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feat: comprehensive framework improvements (#447)

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* refactor(docs): move core docs into framework/business/research (move-only)

- framework/: principles, rules, flags (思想・行動規範)
- business/: symbols, examples (ビジネス領域)
- research/: config (調査設定)
- All files renamed to lowercase for consistency

* docs: update references to new directory structure

- Update ~/.claude/CLAUDE.md with new paths
- Add migration notice in core/MOVED.md
- Remove pm.md.backup
- All @superclaude/ references now point to framework/business/research/

* fix(setup): update framework_docs to use new directory structure

- Add validate_prerequisites() override for multi-directory validation
- Add _get_source_dirs() for framework/business/research directories
- Override _discover_component_files() for multi-directory discovery
- Override get_files_to_install() for relative path handling
- Fix get_size_estimate() to use get_files_to_install()
- Fix uninstall/update/validate to use install_component_subdir

Fixes installation validation errors for new directory structure.

Tested: make dev installs successfully with new structure
  - framework/: flags.md, principles.md, rules.md
  - business/: examples.md, symbols.md
  - research/: config.md

* refactor(modes): update component references for docs restructure

* chore: remove redundant docs after PLANNING.md migration

Cleanup after Self-Improvement Loop implementation:

**Deleted (21 files, ~210KB)**:
- docs/Development/ - All content migrated to PLANNING.md & TASK.md
  * ARCHITECTURE.md (15KB) → PLANNING.md
  * TASKS.md (3.7KB) → TASK.md
  * ROADMAP.md (11KB) → TASK.md
  * PROJECT_STATUS.md (4.2KB) → outdated
  * 13 PM Agent research files → archived in KNOWLEDGE.md
- docs/PM_AGENT.md - Old implementation status
- docs/pm-agent-implementation-status.md - Duplicate
- docs/templates/ - Empty directory

**Retained (valuable documentation)**:
- docs/memory/ - Active session metrics & context
- docs/patterns/ - Reusable patterns
- docs/research/ - Research reports
- docs/user-guide*/ - User documentation (4 languages)
- docs/reference/ - Reference materials
- docs/getting-started/ - Quick start guides
- docs/agents/ - Agent-specific guides
- docs/testing/ - Test procedures

**Result**:
- Eliminated redundancy after Root Documents consolidation
- Preserved all valuable content in PLANNING.md, TASK.md, KNOWLEDGE.md
- Maintained user-facing documentation structure

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

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

* refactor: relocate PM modules to commands/modules

- Move modules to superclaude/commands/modules/
- Organize command-specific modules under commands/

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

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

* feat: add self-improvement loop with 4 root documents

Implements Self-Improvement Loop based on Cursor's proven patterns:

**New Root Documents**:
- PLANNING.md: Architecture, design principles, 10 absolute rules
- TASK.md: Current tasks with priority (🔴🟡🟢⚪)
- KNOWLEDGE.md: Accumulated insights, best practices, failures
- README.md: Updated with developer documentation links

**Key Features**:
- Session Start Protocol: Read docs → Git status → Token budget → Ready
- Evidence-Based Development: No guessing, always verify
- Parallel Execution Default: Wave → Checkpoint → Wave pattern
- Mac Environment Protection: Docker-first, no host pollution
- Failure Pattern Learning: Past mistakes become prevention rules

**Cleanup**:
- Removed: docs/memory/checkpoint.json, current_plan.json (migrated to TASK.md)
- Enhanced: setup/components/commands.py (module discovery)

**Benefits**:
- LLM reads rules at session start → consistent quality
- Past failures documented → no repeats
- Progressive knowledge accumulation → continuous improvement
- 3.5x faster execution with parallel patterns

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

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

* test: validate Self-Improvement Loop workflow

Tested complete cycle: Read docs → Extract rules → Execute task → Update docs

Test Results:
- Session Start Protocol: ✅ All 6 steps successful
- Rule Extraction: ✅ 10/10 absolute rules identified from PLANNING.md
- Task Identification: ✅ Next tasks identified from TASK.md
- Knowledge Application: ✅ Failure patterns accessed from KNOWLEDGE.md
- Documentation Update: ✅ TASK.md and KNOWLEDGE.md updated with completed work
- Confidence Score: 95% (exceeds 70% threshold)

Proved Self-Improvement Loop closes: Execute → Learn → Update → Improve

* refactor: responsibility-driven component architecture

Rename components to reflect their responsibilities:
- framework_docs.py → knowledge_base.py (KnowledgeBaseComponent)
- modes.py → behavior_modes.py (BehaviorModesComponent)
- agents.py → agent_personas.py (AgentPersonasComponent)
- commands.py → slash_commands.py (SlashCommandsComponent)
- mcp.py → mcp_integration.py (MCPIntegrationComponent)

Each component now clearly documents its responsibility:
- knowledge_base: Framework knowledge initialization
- behavior_modes: Execution mode definitions
- agent_personas: AI agent personality definitions
- slash_commands: CLI command registration
- mcp_integration: External tool integration

Benefits:
- Self-documenting architecture
- Clear responsibility boundaries
- Easy to navigate and extend
- Scalable for future hierarchical organization

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

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

* docs: add project-specific CLAUDE.md with UV rules

- Document UV as required Python package manager
- Add common operations and integration examples
- Document project structure and component architecture
- Provide development workflow guidelines

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

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

* fix: resolve installation failures after framework_docs rename

## Problems Fixed
1. **Syntax errors**: Duplicate docstrings in all component files (line 1)
2. **Dependency mismatch**: Stale framework_docs references after rename to knowledge_base

## Changes
- Fix docstring format in all component files (behavior_modes, agent_personas, slash_commands, mcp_integration)
- Update all dependency references: framework_docs → knowledge_base
- Update component registration calls in knowledge_base.py (5 locations)
- Update install.py files in both setup/ and superclaude/ (5 locations total)
- Fix documentation links in README-ja.md and README-zh.md

## Verification
✅ All components load successfully without syntax errors
✅ Dependency resolution works correctly
✅ Installation completes in 0.5s with all validations passing
✅ make dev succeeds

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

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

* feat: add automated README translation workflow

## New Features
- **Auto-translation workflow** using GPT-Translate
- Automatically translates README.md to Chinese (ZH) and Japanese (JA)
- Triggers on README.md changes to master/main branches
- Cost-effective: ~¥90/month for typical usage

## Implementation Details
- Uses OpenAI GPT-4 for high-quality translations
- GitHub Actions integration with gpt-translate@v1.1.11
- Secure API key management via GitHub Secrets
- Automatic commit and PR creation on translation updates

## Files Added
- `.github/workflows/translation-sync.yml` - Auto-translation workflow
- `docs/Development/translation-workflow.md` - Setup guide and documentation

## Setup Required
Add `OPENAI_API_KEY` to GitHub repository secrets to enable auto-translation.

## Benefits
- 🤖 Automated translation on every README update
- 💰 Low cost (~$0.06 per translation)
- 🛡️ Secure API key storage
- 🔄 Consistent translation quality across languages

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

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

* fix(mcp): update airis-mcp-gateway URL to correct organization

Fixes #440

## Problem
Code referenced non-existent `oraios/airis-mcp-gateway` repository,
causing MCP installation to fail completely.

## Root Cause
- Repository was moved to organization: `agiletec-inc/airis-mcp-gateway`
- Old reference `oraios/airis-mcp-gateway` no longer exists
- Users reported "not a python/uv module" error

## Changes
- Update install_command URL: oraios → agiletec-inc
- Update run_command URL: oraios → agiletec-inc
- Location: setup/components/mcp_integration.py lines 37-38

## Verification
✅ Correct URL now references active repository
✅ MCP installation will succeed with proper organization
✅ No other code references oraios/airis-mcp-gateway

## Related Issues
- Fixes #440 (Airis-mcp-gateway url has changed)
- Related to #442 (MCP update issues)

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

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

* feat: replace cloud translation with local Neural CLI

## Changes

### Removed (OpenAI-dependent)
- ❌ `.github/workflows/translation-sync.yml` - GPT-Translate workflow
- ❌ `docs/Development/translation-workflow.md` - OpenAI setup docs

### Added (Local Ollama-based)
- ✅ `Makefile`: New `make translate` target using Neural CLI
- ✅ `docs/Development/translation-guide.md` - Neural CLI guide

## Benefits

**Before (GPT-Translate)**:
- 💰 Monthly cost: ~¥90 (OpenAI API)
- 🔑 Requires API key setup
- 🌐 Data sent to external API
- ⏱️ Network latency

**After (Neural CLI)**:
- ✅ **$0 cost** - Fully local execution
- ✅ **No API keys** - Zero setup friction
- ✅ **Privacy** - No external data transfer
- ✅ **Fast** - ~1-2 min per README
- ✅ **Offline capable** - Works without internet

## Technical Details

**Neural CLI**:
- Built in Rust with Tauri
- Uses Ollama + qwen2.5:3b model
- Binary size: 4.0MB
- Auto-installs to ~/.local/bin/

**Usage**:
```bash
make translate  # Translates README.md → README-zh.md, README-ja.md
```

## Requirements

- Ollama installed: `curl -fsSL https://ollama.com/install.sh | sh`
- Model downloaded: `ollama pull qwen2.5:3b`
- Neural CLI built: `cd ~/github/neural/src-tauri && cargo build --bin neural-cli --release`

🤖 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>
This commit is contained in:
kazuki nakai
2025-10-18 23:58:10 +09:00
committed by GitHub
parent 882a0d8356
commit 00706f0ea9
52 changed files with 3277 additions and 6487 deletions
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docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md
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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`
```yaml
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
```yaml
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
```markdown
📊 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
```yaml
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）
```markdown
## 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:
- [strength 1]: [rationale]
- [strength 2]: [rationale]
Missing Elements:
- [gap 1]: [impact]
- [gap 2]: [impact]
```
```
#### 2. Confident Proposal Phase（強化）
```markdown
## 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:
1. [Step 1 with rationale]
2. [Step 2 with rationale]
3. [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）
```markdown
## 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)
```yaml
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。