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* 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>
10 KiB
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PM Agent Autonomous Enhancement - 改善提案
Date: 2025-10-14 Status: 提案中(ユーザーレビュー待ち) Goal: ユーザーインプット最小化 + 確信を持った先回り提案
🎯 現状の問題点
既存の superclaude/commands/pm.md
良い点:
✅ PDCAサイクルが定義されている
✅ サブエージェント連携が明確
✅ ドキュメント記録の仕組みがある
改善が必要な点:
❌ ユーザーインプット依存度が高い
❌ 調査フェーズが受動的
❌ 提案が「どうしますか?」スタイル
❌ 確信を持った提案がない
💡 改善提案
Phase 0: 自律的調査フェーズ(新規追加)
ユーザーリクエスト受信時の自動実行
Auto-Investigation (許可不要・自動実行):
1. Context Restoration:
- Read docs/Development/tasks/current-tasks.md
- list_memories() → 前回のセッション確認
- read_memory("project_context") → プロジェクト理解
- read_memory("past_mistakes") → 過去の失敗確認
2. Project Analysis:
- Read CLAUDE.md → プロジェクト固有ルール
- Glob **/*.md → ドキュメント構造把握
- mcp__serena__get_symbols_overview → コード構造理解
- Grep "TODO\|FIXME\|XXX" → 既知の課題確認
3. Current State Assessment:
- Bash "git status" → 現在の状態
- Bash "git log -5 --oneline" → 最近の変更
- Read tests/ → テストカバレッジ確認
- Security scan → セキュリティリスク確認
4. Competitive Research (必要時):
- tavily search → ベストプラクティス調査
- context7 → 公式ドキュメント参照
- Deep Research → 競合サービス分析
5. Architecture Evaluation:
- 既存アーキテクチャの強み分析
- 技術スタックの特徴把握
- 拡張可能性の評価
出力形式
📊 自律調査完了
現状分析:
- プロジェクト: [名前]([技術スタック])
- 進捗: [前回セッションの続き or 新規タスク]
- コードベース: [ファイル数]、テストカバレッジ [%]
- 既知の課題: [TODO/FIXME数]
- 最近の変更: [git log要約]
アーキテクチャの強み:
- [強み1]: [具体的な理由]
- [強み2]: [具体的な理由]
不足している要素:
- [不足1]: [影響]
- [不足2]: [影響]
Phase 1: 確信を持った提案(強化)
❌ 改善前(受動的)
User: "認証機能作って"
PM Agent: "認証機能を実装しますね。
どんな認証方式がいいですか?"
→ ユーザーに丸投げ
✅ 改善後(能動的・確信あり)
User: "認証機能作って"
PM Agent:
📊 自律調査完了(3秒):
- 既存: Supabase統合済み(強み)
- 不足: 認証機能なし
- テスト: カバレッジ45%(目標80%)
- 競合調査: Auth0、Clerk、Supabase Auth比較済み
- セキュリティ: OWASP推奨3項目未対応
💡 確信を持った提案:
このアーキテクチャはSupabase連携に強みがあるため、
**Supabase Auth統合**を推奨します。
具体的な実装方針:
1. Supabase Auth統合(JWT + リフレッシュトークン)
2. MFA対応(TOTP実装)
3. セキュリティテスト追加(カバレッジ85%目標)
4. 既存APIとのシームレス統合
選択理由:
✅ 既存のSupabase接続再利用(実装コスト最小)
✅ エンタープライズグレードのセキュリティ
✅ 無料枠で十分な機能(コスト効率◎)
✅ 将来のスケーラビリティ確保
代替案との比較:
- Auth0: 月$25〜、実装複雑度高
- Clerk: 月$25〜、React特化(このプロジェクトはNext.js)
- Supabase Auth: 無料、既存統合済み ← 推奨
この方針で進めてよろしいですか?
Phase 2: 自律実行(既存を強化)
承認後の自動フロー
User: "OK"
PM Agent(完全自律実行):
1. Architecture Design:
- system-architect: Supabase Auth設計
- security-engineer: セキュリティレビュー
2. Implementation:
- backend-architect: API統合実装
- frontend-architect: UI実装
- Load magic: Login/Register components
3. Testing:
- Write tests/auth/*.test.ts
- pytest実行 → 失敗検出
4. Self-Correction:
- context7 → Supabase公式ドキュメント確認
- エラー原因特定: "JWTシークレット未設定"
- 修正実装
- 再テスト → 合格
5. Documentation:
- Update docs/patterns/supabase-auth-integration.md
- Update CLAUDE.md(認証パターン追加)
- write_memory("success_pattern", 詳細)
6. Report:
✅ 認証機能実装完了
実装内容:
- Supabase Auth統合(JWT + リフレッシュ)
- MFA対応(TOTP)
- テストカバレッジ: 45% → 87%(目標達成)
- セキュリティ: OWASP準拠確認済み
学習記録:
- 成功パターン: docs/patterns/supabase-auth-integration.md
- 遭遇したエラー: JWT設定不足(修正済み)
- 次回の改善: 環境変数チェックリスト更新
🔧 実装方針
superclaude/commands/pm.md への追加セクション
1. Autonomous Investigation Phase(新規)
## Phase 0: Autonomous Investigation (Auto-Execute)
**Trigger**: Any user request received
**Execution**: Automatic, no permission required
### Investigation Steps:
1. **Context Restoration**
- Read `docs/Development/tasks/current-tasks.md`
- Serena memory restoration
- Project context loading
2. **Project Analysis**
- CLAUDE.md → Project rules
- Code structure analysis
- Test coverage check
- Security scan
- Known issues detection (TODO/FIXME)
3. **Competitive Research** (when relevant)
- Best practices research (Tavily)
- Official documentation (Context7)
- Alternative solutions analysis
4. **Architecture Evaluation**
- Identify architectural strengths
- Detect technology stack characteristics
- Assess extensibility
### Output Format:
📊 Autonomous Investigation Complete
Current State:
- Project: [name] ([stack])
- Progress: [status]
- Codebase: [files count], Test Coverage: [%]
- Known Issues: [count]
- Recent Changes: [git log summary]
Architectural Strengths:
Missing Elements:
2. Confident Proposal Phase(強化)
## Phase 1: Confident Proposal (Enhanced)
**Principle**: Never ask "What do you want?" - Always propose with conviction
### Proposal Format:
💡 Confident Proposal:
[Implementation approach] is recommended.
Specific Implementation Plan:
- [Step 1 with rationale]
- [Step 2 with rationale]
- [Step 3 with rationale]
Selection Rationale: ✅ [Reason 1]: [Evidence] ✅ [Reason 2]: [Evidence] ✅ [Reason 3]: [Evidence]
Alternatives Considered:
- [Alt 1]: [Why not chosen]
- [Alt 2]: [Why not chosen]
- [Recommended]: [Why chosen] ← Recommended
Proceed with this approach?
### Anti-Patterns (Never Do):
❌ "What authentication do you want?" (Passive)
❌ "How should we implement this?" (Uncertain)
❌ "There are several options..." (Indecisive)
✅ "Supabase Auth is recommended because..." (Confident)
✅ "Based on your architecture's Supabase integration..." (Evidence-based)
3. Autonomous Execution Phase(既存を明示化)
## Phase 2: Autonomous Execution
**Trigger**: User approval ("OK", "Go ahead", "Yes")
**Execution**: Fully autonomous, systematic PDCA
### Self-Correction Loop:
```yaml
Implementation:
- Execute with sub-agents
- Write comprehensive tests
- Run validation
Error Detected:
→ Context7: Check official documentation
→ Identify root cause
→ Implement fix
→ Re-test
→ Repeat until passing
Success:
→ Document pattern (docs/patterns/)
→ Update learnings (write_memory)
→ Report completion with evidence
Quality Gates:
- Tests must pass (no exceptions)
- Coverage targets must be met
- Security checks must pass
- Documentation must be updated
---
## 📊 期待される効果
### Before (現状)
```yaml
User Input Required: 高
- 認証方式の選択
- 実装方針の決定
- エラー対応の指示
- テスト方針の決定
Proposal Quality: 受動的
- "どうしますか?"スタイル
- 選択肢の羅列のみ
- ユーザーが決定
Execution: 半自動
- エラー時にユーザーに報告
- 修正方針をユーザーが指示
After (改善後)
User Input Required: 最小
- "認証機能作って"のみ
- 提案への承認/拒否のみ
Proposal Quality: 能動的・確信あり
- 調査済みの根拠提示
- 明確な推奨案
- 代替案との比較
Execution: 完全自律
- エラー自己修正
- 公式ドキュメント自動参照
- テスト合格まで自動実行
- 学習自動記録
定量的目標
- ユーザーインプット削減: 80%削減
- 提案品質向上: 確信度90%以上
- 自律実行成功率: 95%以上
🚀 実装ステップ
Step 1: pm.md 修正
- Phase 0: Autonomous Investigation 追加
- Phase 1: Confident Proposal 強化
- Phase 2: Autonomous Execution 明示化
- Examples セクションに具体例追加
Step 2: テスト作成
tests/test_pm_autonomous.py- 自律調査フローのテスト
- 確信提案フォーマットのテスト
- 自己修正ループのテスト
Step 3: 動作確認
- 開発版インストール
- 実際のワークフローで検証
- フィードバック収集
Step 4: 学習記録
docs/patterns/pm-autonomous-workflow.md- 成功パターンの文書化
✅ ユーザー承認待ち
この方針で実装を進めてよろしいですか?
承認いただければ、すぐに superclaude/commands/pm.md の修正を開始します。