
+    lines.push('tools:')
+    skill.tools.forEach((tool) => lines.push(`  - ${tool}`))
+  }
+  lines.push('---')
+  lines.push('')
+  lines.push(skill.prompt || '')
+  return lines.join('\n')
+}
+
+class AiSkillService {
+  private readonly config = ConfigService.getInstance()
+  private initialized = false
+  private readonly cache = new Map<string, SkillDef>()
+
+  private getRootDirCandidates(): string[] {
+    const dbPath = normalizeText(this.config.get('dbPath'))
+    const wxid = normalizeText(this.config.get('myWxid'))
+    const roots: string[] = []
+    if (dbPath && wxid) {
+      roots.push(join(dbPath, wxid, 'db_storage', 'wf_ai_v2'))
+      roots.push(join(dbPath, wxid, 'db_storage', 'wf_ai'))
+    }
+    roots.push(join(process.cwd(), 'data', 'wf_ai_v2'))
+    return roots
+  }
+
+  private async getRootDir(): Promise<string> {
+    const roots = this.getRootDirCandidates()
+    const dir = roots[0]
+    await mkdir(dir, { recursive: true })
+    return dir
+  }
+
+  private async getSkillsDir(): Promise<string> {
+    const root = await this.getRootDir()
+    const dir = join(root, 'skills')
+    await mkdir(dir, { recursive: true })
+    return dir
+  }
+
+  private async ensureInitialized(): Promise<void> {
+    if (this.initialized) return
+    const dir = await this.getSkillsDir()
+
+    for (const builtin of BUILTIN_SKILLS) {
+      const filePath = join(dir, `${builtin.id}.md`)
+      if (!existsSync(filePath)) {
+        const parsed = parseSkillMarkdown(builtin.raw)
+        const config: SkillDef = {
+          ...parsed,
+          builtinId: parsed.id
+        }
+        await writeFile(filePath, serializeSkillMarkdown(config), 'utf8')
+        continue
+      }
+      try {
+        const raw = await readFile(filePath, 'utf8')
+        const parsed = parseSkillMarkdown(raw)
+        if (!parsed.builtinId) {
+          parsed.builtinId = builtin.id
+          await writeFile(filePath, serializeSkillMarkdown(parsed), 'utf8')
+        }
+      } catch {
+        // ignore broken file
+      }
+    }
+
+    this.cache.clear()
+    const files = await readdir(dir)
+    for (const fileName of files) {
+      if (!fileName.endsWith('.md')) continue
+      const filePath = join(dir, fileName)
+      try {
+        const raw = await readFile(filePath, 'utf8')
+        const parsed = parseSkillMarkdown(raw)
+        if (!parsed.id) continue
+        this.cache.set(parsed.id, parsed)
+      } catch {
+        // ignore broken file
+      }
+    }
+    this.initialized = true
+  }
+
+  async getAll(): Promise<SkillSummary[]> {
+    await this.ensureInitialized()
+    return Array.from(this.cache.values())
+      .sort((a, b) => a.name.localeCompare(b.name, 'zh-Hans-CN'))
+      .map((skill) => ({
+        id: skill.id,
+        name: skill.name,
+        description: skill.description,
+        tags: [...skill.tags],
+        chatScope: skill.chatScope,
+        tools: [...skill.tools],
+        builtinId: skill.builtinId
+      }))
+  }
+
+  async getConfig(id: string): Promise<SkillDef | null> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const value = this.cache.get(key)
+    return value ? {
+      ...value,
+      tags: [...value.tags],
+      tools: [...value.tools]
+    } : null
+  }
+
+  async create(rawMd: string): Promise<{ success: boolean; id?: string; error?: string }> {
+    await this.ensureInitialized()
+    try {
+      const parsed = parseSkillMarkdown(rawMd)
+      if (!parsed.id) return { success: false, error: '缺少 id' }
+      if (this.cache.has(parsed.id)) return { success: false, error: '技能 ID 已存在' }
+      const dir = await this.getSkillsDir()
+      await writeFile(join(dir, `${parsed.id}.md`), serializeSkillMarkdown(parsed), 'utf8')
+      this.cache.set(parsed.id, parsed)
+      return { success: true, id: parsed.id }
+    } catch (error) {
+      return { success: false, error: String((error as Error)?.message || error) }
+    }
+  }
+
+  async update(id: string, rawMd: string): Promise<{ success: boolean; error?: string }> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const existing = this.cache.get(key)
+    if (!existing) return { success: false, error: '技能不存在' }
+    try {
+      const parsed = parseSkillMarkdown(rawMd)
+      parsed.id = key
+      if (existing.builtinId && !parsed.builtinId) parsed.builtinId = existing.builtinId
+      const dir = await this.getSkillsDir()
+      await writeFile(join(dir, `${key}.md`), serializeSkillMarkdown(parsed), 'utf8')
+      this.cache.set(key, parsed)
+      return { success: true }
+    } catch (error) {
+      return { success: false, error: String((error as Error)?.message || error) }
+    }
+  }
+
+  async delete(id: string): Promise<{ success: boolean; error?: string }> {
+    await this.ensureInitialized()
+    const key = normalizeText(id)
+    const dir = await this.getSkillsDir()
+    const filePath = join(dir, `${key}.md`)
+    if (existsSync(filePath)) {
+      await rm(filePath, { force: true })
+    }
+    this.cache.delete(key)
+    return { success: true }
+  }
+
+  async getBuiltinCatalog(): Promise<BuiltinSkillInfo[]> {
+    await this.ensureInitialized()
+    return BUILTIN_SKILLS.map((builtin) => {
+      const parsed = parseSkillMarkdown(builtin.raw)
+      const imported = Array.from(this.cache.values()).some((skill) => skill.builtinId === parsed.id || skill.id === parsed.id)
+      return {
+        id: parsed.id,
+        name: parsed.name,
+        description: parsed.description,
+        tags: parsed.tags,
+        chatScope: parsed.chatScope,
+        tools: parsed.tools,
+        imported
+      }
+    })
+  }
+
+  async importFromMd(rawMd: string): Promise<{ success: boolean; id?: string; error?: string }> {
+    return this.create(rawMd)
+  }
+
+  async getAutoSkillMenu(
+    chatScope: SkillChatScope,
+    allowedTools?: string[]
+  ): Promise<string | null> {
+    await this.ensureInitialized()
+    const compatible = Array.from(this.cache.values()).filter((skill) => {
+      if (skill.chatScope !== 'all' && skill.chatScope !== chatScope) return false
+      if (!allowedTools || allowedTools.length === 0) return true
+      return skill.tools.every((tool) => allowedTools.includes(tool))
+    })
+    if (compatible.length === 0) return null
+    const lines = compatible.slice(0, 15).map((skill) => `- ${skill.id}: ${skill.name} - ${skill.description}`)
+    return [
+      '你可以按需调用工具 activate_skill 以激活对应技能。',
+      '当用户问题明显匹配某个技能时，先调用 activate_skill 获取执行手册。',
+      '若问题简单或不匹配技能，可直接回答。',
+      '',
+      ...lines
+    ].join('\n')
+  }
+}
+
+export const aiSkillService = new AiSkillService()

electron/services/config.ts

@@ -74,6 +74,16 @@ interface ConfigSchema {
   aiModelApiBaseUrl: string
   aiModelApiKey: string
   aiModelApiModel: string
+  aiAgentMaxMessagesPerRequest: number
+  aiAgentMaxHistoryRounds: number
+  aiAgentEnableAutoSkill: boolean
+  aiAgentSearchContextBefore: number
+  aiAgentSearchContextAfter: number
+  aiAgentPreprocessClean: boolean
+  aiAgentPreprocessMerge: boolean
+  aiAgentPreprocessDenoise: boolean
+  aiAgentPreprocessDesensitize: boolean
+  aiAgentPreprocessAnonymize: boolean
   aiInsightEnabled: boolean
   aiInsightApiBaseUrl: string
   aiInsightApiKey: string
@@ -184,6 +194,16 @@ export class ConfigService {
       aiModelApiBaseUrl: '',
       aiModelApiKey: '',
       aiModelApiModel: 'gpt-4o-mini',
+      aiAgentMaxMessagesPerRequest: 120,
+      aiAgentMaxHistoryRounds: 12,
+      aiAgentEnableAutoSkill: true,
+      aiAgentSearchContextBefore: 3,
+      aiAgentSearchContextAfter: 3,
+      aiAgentPreprocessClean: true,
+      aiAgentPreprocessMerge: true,
+      aiAgentPreprocessDenoise: true,
+      aiAgentPreprocessDesensitize: false,
+      aiAgentPreprocessAnonymize: false,
       aiInsightEnabled: false,
       aiInsightApiBaseUrl: '',
       aiInsightApiKey: '',

electron/services/wcdbCore.ts

@@ -85,6 +85,10 @@ export class WcdbCore {
   private wcdbScanMediaStream: any = null
   private wcdbGetHeadImageBuffers: any = null
   private wcdbSearchMessages: any = null
+  private wcdbAiQuerySessionCandidates: any = null
+  private wcdbAiQueryTimeline: any = null
+  private wcdbAiQueryTopicStats: any = null
+  private wcdbAiQuerySourceRefs: any = null
   private wcdbGetSnsTimeline: any = null
   private wcdbGetSnsAnnualStats: any = null
   private wcdbGetSnsUsernames: any = null
@@ -1060,6 +1064,26 @@ export class WcdbCore {
       } catch {
         this.wcdbSearchMessages = null
       }
+      try {
+        this.wcdbAiQuerySessionCandidates = this.lib.func('int32 wcdb_ai_query_session_candidates(int64 handle, const char* optionsJson, _Out_ void** outJson)')
+      } catch {
+        this.wcdbAiQuerySessionCandidates = null
+      }
+      try {
+        this.wcdbAiQueryTimeline = this.lib.func('int32 wcdb_ai_query_timeline(int64 handle, const char* optionsJson, _Out_ void** outJson)')
+      } catch {
+        this.wcdbAiQueryTimeline = null
+      }
+      try {
+        this.wcdbAiQueryTopicStats = this.lib.func('int32 wcdb_ai_query_topic_stats(int64 handle, const char* optionsJson, _Out_ void** outJson)')
+      } catch {
+        this.wcdbAiQueryTopicStats = null
+      }
+      try {
+        this.wcdbAiQuerySourceRefs = this.lib.func('int32 wcdb_ai_query_source_refs(int64 handle, const char* optionsJson, _Out_ void** outJson)')
+      } catch {
+        this.wcdbAiQuerySourceRefs = null
+      }
 
       // wcdb_status wcdb_get_sns_timeline(wcdb_handle handle, int32_t limit, int32_t offset, const char* username, const char* keyword, int32_t start_time, int32_t end_time, char** out_json)
       try {
@@ -3370,6 +3394,204 @@ export class WcdbCore {
     }
   }
 
+  private normalizeSqlIdentifier(name: string): string {
+    return `"${String(name || '').replace(/"/g, '""')}"`
+  }
+
+  private stripSqlComments(sql: string): string {
+    return String(sql || '')
+      .replace(/\/\*[\s\S]*?\*\//g, ' ')
+      .replace(/--[^\n\r]*/g, ' ')
+      .trim()
+  }
+
+  private isSqlLabReadOnly(sql: string): boolean {
+    const normalized = this.stripSqlComments(sql).trim()
+    if (!normalized) return false
+    if (normalized.includes('\u0000')) return false
+    const hasMultipleStatements = /;[\s\r\n]*\S/.test(normalized)
+    if (hasMultipleStatements) return false
+    const lower = normalized.toLowerCase()
+    if (/(insert|update|delete|drop|alter|create|attach|detach|replace|truncate|reindex|vacuum|analyze|begin|commit|rollback|savepoint|release)\b/.test(lower)) {
+      return false
+    }
+    if (/pragma\s+.*(writable_schema|journal_mode|locking_mode|foreign_keys)\s*=/.test(lower)) {
+      return false
+    }
+    return /^(select|with|pragma|explain)\b/.test(lower)
+  }
+
+  private async sqlLabListTablesForSource(
+    kind: 'message' | 'contact' | 'biz',
+    path: string | null,
+    maxTables: number = 60,
+    maxColumns: number = 120
+  ): Promise<Array<{ name: string; columns: string[] }>> {
+    const tableRows = await this.execQuery(
+      kind,
+      path,
+      `SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%' ORDER BY name LIMIT ${Math.max(1, maxTables)}`
+    )
+    if (!tableRows.success || !Array.isArray(tableRows.rows)) return []
+
+    const tables: Array<{ name: string; columns: string[] }> = []
+    for (const row of tableRows.rows) {
+      const tableName = String((row as any)?.name || '').trim()
+      if (!tableName) continue
+      const pragma = await this.execQuery(kind, path, `PRAGMA table_info(${this.normalizeSqlIdentifier(tableName)})`)
+      const columns = pragma.success && Array.isArray(pragma.rows)
+        ? pragma.rows
+            .map((item: any) => String(item?.name || '').trim())
+            .filter(Boolean)
+            .slice(0, maxColumns)
+        : []
+      tables.push({ name: tableName, columns })
+    }
+
+    return tables
+  }
+
+  async sqlLabGetSchema(payload?: { sessionId?: string }): Promise<{
+    success: boolean
+    schema?: {
+      generatedAt: number
+      sources: Array<{
+        kind: 'message' | 'contact' | 'biz'
+        path: string | null
+        label: string
+        tables: Array<{ name: string; columns: string[] }>
+      }>
+    }
+    schemaText?: string
+    error?: string
+  }> {
+    if (!this.ensureReady()) {
+      return { success: false, error: 'WCDB 未连接' }
+    }
+
+    try {
+      const sessionId = String(payload?.sessionId || '').trim()
+      const sources: Array<{
+        kind: 'message' | 'contact' | 'biz'
+        path: string | null
+        label: string
+        tables: Array<{ name: string; columns: string[] }>
+      }> = []
+
+      if (sessionId) {
+        const tableStats = await this.getMessageTableStats(sessionId)
+        const tableEntries = tableStats.success && Array.isArray(tableStats.tables) ? tableStats.tables : []
+        const dbPathSet = new Set<string>()
+        for (const entry of tableEntries) {
+          const dbPath = String((entry as any)?.db_path || '').trim()
+          if (!dbPath) continue
+          dbPathSet.add(dbPath)
+        }
+        for (const dbPath of Array.from(dbPathSet).slice(0, 8)) {
+          sources.push({
+            kind: 'message',
+            path: dbPath,
+            label: dbPath.split(/[\\/]/).pop() || dbPath,
+            tables: await this.sqlLabListTablesForSource('message', dbPath)
+          })
+        }
+      } else {
+        const messageDbs = await this.listMessageDbs()
+        const paths = messageDbs.success && Array.isArray(messageDbs.data) ? messageDbs.data : []
+        for (const dbPath of paths.slice(0, 8)) {
+          sources.push({
+            kind: 'message',
+            path: dbPath,
+            label: dbPath.split(/[\\/]/).pop() || dbPath,
+            tables: await this.sqlLabListTablesForSource('message', dbPath)
+          })
+        }
+      }
+
+      sources.push({
+        kind: 'contact',
+        path: null,
+        label: 'contact',
+        tables: await this.sqlLabListTablesForSource('contact', null)
+      })
+      sources.push({
+        kind: 'biz',
+        path: null,
+        label: 'biz',
+        tables: await this.sqlLabListTablesForSource('biz', null)
+      })
+
+      const schemaText = sources
+        .map((source) => {
+          const tableLines = source.tables
+            .map((table) => `- ${table.name} (${table.columns.join(', ')})`)
+            .join('\n')
+          return `[${source.kind}] ${source.label}\n${tableLines}`
+        })
+        .join('\n\n')
+
+      return {
+        success: true,
+        schema: {
+          generatedAt: Date.now(),
+          sources
+        },
+        schemaText
+      }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
+  async sqlLabExecuteReadonly(payload: {
+    kind: 'message' | 'contact' | 'biz'
+    path?: string | null
+    sql: string
+    limit?: number
+  }): Promise<{
+    success: boolean
+    rows?: any[]
+    columns?: string[]
+    total?: number
+    error?: string
+  }> {
+    if (!this.ensureReady()) {
+      return { success: false, error: 'WCDB 未连接' }
+    }
+
+    try {
+      const sql = String(payload?.sql || '').trim()
+      if (!this.isSqlLabReadOnly(sql)) {
+        return { success: false, error: '仅允许只读 SQL（SELECT/WITH/PRAGMA/EXPLAIN）' }
+      }
+
+      const kind = payload?.kind === 'contact' || payload?.kind === 'biz' ? payload.kind : 'message'
+      const path = kind === 'message'
+        ? (payload?.path == null ? null : String(payload.path))
+        : null
+      const limit = Math.max(1, Math.min(1000, Number(payload?.limit || 200)))
+      const sqlNoTail = sql.replace(/;+\s*$/, '')
+      const lower = sqlNoTail.toLowerCase()
+      const executable = /^(select|with)\b/.test(lower)
+        ? `SELECT * FROM (${sqlNoTail}) LIMIT ${limit}`
+        : sqlNoTail
+
+      const result = await this.execQuery(kind, path, executable)
+      if (!result.success) {
+        return { success: false, error: result.error || '执行 SQL 失败' }
+      }
+      const rows = Array.isArray(result.rows) ? result.rows : []
+      return {
+        success: true,
+        rows,
+        columns: rows[0] && typeof rows[0] === 'object' ? Object.keys(rows[0] as Record<string, unknown>) : [],
+        total: rows.length
+      }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
   async execQuery(kind: string, path: string | null, sql: string, params: any[] = []): Promise<{ success: boolean; rows?: any[]; error?: string }> {
     if (!this.ensureReady()) {
       return { success: false, error: 'WCDB 未连接' }
@@ -3979,6 +4201,110 @@ export class WcdbCore {
     }
   }
 
+  async aiQuerySessionCandidates(options: {
+    keyword: string
+    limit?: number
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; rows?: any[]; error?: string }> {
+    if (!this.ensureReady()) return { success: false, error: 'WCDB 未连接' }
+    if (!this.wcdbAiQuerySessionCandidates) return { success: false, error: '当前数据服务版本不支持 AI 候选会话查询' }
+    try {
+      const outPtr = [null as any]
+      const result = this.wcdbAiQuerySessionCandidates(this.handle, JSON.stringify({
+        keyword: options.keyword || '',
+        limit: options.limit || 12,
+        begin_timestamp: options.beginTimestamp || 0,
+        end_timestamp: options.endTimestamp || 0
+      }), outPtr)
+      if (result !== 0 || !outPtr[0]) return { success: false, error: `AI 候选会话查询失败: ${result}` }
+      const jsonStr = this.decodeJsonPtr(outPtr[0])
+      if (!jsonStr) return { success: false, error: '解析 AI 候选会话结果失败' }
+      const rows = JSON.parse(jsonStr)
+      return { success: true, rows: Array.isArray(rows) ? rows : [] }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
+  async aiQueryTimeline(options: {
+    sessionId?: string
+    keyword: string
+    limit?: number
+    offset?: number
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; rows?: any[]; error?: string }> {
+    if (!this.ensureReady()) return { success: false, error: 'WCDB 未连接' }
+    if (!this.wcdbAiQueryTimeline) return { success: false, error: '当前数据服务版本不支持 AI 时间轴查询' }
+    try {
+      const outPtr = [null as any]
+      const result = this.wcdbAiQueryTimeline(this.handle, JSON.stringify({
+        session_id: options.sessionId || '',
+        keyword: options.keyword || '',
+        limit: options.limit || 120,
+        offset: options.offset || 0,
+        begin_timestamp: options.beginTimestamp || 0,
+        end_timestamp: options.endTimestamp || 0
+      }), outPtr)
+      if (result !== 0 || !outPtr[0]) return { success: false, error: `AI 时间轴查询失败: ${result}` }
+      const jsonStr = this.decodeJsonPtr(outPtr[0])
+      if (!jsonStr) return { success: false, error: '解析 AI 时间轴结果失败' }
+      const rows = this.parseMessageJson(jsonStr)
+      return { success: true, rows }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
+  async aiQueryTopicStats(options: {
+    sessionIds: string[]
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; data?: any; error?: string }> {
+    if (!this.ensureReady()) return { success: false, error: 'WCDB 未连接' }
+    if (!this.wcdbAiQueryTopicStats) return { success: false, error: '当前数据服务版本不支持 AI 主题统计' }
+    try {
+      const outPtr = [null as any]
+      const result = this.wcdbAiQueryTopicStats(this.handle, JSON.stringify({
+        session_ids_json: JSON.stringify(options.sessionIds || []),
+        begin_timestamp: options.beginTimestamp || 0,
+        end_timestamp: options.endTimestamp || 0
+      }), outPtr)
+      if (result !== 0 || !outPtr[0]) return { success: false, error: `AI 主题统计失败: ${result}` }
+      const jsonStr = this.decodeJsonPtr(outPtr[0])
+      if (!jsonStr) return { success: false, error: '解析 AI 主题统计失败' }
+      const data = JSON.parse(jsonStr)
+      return { success: true, data }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
+  async aiQuerySourceRefs(options: {
+    sessionIds: string[]
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; data?: any; error?: string }> {
+    if (!this.ensureReady()) return { success: false, error: 'WCDB 未连接' }
+    if (!this.wcdbAiQuerySourceRefs) return { success: false, error: '当前数据服务版本不支持 AI 来源引用查询' }
+    try {
+      const outPtr = [null as any]
+      const result = this.wcdbAiQuerySourceRefs(this.handle, JSON.stringify({
+        session_ids_json: JSON.stringify(options.sessionIds || []),
+        begin_timestamp: options.beginTimestamp || 0,
+        end_timestamp: options.endTimestamp || 0
+      }), outPtr)
+      if (result !== 0 || !outPtr[0]) return { success: false, error: `AI 来源引用查询失败: ${result}` }
+      const jsonStr = this.decodeJsonPtr(outPtr[0])
+      if (!jsonStr) return { success: false, error: '解析 AI 来源引用查询失败' }
+      const data = JSON.parse(jsonStr)
+      return { success: true, data }
+    } catch (e) {
+      return { success: false, error: String(e) }
+    }
+  }
+
   async getSnsTimeline(limit: number, offset: number, usernames?: string[], keyword?: string, startTime?: number, endTime?: number): Promise<{ success: boolean; timeline?: any[]; error?: string }> {
     if (!this.ensureReady()) return { success: false, error: 'WCDB 未连接' }
     if (!this.wcdbGetSnsTimeline) return { success: false, error: '当前数据服务版本不支持获取朋友圈' }

electron/services/wcdbService.ts

@@ -489,6 +489,44 @@ export class WcdbService {
     return this.callWorker('closeMessageCursor', { cursor })
   }
 
+  /**
+   * SQL Lab: 获取多数据源 Schema 摘要
+   */
+  async sqlLabGetSchema(payload?: { sessionId?: string }): Promise<{
+    success: boolean
+    schema?: {
+      generatedAt: number
+      sources: Array<{
+        kind: 'message' | 'contact' | 'biz'
+        path: string | null
+        label: string
+        tables: Array<{ name: string; columns: string[] }>
+      }>
+    }
+    schemaText?: string
+    error?: string
+  }> {
+    return this.callWorker('sqlLabGetSchema', payload || {})
+  }
+
+  /**
+   * SQL Lab: 执行只读 SQL
+   */
+  async sqlLabExecuteReadonly(payload: {
+    kind: 'message' | 'contact' | 'biz'
+    path?: string | null
+    sql: string
+    limit?: number
+  }): Promise<{
+    success: boolean
+    rows?: any[]
+    columns?: string[]
+    total?: number
+    error?: string
+  }> {
+    return this.callWorker('sqlLabExecuteReadonly', payload)
+  }
+
   /**
    * 执行 SQL 查询（仅主进程内部使用：fallback/diagnostic/低频兼容）
    */
@@ -542,6 +580,42 @@ export class WcdbService {
     return this.callWorker('searchMessages', { keyword, sessionId, limit, offset, beginTimestamp, endTimestamp })
   }
 
+  async aiQuerySessionCandidates(options: {
+    keyword: string
+    limit?: number
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; rows?: any[]; error?: string }> {
+    return this.callWorker('aiQuerySessionCandidates', { options })
+  }
+
+  async aiQueryTimeline(options: {
+    sessionId?: string
+    keyword: string
+    limit?: number
+    offset?: number
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; rows?: any[]; error?: string }> {
+    return this.callWorker('aiQueryTimeline', { options })
+  }
+
+  async aiQueryTopicStats(options: {
+    sessionIds: string[]
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; data?: any; error?: string }> {
+    return this.callWorker('aiQueryTopicStats', { options })
+  }
+
+  async aiQuerySourceRefs(options: {
+    sessionIds: string[]
+    beginTimestamp?: number
+    endTimestamp?: number
+  }): Promise<{ success: boolean; data?: any; error?: string }> {
+    return this.callWorker('aiQuerySourceRefs', { options })
+  }
+
   /**
    * 获取语音数据
    */