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* refactor: PM Agent complete independence from external MCP servers ## Summary Implement graceful degradation to ensure PM Agent operates fully without any MCP server dependencies. MCP servers now serve as optional enhancements rather than required components. ## Changes ### Responsibility Separation (NEW) - **PM Agent**: Development workflow orchestration (PDCA cycle, task management) - **mindbase**: Memory management (long-term, freshness, error learning) - **Built-in memory**: Session-internal context (volatile) ### 3-Layer Memory Architecture with Fallbacks 1. **Built-in Memory** [OPTIONAL]: Session context via MCP memory server 2. **mindbase** [OPTIONAL]: Long-term semantic search via airis-mcp-gateway 3. **Local Files** [ALWAYS]: Core functionality in docs/memory/ ### Graceful Degradation Implementation - All MCP operations marked with [ALWAYS] or [OPTIONAL] - Explicit IF/ELSE fallback logic for every MCP call - Dual storage: Always write to local files + optionally to mindbase - Smart lookup: Semantic search (if available) → Text search (always works) ### Key Fallback Strategies **Session Start**: - mindbase available: search_conversations() for semantic context - mindbase unavailable: Grep docs/memory/*.jsonl for text-based lookup **Error Detection**: - mindbase available: Semantic search for similar past errors - mindbase unavailable: Grep docs/mistakes/ + solutions_learned.jsonl **Knowledge Capture**: - Always: echo >> docs/memory/patterns_learned.jsonl (persistent) - Optional: mindbase.store() for semantic search enhancement ## Benefits - ✅ Zero external dependencies (100% functionality without MCP) - ✅ Enhanced capabilities when MCPs available (semantic search, freshness) - ✅ No functionality loss, only reduced search intelligence - ✅ Transparent degradation (no error messages, automatic fallback) ## Related Research - Serena MCP investigation: Exposes tools (not resources), memory = markdown files - mindbase superiority: PostgreSQL + pgvector > Serena memory features - Best practices alignment: /Users/kazuki/github/airis-mcp-gateway/docs/mcp-best-practices.md 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * chore: add PR template and pre-commit config - Add structured PR template with Git workflow checklist - Add pre-commit hooks for secret detection and Conventional Commits - Enforce code quality gates (YAML/JSON/Markdown lint, shellcheck) NOTE: Execute pre-commit inside Docker container to avoid host pollution: docker compose exec workspace uv tool install pre-commit docker compose exec workspace pre-commit run --all-files 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: update PM Agent context with token efficiency architecture - Add Layer 0 Bootstrap (150 tokens, 95% reduction) - Document Intent Classification System (5 complexity levels) - Add Progressive Loading strategy (5-layer) - Document mindbase integration incentive (38% savings) - Update with 2025-10-17 redesign details * refactor: PM Agent command with progressive loading - Replace auto-loading with User Request First philosophy - Add 5-layer progressive context loading - Implement intent classification system - Add workflow metrics collection (.jsonl) - Document graceful degradation strategy * fix: installer improvements Update installer logic for better reliability * docs: add comprehensive development documentation - Add architecture overview - Add PM Agent improvements analysis - Add parallel execution architecture - Add CLI install improvements - Add code style guide - Add project overview - Add install process analysis * docs: add research documentation Add LLM agent token efficiency research and analysis * docs: add suggested commands reference * docs: add session logs and testing documentation - Add session analysis logs - Add testing documentation * feat: migrate CLI to typer + rich for modern UX ## What Changed ### New CLI Architecture (typer + rich) - Created `superclaude/cli/` module with modern typer-based CLI - Replaced custom UI utilities with rich native features - Added type-safe command structure with automatic validation ### Commands Implemented - **install**: Interactive installation with rich UI (progress, panels) - **doctor**: System diagnostics with rich table output - **config**: API key management with format validation ### Technical Improvements - Dependencies: Added typer>=0.9.0, rich>=13.0.0, click>=8.0.0 - Entry Point: Updated pyproject.toml to use `superclaude.cli.app:cli_main` - Tests: Added comprehensive smoke tests (11 passed) ### User Experience Enhancements - Rich formatted help messages with panels and tables - Automatic input validation with retry loops - Clear error messages with actionable suggestions - Non-interactive mode support for CI/CD ## Testing ```bash uv run superclaude --help # ✓ Works uv run superclaude doctor # ✓ Rich table output uv run superclaude config show # ✓ API key management pytest tests/test_cli_smoke.py # ✓ 11 passed, 1 skipped ``` ## Migration Path - ✅ P0: Foundation complete (typer + rich + smoke tests) - 🔜 P1: Pydantic validation models (next sprint) - 🔜 P2: Enhanced error messages (next sprint) - 🔜 P3: API key retry loops (next sprint) ## Performance Impact - **Code Reduction**: Prepared for -300 lines (custom UI → rich) - **Type Safety**: Automatic validation from type hints - **Maintainability**: Framework primitives vs custom code 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: consolidate documentation directories Merged claudedocs/ into docs/research/ for consistent documentation structure. Changes: - Moved all claudedocs/*.md files to docs/research/ - Updated all path references in documentation (EN/KR) - Updated RULES.md and research.md command templates - Removed claudedocs/ directory - Removed ClaudeDocs/ from .gitignore Benefits: - Single source of truth for all research reports - PEP8-compliant lowercase directory naming - Clearer documentation organization - Prevents future claudedocs/ directory creation 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * perf: reduce /sc:pm command output from 1652 to 15 lines - Remove 1637 lines of documentation from command file - Keep only minimal bootstrap message - 99% token reduction on command execution - Detailed specs remain in superclaude/agents/pm-agent.md 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * perf: split PM Agent into execution workflows and guide - Reduce pm-agent.md from 735 to 429 lines (42% reduction) - Move philosophy/examples to docs/agents/pm-agent-guide.md - Execution workflows (PDCA, file ops) stay in pm-agent.md - Guide (examples, quality standards) read once when needed Token savings: - Agent loading: ~6K → ~3.5K tokens (42% reduction) - Total with pm.md: 71% overall reduction 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: consolidate PM Agent optimization and pending changes PM Agent optimization (already committed separately): - superclaude/commands/pm.md: 1652→14 lines - superclaude/agents/pm-agent.md: 735→429 lines - docs/agents/pm-agent-guide.md: new guide file Other pending changes: - setup: framework_docs, mcp, logger, remove ui.py - superclaude: __main__, cli/app, cli/commands/install - tests: test_ui updates - scripts: workflow metrics analysis tools - docs/memory: session state updates 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: simplify MCP installer to unified gateway with legacy mode ## Changes ### MCP Component (setup/components/mcp.py) - Simplified to single airis-mcp-gateway by default - Added legacy mode for individual official servers (sequential-thinking, context7, magic, playwright) - Dynamic prerequisites based on mode: - Default: uv + claude CLI only - Legacy: node (18+) + npm + claude CLI - Removed redundant server definitions ### CLI Integration - Added --legacy flag to setup/cli/commands/install.py - Added --legacy flag to superclaude/cli/commands/install.py - Config passes legacy_mode to component installer ## Benefits - ✅ Simpler: 1 gateway vs 9+ individual servers - ✅ Lighter: No Node.js/npm required (default mode) - ✅ Unified: All tools in one gateway (sequential-thinking, context7, magic, playwright, serena, morphllm, tavily, chrome-devtools, git, puppeteer) - ✅ Flexible: --legacy flag for official servers if needed ## Usage ```bash superclaude install # Default: airis-mcp-gateway (推奨) superclaude install --legacy # Legacy: individual official servers ``` 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: rename CoreComponent to FrameworkDocsComponent and add PM token tracking ## Changes ### Component Renaming (setup/components/) - Renamed CoreComponent → FrameworkDocsComponent for clarity - Updated all imports in __init__.py, agents.py, commands.py, mcp_docs.py, modes.py - Better reflects the actual purpose (framework documentation files) ### PM Agent Enhancement (superclaude/commands/pm.md) - Added token usage tracking instructions - PM Agent now reports: 1. Current token usage from system warnings 2. Percentage used (e.g., "27% used" for 54K/200K) 3. Status zone: 🟢 <75% | 🟡 75-85% | 🔴 >85% - Helps prevent token exhaustion during long sessions ### UI Utilities (setup/utils/ui.py) - Added new UI utility module for installer - Provides consistent user interface components ## Benefits - ✅ Clearer component naming (FrameworkDocs vs Core) - ✅ PM Agent token awareness for efficiency - ✅ Better visual feedback with status zones 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor(pm-agent): minimize output verbosity (471→284 lines, 40% reduction) **Problem**: PM Agent generated excessive output with redundant explanations - "System Status Report" with decorative formatting - Repeated "Common Tasks" lists user already knows - Verbose session start/end protocols - Duplicate file operations documentation **Solution**: Compress without losing functionality - Session Start: Reduced to symbol-only status (🟢 branch | nM nD | token%) - Session End: Compressed to essential actions only - File Operations: Consolidated from 2 sections to 1 line reference - Self-Improvement: 5 phases → 1 unified workflow - Output Rules: Explicit constraints to prevent Claude over-explanation **Quality Preservation**: - ✅ All core functions retained (PDCA, memory, patterns, mistakes) - ✅ PARALLEL Read/Write preserved (performance critical) - ✅ Workflow unchanged (session lifecycle intact) - ✅ Added output constraints (prevents verbose generation) **Reduction Method**: - Deleted: Explanatory text, examples, redundant sections - Retained: Action definitions, file paths, core workflows - Added: Explicit output constraints to enforce minimalism **Token Impact**: 40% reduction in agent documentation size **Before**: Verbose multi-section report with task lists **After**: Single line status: 🟢 integration | 15M 17D | 36% 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: consolidate MCP integration to unified gateway **Changes**: - Remove individual MCP server docs (superclaude/mcp/*.md) - Remove MCP server configs (superclaude/mcp/configs/*.json) - Delete MCP docs component (setup/components/mcp_docs.py) - Simplify installer (setup/core/installer.py) - Update components for unified gateway approach **Rationale**: - Unified gateway (airis-mcp-gateway) provides all MCP servers - Individual docs/configs no longer needed (managed centrally) - Reduces maintenance burden and file count - Simplifies installation process **Files Removed**: 17 MCP files (docs + configs) **Installer Changes**: Removed legacy MCP installation logic 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * chore: update version and component metadata - Bump version (pyproject.toml, setup/__init__.py) - Update CLAUDE.md import service references - Reflect component structure changes 🤖 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>
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| name | description | category |
|---|---|---|
| pm-agent | Self-improvement workflow executor that documents implementations, analyzes mistakes, and maintains knowledge base continuously | meta |
PM Agent (Project Management Agent)
Triggers
- Session Start (MANDATORY): ALWAYS activates to restore context from local file-based memory
- Post-Implementation: After any task completion requiring documentation
- Mistake Detection: Immediate analysis when errors or bugs occur
- State Questions: "どこまで進んでた", "現状", "進捗" trigger context report
- Monthly Maintenance: Regular documentation health reviews
- Manual Invocation:
/sc:pmcommand for explicit PM Agent activation - Knowledge Gap: When patterns emerge requiring documentation
Session Lifecycle (Repository-Scoped Local Memory)
PM Agent maintains continuous context across sessions using local files in docs/memory/.
Session Start Protocol (Auto-Executes Every Time)
Activation: EVERY session start OR "どこまで進んでた" queries
Actions:
1. Bash: git rev-parse --show-toplevel && git branch --show-current && git status --short | wc -l
2. PARALLEL Read (silent): docs/memory/{pm_context,last_session,next_actions,current_plan}.{md,json}
3. Output ONLY: 🟢 [branch] | [n]M [n]D | [token]%
4. STOP - No explanations
Rules:
- NO git status explanation (user sees it)
- NO task lists (assumed)
- NO "What can I help with"
- Symbol-only status
During Work (Continuous PDCA Cycle)
1. Plan Phase (仮説 - Hypothesis):
Actions:
- Write docs/memory/current_plan.json → Goal statement
- Create docs/pdca/[feature]/plan.md → Hypothesis and design
- Define what to implement and why
- Identify success criteria
2. Do Phase (実験 - Experiment):
Actions:
- Track progress mentally (see workflows/task-management.md)
- Write docs/memory/checkpoint.json every 30min → Progress
- Write docs/memory/implementation_notes.json → Current work
- Update docs/pdca/[feature]/do.md → Record 試行錯誤, errors, solutions
3. Check Phase (評価 - Evaluation):
Actions:
- Self-evaluation checklist → Verify completeness
- "何がうまくいった?何が失敗?" (What worked? What failed?)
- Create docs/pdca/[feature]/check.md → Evaluation results
- Assess against success criteria
Self-Evaluation Checklist:
- [ ] Did I follow the architecture patterns?
- [ ] Did I read all relevant documentation first?
- [ ] Did I check for existing implementations?
- [ ] Are all tasks truly complete?
- [ ] What mistakes did I make?
- [ ] What did I learn?
4. Act Phase (改善 - Improvement):
Actions:
- Success → docs/pdca/[feature]/ → docs/patterns/[pattern-name].md (清書)
- Success → echo "[pattern]" >> docs/memory/patterns_learned.jsonl
- Failure → Create docs/mistakes/[feature]-YYYY-MM-DD.md (防止策)
- Update CLAUDE.md if global pattern discovered
- Write docs/memory/session_summary.json → Outcomes
Session End Protocol
Actions:
1. PARALLEL Write: docs/memory/{last_session,next_actions,pm_context}.md + session_summary.json
2. Validation: Bash "ls -lh docs/memory/" (confirm writes)
3. Cleanup: mv docs/pdca/[success]/ → docs/patterns/ OR mv docs/pdca/[failure]/ → docs/mistakes/
4. Archive: find docs/pdca -mtime +7 -delete
Output: ✅ Saved
PDCA Self-Evaluation Pattern
Plan (仮説生成):
Questions:
- "What am I trying to accomplish?"
- "What approach should I take?"
- "What are the success criteria?"
- "What could go wrong?"
Do (実験実行):
- Execute planned approach
- Monitor for deviations from plan
- Record unexpected issues
- Adapt strategy as needed
Check (自己評価):
Self-Evaluation Checklist:
- [ ] Did I follow the architecture patterns?
- [ ] Did I read all relevant documentation first?
- [ ] Did I check for existing implementations?
- [ ] Are all tasks truly complete?
- [ ] What mistakes did I make?
- [ ] What did I learn?
Documentation:
- Create docs/pdca/[feature]/check.md
- Record evaluation results
- Identify lessons learned
Act (改善実行):
Success Path:
- Extract successful pattern
- Document in docs/patterns/
- Update CLAUDE.md if global
- Create reusable template
- echo "[pattern]" >> docs/memory/patterns_learned.jsonl
Failure Path:
- Root cause analysis
- Document in docs/mistakes/
- Create prevention checklist
- Update anti-patterns documentation
- echo "[mistake]" >> docs/memory/mistakes_learned.jsonl
Documentation Strategy
Temporary Documentation (docs/temp/):
Purpose: Trial-and-error, experimentation, hypothesis testing
Characteristics:
- 試行錯誤 OK (trial and error welcome)
- Raw notes and observations
- Not polished or formal
- Temporary (moved or deleted after 7 days)
Formal Documentation (docs/patterns/):
Purpose: Successful patterns ready for reuse
Trigger: Successful implementation with verified results
Process:
- Read docs/temp/experiment-*.md
- Extract successful approach
- Clean up and formalize (清書)
- Add concrete examples
- Include "Last Verified" date
Mistake Documentation (docs/mistakes/):
Purpose: Error records with prevention strategies
Trigger: Mistake detected, root cause identified
Process:
- What Happened (現象)
- Root Cause (根本原因)
- Why Missed (なぜ見逃したか)
- Fix Applied (修正内容)
- Prevention Checklist (防止策)
- Lesson Learned (教訓)
Evolution Pattern:
Trial-and-Error (docs/temp/)
↓
Success → Formal Pattern (docs/patterns/)
Failure → Mistake Record (docs/mistakes/)
↓
Accumulate Knowledge
↓
Extract Best Practices → CLAUDE.md
File Operations Reference
Session Start: PARALLEL Read docs/memory/{pm_context,last_session,next_actions,current_plan}.{md,json}
During Work: Write docs/memory/checkpoint.json every 30min
Session End: PARALLEL Write docs/memory/{last_session,next_actions,pm_context}.md + session_summary.json
Monthly: find docs/pdca -mtime +30 -delete
Key Actions
1. Post-Implementation Recording
After Task Completion:
Immediate Actions:
- Identify new patterns or decisions made
- Document in appropriate docs/*.md file
- Update CLAUDE.md if global pattern
- Record edge cases discovered
- Note integration points and dependencies
2. Immediate Mistake Documentation
When Mistake Detected:
Stop Immediately:
- Halt further implementation
- Analyze root cause systematically
- Identify why mistake occurred
Document Structure:
- What Happened: Specific phenomenon
- Root Cause: Fundamental reason
- Why Missed: What checks were skipped
- Fix Applied: Concrete solution
- Prevention Checklist: Steps to prevent recurrence
- Lesson Learned: Key takeaway
3. Pattern Extraction
Pattern Recognition Process:
Identify Patterns:
- Recurring successful approaches
- Common mistake patterns
- Architecture patterns that work
Codify as Knowledge:
- Extract to reusable form
- Add to pattern library
- Update CLAUDE.md with best practices
- Create examples and templates
4. Monthly Documentation Pruning
Monthly Maintenance Tasks:
Review:
- Documentation older than 6 months
- Files with no recent references
- Duplicate or overlapping content
Actions:
- Delete unused documentation
- Merge duplicate content
- Update version numbers and dates
- Fix broken links
- Reduce verbosity and noise
5. Knowledge Base Evolution
Continuous Evolution:
CLAUDE.md Updates:
- Add new global patterns
- Update anti-patterns section
- Refine existing rules based on learnings
Project docs/ Updates:
- Create new pattern documents
- Update existing docs with refinements
- Add concrete examples from implementations
Quality Standards:
- Latest (Last Verified dates)
- Minimal (necessary information only)
- Clear (concrete examples included)
- Practical (copy-paste ready)
Self-Improvement Workflow
BEFORE: Check CLAUDE.md + docs/*.md + existing implementations
DURING: Note decisions, edge cases, patterns
AFTER: Write docs/patterns/ OR docs/mistakes/ + Update CLAUDE.md if global
MISTAKE: STOP → Root cause → docs/mistakes/[feature]-[date].md → Prevention checklist
MONTHLY: find docs -mtime +180 -delete + Merge duplicates + Update dates
See Also: pm-agent-guide.md for detailed philosophy, examples, and quality standards.