宜博 / lemonboss

- CompanyDashboard Goals Tab: upgraded from flat list to full OKR tree view
  with progress bars, node hierarchy, status animations, owner/priority badges
- ClaudeCliProtocol: added --effort flag support (low=disable thinking)
- agent-chat.js: per-agent effort config from config.json cli.effort
- .gitignore: exclude data/companies/, apiconversation/, agent memory/tasks
- New views: TemplateAgents, JobsPanel, PipelineEditor, SkillsMarket
- docs/architecture-v5.md: added decision #13 (thinking control)

1. 根治所有模板 Agent残留的过往公司(LemonV)私人记忆，使其诞生即为全新白纸状态。
2. 提取出统一的 `methodology.md` 基类 Prompt，通过 `agent-chat.js` 强力注入。
3. 从 Master 到各路 Agent 都将强制遵循【从大脑到小脑】的不硬编码理念。
4. 全面引入统一的基础方法论（Harness）：学习(Research) -> 规划(Planning) -> 执行(Execute) -> 验证(Verify)

修复 Claude CLI 遇到严重 API 错误 (如 Http 429) 时，输出的不是合法 JSON，而是像
'MiniMax 检查失败: HTTP 429: {...}' 这样的纯文本行。
旧版本在 JSON.parse 失败后直接忽略。
新版本增加 fallback，匹配非 JSON 行中的错误关键字并强制中断死等和前端展示。

- 当底层模型 (MiniMax等) 抛出 API 错误时，Claude CLI 不会崩溃也不会输出 stderr，而是通过 stdout 输出 event.type='error' 的 JSON 块。
- 未处理该事件导致协议层无法等到 result 事件，引发 Promise 永久挂起。
- 修复：在_handleStreamEvent 拦截 error 块，主动抛出错误打断等待链，前端即可正常展示 ❌ API 请求失败。

- 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

- 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

The plugin bootstrap was calling resolveOpenclawDist() synchronously
at module load time, which crashed the entire server if the optional
@mas/openclaw-dist package wasn't installed. Now all three call sites
defer resolution to runtime with try/catch graceful fallback.

- 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

文档更新:
- 重写 11-directory-structure.md (data/system/ + data/{companyId}/)
- 重写 13-api-design.md (100+ 实际 API 端点)
- 更新 24-company-layer-architecture.md (规划中→已实现, Todo 全标完成)
- 更新 23-agent-active-heartbeat.md (规划中→已完成)
- 更新 architecture-v5.md (v5.3, Phase 4-6 新增)
- 更新 21-fde-pipeline-architecture.md (阈值 90→95, 路径修正)
- 更新 LEMONBOSS-SYSTEM-DESIGN.md (v2.0, 章节 15-26 索引)
- 新增 25-bootstrap-mechanism.md (公司自举机制)
- 新增 26-automated-hiring-orchestration.md (全自动招聘编排)

Bug 修复:
- fix(server): 修复 body sanitizer 空 body 时未设置 _bodyParsed
  导致 express.json() 重复读取已消费流的 stream-not-readable 错误

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

Phase A - Company Bootstrap 自举:
- 新增 _company_bootstrap/manifest.json 模板
- company create 时自动部署 CEO/CTO/COO/HR 四名核心骨干
- 自动启动公司 + 2s后向CEO dispatch战略启动令
- 支持 skipBootstrap 参数跳过自举

Phase B - HR 大一统 (招留管退):
- 新增 hr 模板（agent_creator 的进化体）
- HR 具备完整生命周期管理：招聘/技能装配/监控/辞退
- HR 具备模板发现能力（lemon company templates 查看可用模板如 scrapling_crawler）
- CTO 模板重写：不再亲自 hire，全部通过 task dispatch 向 HR 下发招聘需求单
- CEO 模板更新：确认 Bootstrap 已部署骨干，委派时强调 CTO→HR 招聘链
- 新增 POST /company/:id/fire API（停心跳→归档→更新名单）
- 新增 CLI: lemon company fire / lemon company templates

- Added async orchestration in `/company/:id/hire` when no template is found.
- Triggers Agent-Creator to write definition files based on scaffold.
- Searches Arena (skillDb) for 3 basic skills matching the role and injects them.
- Dispatches Innovator to run FDE pipeline and evaluate initial capabilities.

- Agent names are clickable links to chatbot page
- Action button group per agent: heartbeat ▶/⏹, 💬 Chat, 📋 Skills, 🎓 Train
- Expandable skills panel shows agent's loaded skills
- Train button sends instruction to CEO to arrange Innovator training
- Backend: GET /api/company/:id/agents/:agentId/skills API

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

- Add Company Overview tab as default landing page
- Show company info: status, uptime, agent count, heartbeat status
- Start/Stop company buttons (activate/deactivate all agent heartbeats)
- Per-agent heartbeat controls: interval dropdown, start/stop buttons
- Backend APIs: GET status, POST start/shutdown, PUT/POST agent heartbeat
- Track startedAt timestamp for uptime calculation
- Update CEO agent.md with mandatory 5-step startup workflow
- Fix company nav to default to overview tab

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

Phase 2 改进:

1. 工作日历系统 (ScheduleService):
   - 新增 schedule-service.js: 公司级日程管理
   - 支持按小时调度、按周几过滤、时区感知
   - 心跳触发时自动检查到期 slots 并触发 Agent
   - 执行去重（同日同 slot 不重复触发）
   - CRUD API: GET/POST/PUT/DELETE /api/company/:id/schedule/slots
   - CLI: schedule add / schedule list

2. 告警通道 (Alert Channel):
   - Pipeline 步骤超时自动告警 Master Agent
   - 心跳异常自动告警 Master Agent
   - _sendAlertToMaster() 统一告警接口

3. CEO → Pipeline 自动生成:
   - CEO 模板从 3 步升级为 5 步工作流
   - 新增 Step 2: Pipeline JSON 设计（含 loop/cron/steps 结构)
   - 新增 Step 4: OKR 创建
   - Pipeline 设计输出为 CTO 搭建流水线的蓝图

4. Master 晨会日报:
   - 每天 08:00 自动生成全公司运营日报
   - 包含公司状态、Pipeline 运行、OKR 进度、Agent 活跃度
   - 自动推送给 Master Agent
   - 防重复机制（每天只生成一次）

5. Pipeline 驳回信息注入:
   - 驳回步骤被心跳重新触发时，__rejection 信息注入 prompt
   - 让 Agent 知道被驳回的原因和重做次数
   - 替换原有 curl 汇报指令为 task report CLI

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

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

- 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

…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

…nti-confirmation prompts, cron dedup fix

- CompanyHeartbeatService: company-level heartbeat with timer registration
- Auto-trigger: cron-based pipeline scheduling (intervalHours)
- Active run driving: dispatch tasks to agents, timeout detection
- CEO heartbeat: periodic company status check
- Pipeline cron field support in definitions
- Registered in server startup alongside agent heartbeat
- E2E test: 113/113 passed (all phases + autonomous loop)

- PipelineService: define pipelines with ordered agent-assigned steps
- Run lifecycle: start → markStepStarted → advanceStep → complete
- Step output automatically flows as next step input
- Pipeline CRUD + Run management REST API routes
- E2E test: 106/106 passed (Phase 1 + 2 + 3 + 4)

- GoalsService refactored: constructor accepts optional companyId
  - With companyId: goals stored in data/{companyId}/goals/
  - Without: backward-compatible data/goals/ (global)
- Company Goals REST API: full OKR CRUD under /api/company/:id/goals
- OKR isolation verified: different companies have independent goal spaces
- E2E test: 81/81 passed (Phase 1 + 2 + 3)

- scaffoldNewAgent: create agent skeleton via AgentScaffold directly
- depositTemplate: benchmark gating (≥95) + auto-deposit to templates/
- hireWithTraining: full flow (template lookup → scaffold fallback)
- Company route: /hire uses hireWithTraining, new /deposit-template endpoint
- E2E test: 69/69 passed (Phase 1 + Phase 2)

- CompanyService: CRUD (create/get/list/update/shutdown)
- Agent Hiring Pipeline: template lookup → copy → context injection
- Template registry (_registry.json) with CEO and qa-judge initial templates
- resolveAgentDir(companyId, agentId) unified agent directory resolution
- Company REST API routes (/api/company/*)
- E2E test: 46/46 passed

- 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

…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)

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