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SuperClaude/docs/User-Guide-zh/session-management.md
kazuki nakai 050d5ea2ab
refactor: PEP8 compliance - directory rename and code formatting (#425) 
* fix(orchestration): add WebFetch auto-trigger for infrastructure configuration

Problem: Infrastructure configuration changes (e.g., Traefik port settings)
were being made based on assumptions without consulting official documentation,
violating the 'Evidence > assumptions' principle in PRINCIPLES.md.

Solution:
- Added Infrastructure Configuration Validation section to MODE_Orchestration.md
- Auto-triggers WebFetch for infrastructure tools (Traefik, nginx, Docker, etc.)
- Enforces MODE_DeepResearch activation for investigation
- BLOCKS assumption-based configuration changes

Testing: Verified WebFetch successfully retrieves Traefik official docs (port 80 default)

This prevents production outages from infrastructure misconfiguration by ensuring
all technical recommendations are backed by official documentation.

* feat: Add PM Agent (Project Manager Agent) for seamless orchestration

Introduces PM Agent as the default orchestration layer that coordinates
all sub-agents and manages workflows automatically.

Key Features:
- Default orchestration: All user interactions handled by PM Agent
- Auto-delegation: Intelligent sub-agent selection based on task analysis
- Docker Gateway integration: Zero-token baseline with dynamic MCP loading
- Self-improvement loop: Automatic documentation of patterns and mistakes
- Optional override: Users can specify sub-agents explicitly if desired

Architecture:
- Agent spec: SuperClaude/Agents/pm-agent.md
- Command: SuperClaude/Commands/pm.md
- Updated docs: README.md (15→16 agents), agents.md (new Orchestration category)

User Experience:
- Default: PM Agent handles everything (seamless, no manual routing)
- Optional: Explicit --agent flag for direct sub-agent access
- Both modes available simultaneously (no user downside)

Implementation Status:
- ✅ Specification complete
- ✅ Documentation complete
- ⏳ Prototype implementation needed
- ⏳ Docker Gateway integration needed
- ⏳ Testing and validation needed

Refs: kazukinakai/docker-mcp-gateway (IRIS MCP Gateway integration)

* feat: Add Agent Orchestration rules for PM Agent default activation

Implements PM Agent as the default orchestration layer in RULES.md.

Key Changes:
- New 'Agent Orchestration' section (CRITICAL priority)
- PM Agent receives ALL user requests by default
- Manual override with @agent-[name] bypasses PM Agent
- Agent Selection Priority clearly defined:
  1. Manual override → Direct routing
  2. Default → PM Agent → Auto-delegation
  3. Delegation based on keywords, file types, complexity, context

User Experience:
- Default: PM Agent handles everything (seamless)
- Override: @agent-[name] for direct specialist access
- Transparent: PM Agent reports delegation decisions

This establishes PM Agent as the orchestration layer while
respecting existing auto-activation patterns and manual overrides.

Next Steps:
- Local testing in agiletec project
- Iteration based on actual behavior
- Documentation updates as needed

* refactor(pm-agent): redesign as self-improvement meta-layer

Problem Resolution:
PM Agent's initial design competed with existing auto-activation for task routing,
creating confusion about orchestration responsibilities and adding unnecessary complexity.

Design Change:
Redefined PM Agent as a meta-layer agent that operates AFTER specialist agents
complete tasks, focusing on:
- Post-implementation documentation and pattern recording
- Immediate mistake analysis with prevention checklists
- Monthly documentation maintenance and noise reduction
- Pattern extraction and knowledge synthesis

Two-Layer Orchestration System:
1. Task Execution Layer: Existing auto-activation handles task routing (unchanged)
2. Self-Improvement Layer: PM Agent meta-layer handles documentation (new)

Files Modified:
- SuperClaude/Agents/pm-agent.md: Complete rewrite with meta-layer design
  - Category: orchestration → meta
  - Triggers: All user interactions → Post-implementation, mistakes, monthly
  - Behavioral Mindset: Continuous learning system
  - Self-Improvement Workflow: BEFORE/DURING/AFTER/MISTAKE RECOVERY/MAINTENANCE

- SuperClaude/Core/RULES.md: Agent Orchestration section updated
  - Split into Task Execution Layer + Self-Improvement Layer
  - Added orchestration flow diagram
  - Clarified PM Agent activates AFTER task completion

- README.md: Updated PM Agent description
  - "orchestrates all interactions" → "ensures continuous learning"

- Docs/User-Guide/agents.md: PM Agent section rewritten
  - Section: Orchestration Agent → Meta-Layer Agent
  - Expertise: Project orchestration → Self-improvement workflow executor
  - Examples: Task coordination → Post-implementation documentation

- PR_DOCUMENTATION.md: Comprehensive PR documentation added
  - Summary, motivation, changes, testing, breaking changes
  - Two-layer orchestration system diagram
  - Verification checklist

Integration Validated:
Tested with agiletec project's self-improvement-workflow.md:
✅ PM Agent aligns with existing BEFORE/DURING/AFTER/MISTAKE RECOVERY phases
✅ Complements (not competes with) existing workflow
✅ agiletec workflow defines WHAT, PM Agent defines WHO executes it

Breaking Changes: None
- Existing auto-activation continues unchanged
- Specialist agents unaffected
- User workflows remain the same
- New capability: Automatic documentation and knowledge maintenance

Value Proposition:
Transforms SuperClaude into a continuously learning system that accumulates
knowledge, prevents recurring mistakes, and maintains fresh documentation
without manual intervention.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add Claude Code conversation history management research

Research covering .jsonl file structure, performance impact, and retention policies.

Content:
- Claude Code .jsonl file format and message types
- Performance issues from GitHub (memory leaks, conversation compaction)
- Retention policies (consumer vs enterprise)
- Rotation recommendations based on actual data
- File history snapshot tracking mechanics

Source: Moved from agiletec project (research applicable to all Claude Code projects)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: add Development documentation structure

Phase 1: Documentation Structure complete

- Add Docs/Development/ directory for development documentation
- Add ARCHITECTURE.md - System architecture with PM Agent meta-layer
- Add ROADMAP.md - 5-phase development plan with checkboxes
- Add TASKS.md - Daily task tracking with progress indicators
- Add PROJECT_STATUS.md - Current status dashboard and metrics
- Add pm-agent-integration.md - Implementation guide for PM Agent mode

This establishes comprehensive documentation foundation for:
- System architecture understanding
- Development planning and tracking
- Implementation guidance
- Progress visibility

Related: #pm-agent-mode #documentation #phase-1

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: PM Agent session lifecycle and PDCA implementation

Phase 2: PM Agent Mode Integration (Design Phase)

Commands/pm.md updates:
- Add "Always-Active Foundation Layer" concept
- Add Session Lifecycle (Session Start/During Work/Session End)
- Add PDCA Cycle (Plan/Do/Check/Act) automation
- Add Serena MCP Memory Integration (list/read/write_memory)
- Document auto-activation triggers

Agents/pm-agent.md updates:
- Add Session Start Protocol (MANDATORY auto-activation)
- Add During Work PDCA Cycle with example workflows
- Add Session End Protocol with state preservation
- Add PDCA Self-Evaluation Pattern
- Add Documentation Strategy (temp → patterns/mistakes)
- Add Memory Operations Reference

Key Features:
- Session start auto-activation for context restoration
- 30-minute checkpoint saves during work
- Self-evaluation with think_about_* operations
- Systematic documentation lifecycle
- Knowledge evolution to CLAUDE.md

Implementation Status:
- ✅ Design complete (Commands/pm.md, Agents/pm-agent.md)
- ⏳ Implementation pending (Core components)
- ⏳ Serena MCP integration pending

Salvaged from mistaken development in ~/.claude directory

Related: #pm-agent-mode #session-lifecycle #pdca-cycle #phase-2

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fix: disable Serena MCP auto-browser launch

Disable web dashboard and GUI log window auto-launch in Serena MCP server
to prevent intrusive browser popups on startup. Users can still manually
access the dashboard at http://localhost:24282/dashboard/ if needed.

Changes:
- Add CLI flags to Serena run command:
  - --enable-web-dashboard false
  - --enable-gui-log-window false
- Ensures Git-tracked configuration (no reliance on ~/.serena/serena_config.yml)
- Aligns with AIRIS MCP Gateway integration approach

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* refactor: rename directories to lowercase for PEP8 compliance

- Rename superclaude/Agents -> superclaude/agents
- Rename superclaude/Commands -> superclaude/commands
- Rename superclaude/Core -> superclaude/core
- Rename superclaude/Examples -> superclaude/examples
- Rename superclaude/MCP -> superclaude/mcp
- Rename superclaude/Modes -> superclaude/modes

This change follows Python PEP8 naming conventions for package directories.

* style: fix PEP8 violations and update package name to lowercase

Changes:
- Format all Python files with black (43 files reformatted)
- Update package name from 'SuperClaude' to 'superclaude' in pyproject.toml
- Fix import statements to use lowercase package name
- Add missing imports (timedelta, __version__)
- Remove old SuperClaude.egg-info directory

PEP8 violations reduced from 2672 to 701 (mostly E501 line length due to black's 88 char vs flake8's 79 char limit).

* docs: add PM Agent development documentation

Add comprehensive PM Agent development documentation:
- PM Agent ideal workflow (7-phase autonomous cycle)
- Project structure understanding (Git vs installed environment)
- Installation flow understanding (CommandsComponent behavior)
- Task management system (current-tasks.md)

Purpose: Eliminate repeated explanations and enable autonomous PDCA cycles

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(pm-agent): add self-correcting execution and warning investigation culture

## Changes

### superclaude/commands/pm.md
- Add "Self-Correcting Execution" section with root cause analysis protocol
- Add "Warning/Error Investigation Culture" section enforcing zero-tolerance for dismissal
- Define error detection protocol: STOP → Investigate → Hypothesis → Different Solution → Execute
- Document anti-patterns (retry without understanding) and correct patterns (research-first)

### docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md
- Add PDCA workflow hypothesis document for PM Agent autonomous enhancement

## Rationale

PM Agent must never retry failed operations without understanding root causes.
All warnings and errors require investigation via context7/WebFetch/documentation
to ensure production-quality code and prevent technical debt accumulation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(installer): add airis-mcp-gateway MCP server option

## Changes

- Add airis-mcp-gateway to MCP server options in installer
- Configuration: GitHub-based installation via uvx
- Repository: https://github.com/oraios/airis-mcp-gateway
- Purpose: Dynamic MCP Gateway for zero-token baseline and on-demand tool loading

## Implementation

Added to setup/components/mcp.py self.mcp_servers dictionary with:
- install_method: github
- install_command: uvx test installation
- run_command: uvx runtime execution
- required: False (optional server)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-14 08:47:09 +05:30

9.1 KiB
Raw Blame History

会话管理指南

SuperClaude 通过 Serena MCP 服务器提供持久会话管理，实现在 Claude Code 对话中真正的上下文保存和长期项目连续性。

具有持久内存的核心会话命令

/sc:load - 具有持久内存的上下文加载

目的：使用项目上下文和以前会话的持久内存初始化会话 MCP 集成：触发 Serena MCP 读取存储的项目内存 语法：/sc:load [project_path]

发生什么：

  • Serena MCP 从以前的会话中读取持久内存文件
  • 从存储的内存中恢复项目上下文
  • 加载以前的决策、模式和进度
  • 使用历史上下文初始化会话状态

使用案例：

# 从持久内存加载现有项目上下文
/sc:load src/

# 恢复特定项目工作及其完整历史
/sc:load "authentication system"

# 使用代码库分析和先前见解初始化
/sc:load . --analyze

/sc:save - 会话持久化到内存

目的：将当前会话状态和决策保存到持久内存 MCP 集成：触发 Serena MCP 写入内存文件 语法：/sc:save "会话描述"

发生什么：

  • 当前上下文和决策被写入 Serena 内存
  • 项目状态和进度在对话中持久保存
  • 关键见解和模式被存储以供未来会话使用
  • 创建带有时间戳的会话摘要以便检索

使用案例：

# 保存已完成的特性工作以供未来参考
/sc:save "user authentication implemented with JWT"

# 复杂工作期间的检查点
/sc:save "API design phase complete, ready for implementation"

# 永久存储架构决策
/sc:save "microservices architecture decided, service boundaries defined"

/sc:reflect - 带有内存上下文的进度评估

目的：根据存储的内存分析当前进度并验证会话完整性 MCP 集成：使用 Serena MCP 将当前状态与存储的内存进行比较 语法：/sc:reflect [--scope project|session]

发生什么：

  • Serena MCP 读取以前的内存和当前上下文
  • 根据存储的目标和里程碑评估进度
  • 使用历史上下文识别差距和下一步
  • 根据项目内存验证会话完整性

使用案例：

# 根据存储的里程碑评估项目进度
/sc:reflect --scope project

# 验证当前会话完整性
/sc:reflect

# 根据内存检查是否准备进入下一阶段
/sc:reflect --scope session

持久内存架构

Serena MCP 如何实现真正的持久性

内存存储：

  • 会话上下文作为结构化内存文件存储
  • 项目决策和架构模式永久保存
  • 代码分析结果和见解在对话中保持
  • 进度跟踪和里程碑数据长期维护

跨会话连续性：

  • 新对话中自动加载以前的会话上下文
  • 决策和理由在对话中保存和可访问
  • 从过去的模式和解决方案中学习并维护
  • 一致的项目理解无限期维护

内存类型：

  • 项目内存：长期项目上下文和架构
  • 会话内存：特定对话结果和决策
  • 模式内存：可重用的解决方案和架构模式
  • 进度内存：里程碑跟踪和完成状态

具有持久性的会话生命周期模式

新项目初始化

# 1. 开始全新项目
/sc:brainstorm "e-commerce platform requirements"

# 2. 将初始决策保存到持久内存
/sc:save "project scope and requirements defined"

# 3. 开始实现规划
/sc:workflow "user authentication system"

# 4. 永久保存架构决策
/sc:save "authentication architecture: JWT + refresh tokens + rate limiting"

恢复现有工作（跨对话）

# 1. 从持久内存加载以前的上下文
/sc:load "e-commerce project"

# 2. 根据存储的进度评估当前状态
/sc:reflect --scope project

# 3. 使用存储的上下文继续下一阶段
/sc:implement "payment processing integration"

# 4. 将进度检查点保存到内存
/sc:save "payment system integrated with Stripe API"

长期项目管理

# 具有持久性的周检查点模式
/sc:load project-name
/sc:reflect --scope project
# ... 处理特性 ...
/sc:save "week N progress: features X, Y, Z completed"

# 具有内存的阶段完成模式
/sc:reflect --scope project
/sc:save "phase 1 complete: core authentication and user management"
/sc:workflow "phase 2: payment and order processing"

跨对话连续性

使用持久性开始新对话

当开始新的 Claude Code 对话时，持久内存系统允许：

  1. 自动上下文恢复

    /sc:load project-name
# 自动恢复所有以前的上下文、决策和进度

  2. 进度继续

    • 以前会话的决策立即可用
    • 架构模式和代码见解被保存
    • 项目历史和理由被维护

  3. 智能上下文构建

    • Serena MCP 根据当前工作提供相关内存
    • 过去的解决方案和模式指导新的实现
    • 项目演变被跟踪和理解

内存优化

有效的内存使用：

  • 使用描述性、可搜索的内存名称
  • 包含项目阶段和时间戳上下文
  • 引用特定功能或架构决策
  • 让未来的检索变得直观

内存内容策略：

  • 存储决策和理由，而不仅仅是结果
  • 包含考虑的替代方案
  • 记录集成模式和依赖关系
  • 为未来参考保留学习和洞察

内存生命周期管理：

  • 定期清理过时的内存
  • 整合相关的会话内存
  • 归档已完成的项目阶段
  • 修剪过时的架构决策

持久会话的最佳实践

会话开始协议

  1. 对于现有项目始终以 /sc:load 开始
  2. 使用 /sc:reflect 从内存中了解当前状态
  3. 根据持久上下文和存储的模式规划工作
  4. 基于以前的决策和架构选择构建

会话结束协议

  1. 使用 /sc:reflect 根据存储的目标评估完整性
  2. 使用 /sc:save 保存关键决策以供未来会话
  3. 在内存中记录下一步和未解决的问题
  4. 为无缝的未来继续保存上下文

内存质量维护

  • 使用清晰、描述性的内存名称以便于检索
  • 包含关于决策和替代方法的上下文
  • 引用特定的代码位置和模式
  • 在跨会话中保持内存结构的一致性

与其他 SuperClaude 功能的集成

MCP 服务器协调

  • Serena MCP：提供持久内存基础设施
  • Sequential MCP：使用存储的内存进行增强的复杂分析
  • Context7 MCP：引用存储的模式和文档方法
  • Morphllm MCP：一致地应用存储的重构模式

智能体与内存的协作

  • 智能体访问持久内存以增强上下文
  • 先前的专家决策被保留和引用
  • 通过共享内存进行跨会话智能体协调
  • 基于项目历史的一致专家建议

命令与持久化的集成

  • 所有 /sc: 命令都可以引用和构建持久上下文
  • 先前的命令输出和决策在跨会话中可用
  • 工作流程模式被存储和重用
  • 实现历史指导未来的命令决策

持久会话故障排除

常见问题

内存未加载：

  • 验证 Serena MCP 配置正确并正常运行
  • 检查内存文件权限和可访问性
  • 确保一致的项目命名约定
  • 验证内存文件完整性和格式

会话间上下文丢失：

  • 在结束会话前始终使用 /sc:save
  • 使用描述性内存名称以便于检索
  • 定期使用 /sc:reflect 验证内存完整性
  • 定期备份重要的内存文件

内存冲突：

  • 使用带时间戳的内存名称进行版本控制
  • 定期清理过时的内存
  • 清楚分离项目和会话内存
  • 在跨会话中保持一致的内存命名约定

快速修复

重置会话状态：

/sc:load --fresh  # 不带先前上下文开始
/sc:reflect       # 评估当前状态

内存清理：

/sc:reflect --cleanup  # 删除过时的内存
/sc:save --consolidate # 合并相关内存

上下文恢复：

/sc:load --recent     # 加载最近的内存
/sc:reflect --repair  # 识别并修复上下文空白

高级持久会话模式

多阶段项目

  • 使用阶段特定的内存命名进行组织
  • 跨阶段维护架构决策连续性
  • 通过持久内存进行跨阶段依赖跟踪
  • 具有历史上下文的渐进式复杂性管理

团队协作

  • 共享的内存约定和命名标准
  • 为团队上下文保留决策理由
  • 所有团队成员都可访问的集成模式文档
  • 通过内存实现一致的代码风格和架构执行

长期维护

  • 已完成项目的内存归档策略
  • 通过累积内存开发模式库
  • 随时间建立的可重用解决方案文档
  • 通过持久内存积累建立知识库

持久会话管理的关键优势

项目连续性

  • 在多次对话中无缝的工作延续
  • Claude Code 会话之间无上下文丢失
  • 保留的架构决策和技术理由
  • 长期项目演进跟踪

提升生产力

  • 减少重新解释项目上下文的需要
  • 继续工作的更快启动时间
  • 基于先前的洞察和模式进行构建
  • 累积的项目知识增长

质量一致性

  • 跨会话的一致架构模式
  • 保留的代码质量决策和标准
  • 可重用的解决方案和最佳实践
  • 维持的技术债务意识

关键要点：通过 Serena MCP 的会话管理将 SuperClaude 从单次对话帮助转变为持久项目伙伴关系，在所有开发阶段和 Claude Code 对话中维护上下文、决策和学习。