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 12:17:09 +09:00
# PM Agent Mode Integration Guide
**Last Updated**: 2025-10-14
**Target Version**: 4.2.0
**Status**: Implementation Guide
---
## 📋 Overview
This guide provides step-by-step procedures for integrating PM Agent mode as SuperClaude's always-active meta-layer with session lifecycle management, PDCA self-evaluation, and systematic knowledge management.
---
## 🎯 Integration Goals
1. **Session Lifecycle** : Auto-activation at session start with context restoration
2. **PDCA Engine** : Automated Plan-Do-Check-Act cycle execution
3. **Memory Operations** : Serena MCP integration for session persistence
4. **Documentation Strategy** : Systematic knowledge evolution
---
## 📐 Architecture Integration
### PM Agent Position
```
┌──────────────────────────────────────────┐
│ PM Agent Mode (Meta-Layer) │
│ • Always Active │
│ • Session Management │
│ • PDCA Self-Evaluation │
└──────────────┬───────────────────────────┘
↓
[Specialist Agents Layer]
↓
[Commands & Modes Layer]
↓
[MCP Tool Layer]
```
See: [ARCHITECTURE.md ](./ARCHITECTURE.md ) for full system architecture
---
## 🔧 Phase 2: Core Implementation
### File Structure
```
superclaude/
├── Commands/
│ └── pm.md # ✅ Already updated
├── Agents/
│ └── pm-agent.md # ✅ Already updated
└── Core/
├── __init__ .py # Module initialization
├── session_lifecycle.py # 🆕 Session management
├── pdca_engine.py # 🆕 PDCA automation
└── memory_ops.py # 🆕 Memory operations
```
### Implementation Order
1. `memory_ops.py` - Serena MCP wrapper (foundation)
2. `session_lifecycle.py` - Session management (depends on memory_ops)
3. `pdca_engine.py` - PDCA automation (depends on memory_ops)
---
## 1️ ⃣ memory_ops.py Implementation
### Purpose
Wrapper for Serena MCP memory operations with error handling and fallback.
### Key Functions
```python
# superclaude/Core/memory_ops.py
class MemoryOperations:
"""Serena MCP memory operations wrapper"""
def list_memories() -> List[str]:
"""List all available memories"""
def read_memory(key: str) -> Optional[Dict]:
"""Read memory by key"""
def write_memory(key: str, value: Dict) -> bool:
"""Write memory with key"""
def delete_memory(key: str) -> bool:
"""Delete memory by key"""
```
### Integration Points
- Connect to Serena MCP server
- Handle connection errors gracefully
- Provide fallback for offline mode
- Validate memory structure
### Testing
```bash
pytest tests/test_memory_ops.py -v
```
---
## 2️ ⃣ session_lifecycle.py Implementation
### Purpose
Auto-activation at session start, context restoration, user report generation.
### Key Functions
```python
# superclaude/Core/session_lifecycle.py
class SessionLifecycle:
"""Session lifecycle management"""
def on_session_start():
"""Hook for session start (auto-activation)"""
# 1. list_memories()
# 2. read_memory("pm_context")
# 3. read_memory("last_session")
# 4. read_memory("next_actions")
# 5. generate_user_report()
def generate_user_report() -> str:
"""Generate user report (前回/進捗/今回/課題)"""
def on_session_end():
"""Hook for session end (checkpoint save)"""
# 1. write_memory("last_session", summary)
# 2. write_memory("next_actions", todos)
# 3. write_memory("pm_context", complete_state)
```
### User Report Format
```
前回: [last session summary]
進捗: [current progress status]
今回: [planned next actions]
課題: [blockers or issues]
```
### Integration Points
- Hook into Claude Code session start
- Read memories using memory_ops
- Generate human-readable report
- Handle missing or corrupted memory
### Testing
```bash
pytest tests/test_session_lifecycle.py -v
```
---
## 3️ ⃣ pdca_engine.py Implementation
### Purpose
Automate PDCA cycle execution with documentation generation.
### Key Functions
```python
# superclaude/Core/pdca_engine.py
class PDCAEngine:
"""PDCA cycle automation"""
def plan_phase(goal: str):
"""Generate hypothesis (仮説)"""
# 1. write_memory("plan", goal)
# 2. Create docs/temp/hypothesis-YYYY-MM-DD.md
def do_phase():
"""Track experimentation (実験)"""
# 1. TodoWrite tracking
# 2. write_memory("checkpoint", progress) every 30min
# 3. Update docs/temp/experiment-YYYY-MM-DD.md
def check_phase():
"""Self-evaluation (評価)"""
# 1. think_about_task_adherence()
# 2. think_about_whether_you_are_done()
# 3. Create docs/temp/lessons-YYYY-MM-DD.md
def act_phase():
"""Knowledge extraction (改善)"""
# 1. Success → docs/patterns/[pattern-name].md
# 2. Failure → docs/mistakes/mistake-YYYY-MM-DD.md
# 3. Update CLAUDE.md if global pattern
```
### Documentation Templates
**hypothesis-template.md**:
```markdown
# Hypothesis: [Goal Description]
Date: YYYY-MM-DD
Status: Planning
## Goal
What are we trying to accomplish?
## Approach
How will we implement this?
## Success Criteria
How do we know when we're done?
## Potential Risks
What could go wrong?
```
**experiment-template.md**:
```markdown
# Experiment Log: [Implementation Name]
Date: YYYY-MM-DD
Status: In Progress
## Implementation Steps
- [ ] Step 1
- [ ] Step 2
## Errors Encountered
- Error 1: Description, solution
## Solutions Applied
- Solution 1: Description, result
## Checkpoint Saves
- 10:00: [progress snapshot]
- 10:30: [progress snapshot]
```
### Integration Points
- Create docs/ directory templates
- Integrate with TodoWrite
- Call Serena MCP think operations
- Generate documentation files
### Testing
```bash
pytest tests/test_pdca_engine.py -v
```
---
## 🔌 Phase 3: Serena MCP Integration
### Prerequisites
```bash
# Install Serena MCP server
# See: docs/troubleshooting/serena-installation.md
```
### Configuration
```json
// ~/.claude/.claude.json
{
"mcpServers": {
"serena": {
"command": "uv",
"args": ["run", "serena-mcp"]
}
}
}
```
### Memory Structure
```json
{
"pm_context": {
"project": "SuperClaude_Framework",
"current_phase": "Phase 2",
"architecture": "Context-Oriented Configuration",
"patterns": ["PDCA Cycle", "Session Lifecycle"]
},
"last_session": {
"date": "2025-10-14",
"accomplished": ["Phase 1 complete"],
"issues": ["Serena MCP not configured"],
"learned": ["Session Lifecycle pattern"]
},
"next_actions": [
"Implement session_lifecycle.py",
"Configure Serena MCP",
"Test memory operations"
]
}
```
### Testing Serena Connection
```bash
# Test memory operations
python -m SuperClaude.Core.memory_ops --test
```
---
## 📁 Phase 4: Documentation Strategy
### Directory Structure
```
docs/
├── temp/ # Temporary (7-day lifecycle)
│ ├── hypothesis-YYYY-MM-DD.md
│ ├── experiment-YYYY-MM-DD.md
│ └── lessons-YYYY-MM-DD.md
├── patterns/ # Formal patterns (永久保存)
│ └── [pattern-name].md
└── mistakes/ # Mistake records (永久保存)
└── mistake-YYYY-MM-DD.md
```
### Lifecycle Automation
```bash
# Create cleanup script
scripts/cleanup_temp_docs.sh
# Run daily via cron
0 0 * * * /path/to/scripts/cleanup_temp_docs.sh
```
### Migration Scripts
```bash
# Migrate successful experiments to patterns
python scripts/migrate_to_patterns.py
# Migrate failures to mistakes
python scripts/migrate_to_mistakes.py
```
---
## 🚀 Phase 5: Auto-Activation (Research Needed)
### Research Questions
1. How does Claude Code handle initialization?
2. Are there plugin hooks available?
3. Can we intercept session start events?
### Implementation Plan (TBD)
Once research complete, implement auto-activation hooks:
```python
# superclaude/Core/auto_activation.py (future)
def on_claude_code_start():
"""Auto-activate PM Agent at session start"""
session_lifecycle.on_session_start()
```
---
## ✅ Implementation Checklist
### Phase 2: Core Implementation
- [ ] Implement `memory_ops.py`
- [ ] Write unit tests for memory_ops
- [ ] Implement `session_lifecycle.py`
- [ ] Write unit tests for session_lifecycle
- [ ] Implement `pdca_engine.py`
- [ ] Write unit tests for pdca_engine
- [ ] Integration testing
### Phase 3: Serena MCP
- [ ] Install Serena MCP server
- [ ] Configure `.claude.json`
- [ ] Test memory operations
- [ ] Test think operations
- [ ] Test cross-session persistence
### Phase 4: Documentation Strategy
- [ ] Create `docs/temp/` template
- [ ] Create `docs/patterns/` template
- [ ] Create `docs/mistakes/` template
- [ ] Implement lifecycle automation
- [ ] Create migration scripts
### Phase 5: Auto-Activation
- [ ] Research Claude Code hooks
- [ ] Design auto-activation system
- [ ] Implement auto-activation
- [ ] Test session start behavior
---
## 🧪 Testing Strategy
### Unit Tests
```bash
tests/
├── test_memory_ops.py # Memory operations
├── test_session_lifecycle.py # Session management
└── test_pdca_engine.py # PDCA automation
```
### Integration Tests
```bash
tests/integration/
├── test_pm_agent_flow.py # End-to-end PM Agent
├── test_serena_integration.py # Serena MCP integration
└── test_cross_session.py # Session persistence
```
### Manual Testing
1. Start new session → Verify context restoration
2. Work on task → Verify checkpoint saves
3. End session → Verify state preservation
4. Restart → Verify seamless resumption
---
## 📊 Success Criteria
### Functional
- [ ] PM Agent activates at session start
- [ ] Context restores from memory
- [ ] User report generates correctly
- [ ] PDCA cycle executes automatically
- [ ] Documentation strategy works
### Performance
- [ ] Session start delay < 500ms
- [ ] Memory operations < 100ms
- [ ] Context restoration reliable (>99%)
### Quality
- [ ] Test coverage >90%
- [ ] No regression in existing features
- [ ] Documentation complete
---
## 🔧 Troubleshooting
### Common Issues
**"Serena MCP not connecting"**
- Check server installation
- Verify `.claude.json` configuration
- Test connection: `claude mcp list`
**"Memory operations failing"**
- Check network connection
- Verify Serena server running
- Check error logs
**"Context not restoring"**
- Verify memory structure
- Check `pm_context` exists
- Test with fresh memory
---
## 📚 References
- [ARCHITECTURE.md ](./ARCHITECTURE.md ) - System architecture
- [ROADMAP.md ](./ROADMAP.md ) - Development roadmap
2025-10-16 00:37:39 +09:00
- [PM_AGENT.md ](../PM_AGENT.md ) - Status tracking
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 12:17:09 +09:00
- [Commands/pm.md ](../../superclaude/Commands/pm.md ) - PM Agent command
- [Agents/pm-agent.md ](../../superclaude/Agents/pm-agent.md ) - PM Agent persona
---
**Last Verified**: 2025-10-14
**Next Review**: 2025-10-21 (1 week)
**Version**: 4.1.5