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- Moved data/system/ → system/ (agents, templates, skills, data, workspace) - Updated all server route/service path references - Updated all script path references - Updated all documentation references - Restructured .gitignore for cleaner system/ vs data/ boundary system/ = platform-shared assets (system agents, template library) data/ = tenant-specific company instance data
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- System agents: 只保留 master (data/system/agents/master) - Templates: 所有可复用 agent 模板 (data/system/templates/) - Companies: 公司创建时自动部署 5 个元 Agent (innovator/hunter/digester/evolver/agent-creator) 路径修复: - agent-chat.js: /list 扫描路径修正 (system/agents + companies/*/agents) - agent-manager.js: 动态 agent 查找路径修正 - skill-config-loader.js: 修正 agents root - pipeline-service.js: pipelines 输出到 companies/{id}/pipelines/ - billing.log: 移至 companies/{id}/logs/ 下 Skills 标准化: - 所有 template agent 建立 .claude/skills/main_skill/SKILL.md - company-service._copyTemplate() 新增 .claude/ 目录复制 - innovator SKILL.md v3.0: 移除旧 l3-hunt/l2-digest 命名 - 清理重复 agent_creator, 统一为 agent-creator 清理: - 移除 data/agents, data/workspace, data/logs, data/goals 旧目录 - 清除所有未使用的 DATA_DIR 声明 - 清除 template 中的 conversations/logs/memory 运行态数据
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Phase 3 反馈进化闭环: 1. DataSourceService (运营数据接入): - 新增 datasource-service.js: 抽象适配器模式 - MockAdapter: 模拟运营数据 (开发调试) - FileAdapter: 从本地 JSON 文件读取数据 - 可扩展: 预留 WechatAdapter/DouyinAdapter 接口 - API: GET /data/metrics, /data/trending, /data/attribution 2. 归因分析引擎: - analyzeAttribution(): 自动对比两个时间段指标 - 计算变化百分比和趋势方向 - 自动提取显著变化维度并生成洞察文本 - API: GET /api/company/:id/data/attribution 3. Know-how 自动更新 (memory-service.js): - 新增 updateAgentKnowhow() 函数 - autoReflect 产出的 patterns/lessons 自动写回 SKILL.md - 在 SKILL.md 末尾维护'经验教训(自动沉淀)'段落 - 保留最近 20 条记录，自动清理过旧条目 - 闭环: Agent执行 → 反思 → 经验写入SKILL → 下次读取改进行为
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…ter Agent cognitive auto-recovery loop - Refactored CompanyDashboard into read-only Observer UI - Enforced strict companyId:roleId namespacing across Node APIs and AgentManager - Added dynamic <env_status> injection to PromptBuilder for robust context - Introduced bin/lemon.js CLI for structured LLM tool execution - Implemented in-stream error interceptors for implicit silent retry loop
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…ze Chinese keyword extraction - Fix: The long trailing history in todo.md drowned out the actual current task keywords because English tokens (e.g. TASK, P2, from) padded the 30-keyword limit beforehand. - Updated extractKeywords: Process Chinese characters first as they carry more weight for NLP context intent. - Added userMessage prefix to searchText in buildSystemPrompt so newly dispatched tasks dominate keyword extraction. - End-to-end e2e test created and passed (27/27 asserts passed)
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Phase 3 features: - autoReflect: auto-trigger on complex conversations (toolCount>=3 or duration>=60s) - Extracts patterns from successful conversations - Extracts lessons from failed conversations - Auto-solidifies cerebellum plans from 5+ tool-call successes - Writes reflection logs to memory/reflections/ - Updates memory.md 'verified patterns' and 'lessons learned' sections - consolidateMemory: merge short-term sessions older than 7 days into long-term/ - Extracts frequent keywords across merged sessions - Writes consolidated summary to long-term/consolidate-{date}.md - Updates long-term/patterns.md with high-frequency patterns - generateDailyReport: aggregate today's sessions and reflections into daily/{date}.md - API endpoints: POST /:agentId/memory/consolidate, POST /:agentId/memory/daily-report Test results: 16/16 passed (Phase 3 test suite) -
- Hippocampus keyword matching engine (extractKeywords + score) - Cerebellum plan storage (saveCerebellumPlan) - Auto-sync hippocampus-index.json + hippocampus.md - POST /:agentId/memory/cerebellum API endpoint - buildSystemPrompt injects matched plans from hippocampus - Use count & lastUsed tracking on plan access - Chinese n-gram + English word tokenizer with stop words - Fix: score formula uses entry keyword count as denominator - Fix: useCount updates original index entry not spread copy - Verified: OKR plan matched + injected into CEO prompt
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- New: server/services/memory-service.js - saveSessionSummary(): auto-save session summary to short-term/ - loadRecentMemory(): inject last 5 sessions into system prompt - appendToMemoryMd(): auto-append key facts with size control - Modified: server/routes/agent-chat.js - buildSystemPrompt() now loads recent short-term sessions - Conversation completion triggers auto memory save - Verified: CEO Agent conversation creates session file + updates memory.md