feat: add SkillManager and activate_skill tool to shared package

Extract SkillManager from Electron to @openchatlab/node-runtime.
Create shared createActivateSkillTool factory.
Integrate skill menu into server agent system prompt and SSE route.

packages/node-runtime/src/ai/activate-skill-tool.ts

@@ -0,0 +1,98 @@
+/**
+ * activate_skill 元工具（AI 自选模式专用）
+ *
+ * LLM 判断用户问题适合某个技能时调用此工具，获取技能的完整执行指导。
+ * 平台无关 — 通过 getter 函数获取技能定义。
+ */
+
+import type { SkillDef } from './types'
+
+export interface ActivateSkillToolResult {
+  content: Array<{ type: 'text'; text: string }>
+  details: Record<string, unknown>
+}
+
+export interface ActivateSkillToolOptions {
+  chatType: 'group' | 'private'
+  allowedTools?: string[]
+  coreToolNames?: Set<string>
+  locale?: string
+  getSkillConfig: (id: string) => SkillDef | null
+}
+
+export interface ActivateSkillTool {
+  name: string
+  label: string
+  description: string
+  parameters: Record<string, unknown>
+  execute: (
+    toolCallId: string,
+    params: { skill_id: string },
+    signal?: AbortSignal,
+    onUpdate?: unknown
+  ) => Promise<ActivateSkillToolResult>
+}
+
+export function createActivateSkillTool(options: ActivateSkillToolOptions): ActivateSkillTool {
+  const { chatType, allowedTools, coreToolNames, getSkillConfig, locale = 'zh-CN' } = options
+  const isZh = locale.startsWith('zh')
+
+  return {
+    name: 'activate_skill',
+    label: 'activate_skill',
+    description: isZh
+      ? '激活一个分析技能，获取该技能的详细执行指导'
+      : 'Activate an analysis skill and get its detailed execution instructions',
+    parameters: {
+      type: 'object',
+      properties: {
+        skill_id: {
+          type: 'string',
+          description: isZh ? '技能 ID' : 'Skill ID',
+        },
+      },
+      required: ['skill_id'],
+    },
+    execute: async (_toolCallId: string, params: { skill_id: string }) => {
+      const skill: SkillDef | null = getSkillConfig(params.skill_id)
+      if (!skill) {
+        return {
+          content: [{ type: 'text' as const, text: isZh ? '技能不存在' : 'Skill not found' }],
+          details: { skillId: params.skill_id, found: false },
+        }
+      }
+
+      if (skill.chatScope !== 'all' && skill.chatScope !== chatType) {
+        const scopeMsg = isZh
+          ? `该技能仅适用于${skill.chatScope === 'group' ? '群聊' : '私聊'}场景`
+          : `This skill is only applicable to ${skill.chatScope === 'group' ? 'group chat' : 'private chat'} scenarios`
+        return {
+          content: [{ type: 'text' as const, text: scopeMsg }],
+          details: { skillId: params.skill_id, found: true, applicable: false },
+        }
+      }
+
+      if (skill.tools.length > 0 && allowedTools && allowedTools.length > 0) {
+        const missing = skill.tools.filter((t) => !(coreToolNames?.has(t) ?? false) && !allowedTools.includes(t))
+        if (missing.length > 0) {
+          const msg = isZh
+            ? `当前助手缺少该技能所需的工具：${missing.join(', ')}`
+            : `Current assistant lacks tools required by this skill: ${missing.join(', ')}`
+          return {
+            content: [{ type: 'text' as const, text: msg }],
+            details: { skillId: params.skill_id, found: true, applicable: false, missingTools: missing },
+          }
+        }
+      }
+
+      const actionPrompt = isZh
+        ? '\n\n[System]: 你已成功加载该技能手册。现在，请立即、自动地开始执行步骤1，调用相关的基础数据工具，不要等待用户的进一步确认！'
+        : '\n\n[System]: You have successfully loaded this skill manual. Now, immediately start executing step 1 by calling the relevant data tools. Do not wait for further user confirmation!'
+
+      return {
+        content: [{ type: 'text' as const, text: `${skill.prompt}${actionPrompt}` }],
+        details: { skillId: params.skill_id, found: true, applicable: true },
+      }
+    },
+  }
+}

packages/node-runtime/src/ai/index.ts

@@ -20,6 +20,12 @@ export type {
 // Tokenizer
 export { countTokens, countMessagesTokens } from './tokenizer'
 
+// SkillManager
+export { SkillManager } from './skill-manager'
+export type { SkillManagerLogger } from './skill-manager'
+export { createActivateSkillTool } from './activate-skill-tool'
+export type { ActivateSkillToolOptions, ActivateSkillTool, ActivateSkillToolResult } from './activate-skill-tool'
+
 // Preprocessor
 export type {
   PreprocessConfig,

packages/node-runtime/src/ai/skill-manager.ts

@@ -0,0 +1,116 @@
+/**
+ * 技能管理器（平台无关）
+ *
+ * 从 aiDataDir/skills/*.md 加载技能定义，
+ * 提供查询和 AI 自选菜单构建。
+ */
+
+import * as fs from 'fs'
+import * as path from 'path'
+import { parseSkillFile } from './skill-parser'
+import type { SkillDef, SkillSummary } from './types'
+
+const SKILLS_DIR_NAME = 'skills'
+const MAX_SKILL_MENU_ITEMS = 15
+
+export interface SkillManagerLogger {
+  info(message: string, extra?: Record<string, unknown>): void
+  warn(message: string, extra?: Record<string, unknown>): void
+}
+
+const defaultLogger: SkillManagerLogger = {
+  info: () => {},
+  warn: () => {},
+}
+
+export class SkillManager {
+  private skills = new Map<string, SkillDef>()
+  private initialized = false
+  private skillsDir: string
+  private logger: SkillManagerLogger
+
+  constructor(aiDataDir: string, logger?: SkillManagerLogger) {
+    this.skillsDir = path.join(aiDataDir, SKILLS_DIR_NAME)
+    this.logger = logger ?? defaultLogger
+  }
+
+  init(): { total: number } {
+    this.loadAll()
+    this.initialized = true
+    this.logger.info(`SkillManager initialized: ${this.skills.size} skills`)
+    return { total: this.skills.size }
+  }
+
+  getSkillConfig(id: string): SkillDef | null {
+    this.ensureInitialized()
+    return this.skills.get(id) ?? null
+  }
+
+  getAllSkills(): SkillSummary[] {
+    this.ensureInitialized()
+    return Array.from(this.skills.values()).map((def) => ({
+      id: def.id,
+      name: def.name,
+      description: def.description,
+      tags: def.tags,
+      chatScope: def.chatScope,
+      tools: def.tools,
+      builtinId: def.builtinId,
+    }))
+  }
+
+  /**
+   * 构建 AI 自选技能菜单文本
+   * 只包含与当前 chatType + 助手工具权限兼容的技能
+   */
+  getSkillMenu(chatType: 'group' | 'private', allowedTools?: string[]): string | null {
+    this.ensureInitialized()
+
+    const compatible = Array.from(this.skills.values()).filter((skill) => {
+      if (skill.chatScope !== 'all' && skill.chatScope !== chatType) return false
+      if (skill.tools.length > 0 && allowedTools && allowedTools.length > 0) {
+        const allCovered = skill.tools.every((t) => allowedTools.includes(t))
+        if (!allCovered) return false
+      }
+      return true
+    })
+
+    if (compatible.length === 0) return null
+
+    const items = compatible.slice(0, MAX_SKILL_MENU_ITEMS)
+    const lines = items.map((s) => `- ${s.id}: ${s.name} — ${s.description}`)
+
+    return `## 可用技能
+以下是你可以使用的分析技能。当你判断用户的问题适合使用某个技能时，
+请调用 activate_skill 工具激活它，然后按照返回的指导完成任务。
+
+${lines.join('\n')}
+
+如果用户的问题不需要使用技能，直接回答即可。`
+  }
+
+  private ensureInitialized(): void {
+    if (!this.initialized) {
+      this.init()
+    }
+  }
+
+  private loadAll(): void {
+    this.skills.clear()
+    if (!fs.existsSync(this.skillsDir)) return
+
+    const files = fs.readdirSync(this.skillsDir).filter((f) => f.endsWith('.md'))
+    for (const file of files) {
+      try {
+        const filePath = path.join(this.skillsDir, file)
+        const content = fs.readFileSync(filePath, 'utf-8')
+        const def = parseSkillFile(content, filePath)
+        if (def) {
+          this.skills.set(def.id, def)
+        }
+      } catch (error) {
+        this.logger.warn(`Failed to load skill: ${file}`, { error: String(error) })
+      }
+    }
+  }
+}

packages/node-runtime/src/index.ts

@@ -36,6 +36,11 @@ export { parseAssistantFile, serializeAssistant, parseSkillFile, extractSkillId
 export { AIConversationManager } from './ai'
 export { countTokens, countMessagesTokens } from './ai'
 
+// SkillManager
+export { SkillManager } from './ai'
+export type { SkillManagerLogger, ActivateSkillToolOptions, ActivateSkillTool, ActivateSkillToolResult } from './ai'
+export { createActivateSkillTool } from './ai'
+
 // Preprocessor
 export type {
   PreprocessConfig,

packages/server/src/ai/agent.ts

@@ -37,6 +37,7 @@ export interface RunAgentOptions {
   chatType?: 'group' | 'private'
   locale?: string
   assistantSystemPrompt?: string
+  skillMenu?: string | null
   tools?: import('@mariozechner/pi-agent-core').AgentTool[]
   aiDataDir: string
   convManager: AIConversationManager
@@ -49,7 +50,8 @@ type SimpleHistoryMessage = { role: 'user' | 'assistant' | 'summary'; content: s
 function buildSystemPrompt(
   _chatType: 'group' | 'private',
   assistantSystemPrompt?: string,
-  locale: string = 'zh-CN'
+  locale: string = 'zh-CN',
+  skillMenu?: string | null
 ): string {
   const now = new Date()
   const dateLocale = locale.startsWith('zh') ? 'zh-CN' : 'en-US'
@@ -72,11 +74,17 @@ function buildSystemPrompt(
     ? '请直接回答用户的问题，不要使用工具除非确实需要。'
     : "Answer the user's question directly. Only use tools when truly necessary."
 
-  return `${role}
+  let prompt = `${role}
 
 ${datePrefix} ${currentDate}。
 
 ${responseNote}`
+
+  if (skillMenu) {
+    prompt += `\n\n${skillMenu}`
+  }
+
+  return prompt
 }
 
 function createEmptyPiUsage(): PiUsage {
@@ -119,6 +127,7 @@ export async function runServerAgent(options: RunAgentOptions): Promise<void> {
     chatType = 'group',
     locale = 'zh-CN',
     assistantSystemPrompt,
+    skillMenu,
     tools = [],
     aiDataDir,
     convManager,
@@ -136,7 +145,7 @@ export async function runServerAgent(options: RunAgentOptions): Promise<void> {
   const piModel = buildPiModel(llmConfig)
   const maxToolRounds = 5
 
-  const systemPrompt = buildSystemPrompt(chatType, assistantSystemPrompt, locale)
+  const systemPrompt = buildSystemPrompt(chatType, assistantSystemPrompt, locale, skillMenu)
   const totalUsage = { promptTokens: 0, completionTokens: 0, totalTokens: 0 }
   const toolsUsed: string[] = []
   let toolRounds = 0

packages/server/src/http/routes/ai.ts

@@ -13,7 +13,7 @@ import * as fs from 'fs'
 import * as path from 'path'
 import type { FastifyInstance } from 'fastify'
 import type { DatabaseManager, AIConversationManager } from '@openchatlab/node-runtime'
-import { parseAssistantFile, parseSkillFile } from '@openchatlab/node-runtime'
+import { parseAssistantFile, parseSkillFile, SkillManager, createActivateSkillTool } from '@openchatlab/node-runtime'
 import { BUILTIN_TOOL_CATALOG, BUILTIN_PROVIDERS, BUILTIN_MODELS, getBuiltinModelsByProvider } from '@openchatlab/core'
 import type { AssistantSummary, SkillSummary } from '@openchatlab/node-runtime'
 import { TOOL_REGISTRY } from '@openchatlab/tools'
@@ -360,6 +360,21 @@ export function registerAiRoutes(
         }))
       : []
 
+    const skillManager = new SkillManager(aiDataDir)
+    skillManager.init()
+    const toolNames = agentTools.map((t: { name: string }) => t.name)
+    const skillMenu = skillManager.getSkillMenu(chatType ?? 'group', toolNames)
+
+    if (skillMenu) {
+      const activateSkillTool = createActivateSkillTool({
+        chatType: chatType ?? 'group',
+        allowedTools: toolNames,
+        locale,
+        getSkillConfig: (id) => skillManager.getSkillConfig(id),
+      })
+      agentTools.push(activateSkillTool as any)
+    }
+
     const onEvent = (event: AgentStreamEvent) => {
       sendSSE(event.type, event)
       if (event.type === 'done') {
@@ -382,6 +397,7 @@ export function registerAiRoutes(
         chatType,
         locale,
         assistantSystemPrompt,
+        skillMenu,
         tools: agentTools,
         aiDataDir,
         convManager,