* 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>
11 KiB
Session Management Guide
SuperClaude provides persistent session management through the Serena MCP server, enabling true context preservation across Claude Code conversations and long-term project continuity.
Core Session Commands with Persistent Memory
/sc:load - Context Loading with Persistent Memory
Purpose: Initialize session with project context and persistent memory from previous sessions
MCP Integration: Triggers Serena MCP to read stored project memories
Syntax: /sc:load [project_path]
What Happens:
- Serena MCP reads persistent memory files from previous sessions
- Project context is restored from stored memories
- Previous decisions, patterns, and progress are loaded
- Session state is initialized with historical context
Use Cases:
# Load existing project context from persistent memory
/sc:load src/
# Resume specific project work with full history
/sc:load "authentication-system"
# Initialize with codebase analysis and previous insights
/sc:load . --analyze
/sc:save - Session Persistence to Memory
Purpose: Save current session state and decisions to persistent memory
MCP Integration: Triggers Serena MCP to write memory files
Syntax: /sc:save "session_description"
What Happens:
- Current context and decisions are written to Serena memory
- Project state and progress are persisted across conversations
- Key insights and patterns are stored for future sessions
- Session summary is created with timestamp for retrieval
Use Cases:
# Save completed feature work for future reference
/sc:save "user authentication implemented with JWT"
# Checkpoint during complex work
/sc:save "API design phase complete, ready for implementation"
# Store architectural decisions permanently
/sc:save "microservices architecture decided, service boundaries defined"
/sc:reflect - Progress Assessment with Memory Context
Purpose: Analyze current progress against stored memories and validate session completeness
MCP Integration: Uses Serena MCP to compare current state against stored memories
Syntax: /sc:reflect [--scope project|session]
What Happens:
- Serena MCP reads previous memories and current context
- Progress is assessed against stored goals and milestones
- Gaps and next steps are identified using historical context
- Session completeness is validated against project memory
Use Cases:
# Assess project progress against stored milestones
/sc:reflect --scope project
# Validate current session completeness
/sc:reflect
# Check if ready to move to next phase based on memory
/sc:reflect --scope session
Persistent Memory Architecture
How Serena MCP Enables True Persistence
Memory Storage:
- Session contexts stored as structured memory files
- Project decisions and architectural patterns preserved permanently
- Code analysis results and insights retained across conversations
- Progress tracking and milestone data maintained long-term
Cross-Session Continuity:
- Previous session context automatically available in new conversations
- Decisions and rationale preserved and accessible across conversations
- Learning from past patterns and solutions maintained
- Consistent project understanding maintained indefinitely
Memory Types:
- Project Memories: Long-term project context and architecture
- Session Memories: Specific conversation outcomes and decisions
- Pattern Memories: Reusable solutions and architectural patterns
- Progress Memories: Milestone tracking and completion status
Session Lifecycle Patterns with Persistence
New Project Initialization
# 1. Start fresh project
/sc:brainstorm "e-commerce platform requirements"
# 2. Save initial decisions to persistent memory
/sc:save "project scope and requirements defined"
# 3. Begin implementation planning
/sc:workflow "user authentication system"
# 4. Save architectural decisions permanently
/sc:save "auth architecture: JWT + refresh tokens + rate limiting"
Resuming Existing Work (Cross-Conversation)
# 1. Load previous context from persistent memory
/sc:load "e-commerce-project"
# 2. Assess current state against stored progress
/sc:reflect --scope project
# 3. Continue with next phase using stored context
/sc:implement "payment processing integration"
# 4. Save progress checkpoint to memory
/sc:save "payment system integrated with Stripe API"
Long-Term Project Management
# Weekly checkpoint pattern with persistence
/sc:load project-name
/sc:reflect --scope project
# ... work on features ...
/sc:save "week N progress: features X, Y, Z completed"
# Phase completion pattern with memory
/sc:reflect --scope project
/sc:save "Phase 1 complete: core authentication and user management"
/sc:workflow "Phase 2: payment and order processing"
Cross-Conversation Continuity
Starting New Conversations with Persistence
When starting a new Claude Code conversation, the persistent memory system allows:
-
Automatic Context Restoration
/sc:load project-name # Automatically restores all previous context, decisions, and progress -
Progress Continuation
- Previous session decisions are immediately available
- Architectural patterns and code insights are preserved
- Project history and rationale are maintained
-
Intelligent Context Building
- Serena MCP provides relevant memories based on current work
- Past solutions and patterns inform new implementations
- Project evolution is tracked and understood
Memory Optimization
Effective Memory Usage:
- Use descriptive, searchable memory names
- Include project phase and timestamp context
- Reference specific features or architectural decisions
- Make future retrieval intuitive
Memory Content Strategy:
- Store decisions and rationale, not just outcomes
- Include alternative approaches considered
- Document integration patterns and dependencies
- Preserve learning and insights for future reference
Memory Lifecycle Management:
- Regular cleanup of outdated memories
- Consolidation of related session memories
- Archiving of completed project phases
- Pruning of obsolete architectural decisions
Best Practices for Persistent Sessions
Session Start Protocol
- Always begin with
/sc:loadfor existing projects - Use
/sc:reflectto understand current state from memory - Plan work based on persistent context and stored patterns
- Build on previous decisions and architectural choices
Session End Protocol
- Use
/sc:reflectto assess completeness against stored goals - Save key decisions with
/sc:savefor future sessions - Document next steps and open questions in memory
- Preserve context for seamless future continuation
Memory Quality Maintenance
- Use clear, descriptive memory names for easy retrieval
- Include context about decisions and alternative approaches
- Reference specific code locations and patterns
- Maintain consistency in memory structure across sessions
Integration with Other SuperClaude Features
MCP Server Coordination
- Serena MCP: Provides the persistent memory infrastructure
- Sequential MCP: Uses stored memories for enhanced complex analysis
- Context7 MCP: References stored patterns and documentation approaches
- Morphllm MCP: Applies stored refactoring patterns consistently
Agent Collaboration with Memory
- Agents access persistent memories for enhanced context
- Previous specialist decisions are preserved and referenced
- Cross-session agent coordination through shared memory
- Consistent specialist recommendations based on project history
Command Integration with Persistence
- All
/sc:commands can reference and build on persistent context - Previous command outputs and decisions are available across sessions
- Workflow patterns are stored and reusable
- Implementation history guides future command decisions
Troubleshooting Persistent Sessions
Common Issues
Memory Not Loading:
- Verify Serena MCP is configured and running properly
- Check memory file permissions and accessibility
- Ensure consistent project naming conventions
- Validate memory file integrity and format
Context Loss Between Sessions:
- Always use
/sc:savebefore ending sessions - Use descriptive memory names for easy retrieval
- Regular
/sc:reflectto validate memory completeness - Backup important memory files periodically
Memory Conflicts:
- Use timestamped memory names for version control
- Regular cleanup of obsolete memories
- Clear separation between project and session memories
- Consistent memory naming conventions across sessions
Quick Fixes
Reset Session State:
/sc:load --fresh # Start without previous context
/sc:reflect # Assess current state
Memory Cleanup:
/sc:reflect --cleanup # Remove obsolete memories
/sc:save --consolidate # Merge related memories
Context Recovery:
/sc:load --recent # Load most recent memories
/sc:reflect --repair # Identify and fix context gaps
Advanced Persistent Session Patterns
Multi-Phase Projects
- Use phase-specific memory naming for organization
- Maintain architectural decision continuity across phases
- Cross-phase dependency tracking through persistent memory
- Progressive complexity management with historical context
Team Collaboration
- Shared memory conventions and naming standards
- Decision rationale preservation for team context
- Integration pattern documentation accessible to all team members
- Consistent code style and architecture enforcement through memory
Long-Term Maintenance
- Memory archiving strategies for completed projects
- Pattern library development through accumulated memories
- Reusable solution documentation built over time
- Knowledge base building through persistent memory accumulation
Key Benefits of Persistent Session Management
Project Continuity
- Seamless work continuation across multiple conversations
- No context loss between Claude Code sessions
- Preserved architectural decisions and technical rationale
- Long-term project evolution tracking
Enhanced Productivity
- Reduced need to re-explain project context
- Faster startup time for continued work
- Building on previous insights and patterns
- Cumulative project knowledge growth
Quality Consistency
- Consistent architectural patterns across sessions
- Preserved code quality decisions and standards
- Reusable solutions and best practices
- Maintained technical debt awareness
Key Takeaway: Session management through Serena MCP transforms SuperClaude from single-conversation assistance to persistent project partnership, maintaining context, decisions, and learning across all development phases and Claude Code conversations.