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

- 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

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 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

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

- 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

- 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

- 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

- 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

- 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