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- ClaudeCliProtocol: stderr 检测 rate_limit/429/401 等致命错误时自动 reject sendPrompt Promise - agent-chat.js: 监听 stderr/disconnected 事件并通过 SSE 推送到前端 - AgentChat.vue: error 事件停止 thinking 状态 + ACP 日志面板显示错误
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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 -
- Add task transition CLI and API for Context Flush & Hot Swap - Enforce strict bash-only tool policy for Base Agents - Inject into system prompt for self-retrying loop - Implement Goal node updates on transitions - Add P0 Execute pre-approval block (Human-in-the-loop) - Track token metrics to billing.log
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核心改动: 1. agent-chat.js buildSystemPrompt 新增 Layer 0: 为公司Agent自动注入 公司环境上下文(companyId、roleName、公司共享工作区路径) 明确禁止写入全局 workspace/ 或 data/workspace/ 2. CEO 模板更新: workspace/ 引用改为"公司共享工作区" 3. 清理旧的 workspace/ 和 data/workspace/ 下的废弃公司目录
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Phase 4 人机流转机制打通: 1. 新增 API 与 CLI: - POST /api/agent/human-request 支持 Agent 求助 - `node bin/lemon.js human request` CLI 暴露给 Agent 使用 - 请求将自动追加至根目录 .env 文件并带有时间戳注释 - 同时将记录追加至 Master 的 workspace/human_todo.md 待办清单 - 触发实时通知事件给 Master Agent 2. `agent_creator` 人事专员模板创建: - 专门负责使用 `skill_search` (或自述构建) 并在新员工的 .claude/skills/ 下写武器代码 - 强制为技能预留 .env 读取代码，并当 key 不存在时使用 human request - 强制在装配初版后将该技能推入 innovator-001 队列进行强化学习训练 3. 架构优化: - 修改 CTO Agent 模板指令：在 hire 底层员工的同时，强制 hire 一名 agent_creator - CTO 不再亲自绑定技能，全部通过 `task dispatch` 给 agent_creator 完成装配
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Phase 1 核心改进: 1. Pipeline↔Task 系统打通: - task/report 回调自动推进 Pipeline 步骤 - findActiveRunStep() 按 agentId 定位活跃步骤 - 扫描所有公司的 Pipeline Runs 实现跨公司桥接 2. Pipeline 循环执行: - 新增 pipeline.loop 配置项 - Run 完成后自动启动下一轮 (最大 maxLoops=365) - loopCount 计数器追踪循环轮次 3. COO 质量门控: - 新增 rejectStep() 驳回方法，含驳回历史记录 - POST /api/agent/task/reject API 端点 - POST /api/company/:id/pipelines/runs/:runId/reject 路由 - node bin/lemon.js task reject CLI 命令 - 驳回后自动唤醒 Agent 重做，注入改进意见 4. COO 模板全面强化: - agent.md: 4维度评分体系、质量审核流程图 - soul.md: 性格、价值观、决策原则 - tools.md: 新增 task reject 核心工具 - heartbeat.md: 结构化巡检清单 + 升级规则
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1. Rewrote master/agent.md: strict anti-overreach rules, cleaned git merge conflicts 2. Enhanced agent-creator/agent.md: force Write tool for new files, mandatory task report 3. Implemented task/report callback: auto-wakes sender agent to continue next steps - Added .tasks/ metadata persistence for dispatch→report traceability - task/report sends [TASK_CALLBACK] to dispatching agent on done/failed
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- company.js: call heartbeatService._setupAgentHeartbeat after hire - CEO agent.md: enforce 3-step continuous execution in same turn - All CXO heartbeat intervals: 5 minutes - task dispatch message: self-drive directive, use lemon CLI - bin/lemon.js: add 'task report' command
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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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…nti-confirmation prompts, cron dedup fix
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- Extracted HeartbeatService to periodically wake up agents flagged with 'heartbeat.enabled' - Sends a silent [SYSTEM HEARTBEAT] message to trigger self-checks (e.g. OKR state validation) - Automatically integrated service dispatch hook in server startup sequence - Configured qa-judge to run autonomous heartbeat every 10 min
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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
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- Fix loadIdentity regex to handle **bold** markdown formatting - Add fallback to config.json name when identity.md has no 名称 field - Add 名称 field to Digester/Evolver/Innovator identity.md
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- Implement OKR GoalsService with hierarchical node tracking - Add /api/goals routes and integrate with dispatch/report APIs - Create Innovator agent with Hunt→Digest→Evolving pipeline - Create Hunter (l3-hunt), Digester (l2-digest), Evolver (evolving) meta agents - Copy L1/L2 dependency skills into each agent's .claude/skills/ - Fix buildSystemPrompt to scan ALL skill subdirectories (critical) - Fix agent list sorting: master pinned top, rest by lastActiveAt - Rename master-001→master, innovator-001→innovator - Establish meta agent output convention: write to target agent dir - Add CXO agent base class for management agents - Update CEO agent with delegation-first management model
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- Agent as Micro-Container: each agent lives in data/agents/{id}/ with full encapsulation - Persona vs Capability split: agent.md (identity) + .claude/skills/main_skill/SKILL.md (workflow) - Conversations co-located: data/agents/{id}/conversations/ replaces global dir - Meta Skills renamed: meta_hunt, meta_digest, meta_creator, meta_evolving, meta_benchmark, meta_research - Dynamic Hot-Reload: AgentManager.getAgentConfig() falls back to filesystem scan - Parallel Sub-Agent orchestration via Promise.all with multi-terminal UI - Removed SQLite dependency, global skills/ directory, and legacy conversations/ - Full architecture docs: 18-local-filesystem-first-agent-encapsulation.md