mirror of
https://github.com/SuperClaude-Org/SuperClaude_Framework.git
synced 2025-12-23 04:36:21 +00:00
* docs: fix mindbase syntax and document as optional MCP enhancement Fix incorrect method call syntax and clarify mindbase as optional enhancement that coexists with built-in ReflexionMemory. Changes: - Fix syntax: mindbase.search_conversations() → natural language instructions that allow Claude to autonomously select tools - Clarify mindbase requires airis-mcp-gateway "recommended" profile - Document ReflexionMemory as built-in fallback (always available) - Show coexistence model: both systems work together Architecture: - ReflexionMemory (built-in): Keyword-based search, local JSONL - Mindbase (optional MCP): Semantic search, PostgreSQL + pgvector - Claude autonomously selects best available tool when needed This approach allows users to enhance error learning with mindbase when installed, while maintaining full functionality with ReflexionMemory alone. Related: #452 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add comprehensive ReflexionMemory user documentation Add user-facing documentation for the ReflexionMemory error learning system to address documentation gap identified during mindbase cleanup. New Documentation: - docs/user-guide/memory-system.md (283 lines) * Complete user guide for ReflexionMemory * How it works, storage format, usage examples * Performance benefits and troubleshooting * Manual inspection and management commands - docs/memory/reflexion.jsonl.example (15 entries) * 15 realistic example reflexion entries * Covers common scenarios: auth, DB, CORS, uploads, etc. * Reference for understanding the data format - docs/memory/README.md (277 lines) * Overview of memory directory structure * Explanation of all files (reflexion, metrics, patterns) * File management, backup, and git guidelines * Quick command reference Context: Previous mindbase cleanup removed references to non-existent external MCP server, but didn't add sufficient user-facing documentation for the actual ReflexionMemory implementation. Related: #452 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: translate Japanese text to English in documentation Address PR feedback to remove Japanese text from English documentation files. Changes: - docs/mcp/mcp-integration-policy.md: Translate headers and descriptions - docs/reference/pm-agent-autonomous-reflection.md: Translate error messages - docs/research/reflexion-integration-2025.md: Translate error messages - docs/memory/pm_context.md: Translate example keywords All Japanese text in English documentation files has been translated to English. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com>
534 lines
13 KiB
Markdown
534 lines
13 KiB
Markdown
# MCP Integration Policy
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Integration policy and usage guidelines for MCP (Model Context Protocol) servers in SuperClaude Framework.
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## MCP Server Definitions
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### Core MCP Servers
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#### Memory & Error Learning
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**ReflexionMemory (Built-in, Always Available)**
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```yaml
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Name: ReflexionMemory
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Purpose: Error history storage and learning
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Category: Memory Management (Built-in)
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Auto-Managed: true (internal implementation)
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PM Agent Role: Automatically used on errors
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Capabilities:
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- Memory of past errors and solutions
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- Keyword-based similar error search
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- Learning to prevent recurrence
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- Project-scoped memory
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Implementation:
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Location: superclaude/core/pm_init/reflexion_memory.py
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Storage: docs/memory/reflexion.jsonl (local file)
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Search: Keyword-based (50% overlap threshold)
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Note: This is an internal implementation, not an external MCP server
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```
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**Mindbase MCP (Optional Enhancement via airis-mcp-gateway)**
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```yaml
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Name: mindbase
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Purpose: Semantic search across all conversation history
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Category: Memory Management (Optional MCP)
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Auto-Managed: false (external MCP server - requires installation)
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PM Agent Role: Automatically selected by Claude when available
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Capabilities:
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- Persistence of all conversation history (PostgreSQL + pgvector)
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- Semantic search (qwen3-embedding:8b)
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- Cross-project knowledge sharing
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- Learning from all past conversations
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Tools:
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- mindbase_search: Semantic search
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- mindbase_store: Conversation storage
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- mindbase_health: Health check
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Installation:
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Requires: airis-mcp-gateway with "recommended" profile
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See: https://github.com/agiletec-inc/airis-mcp-gateway
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Profile Dependency:
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- "recommended" profile: mindbase included (long-term projects)
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- "minimal" profile: mindbase NOT included (lightweight, quick tasks)
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Usage Pattern:
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- With installation + recommended profile: Claude automatically uses it
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- Otherwise: Falls back to ReflexionMemory
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- PM Agent instructs: "Search past errors" (Claude selects tool)
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Note: Optional enhancement. SuperClaude works fully with ReflexionMemory alone.
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```
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#### Serena MCP
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```yaml
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Name: serena
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Purpose: コードベース理解のためのシンボル管理
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Category: Code Understanding
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Auto-Managed: false (明示的使用)
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PM Agent Role: コード理解タスクで自動活用
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Capabilities:
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- シンボル追跡(関数、クラス、変数)
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- コード構造分析
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- リファクタリング支援
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- 依存関係マッピング
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Lifecycle:
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Start: 何もしない
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During: コード理解時に使用
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End: 自動削除(セッション終了)
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Cleanup: 自動
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Usage Pattern:
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Use Cases:
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- リファクタリング計画
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- コード構造分析
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- シンボル間の関係追跡
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- 大規模コードベース探索
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NOT for:
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- タスク管理
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- 会話記憶
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- ドキュメント保存
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- プロジェクト知識管理
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Trigger Conditions:
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- Keywords: "refactor", "analyze code structure", "find all usages"
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- File Count: >10 files involved
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- Complexity: Cross-file symbol tracking needed
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Example:
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Task: "Refactor authentication system across 15 files"
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→ Serena: Track auth-related symbols
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→ PM Agent: Coordinate refactoring with Serena insights
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```
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#### Sequential MCP
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```yaml
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Name: sequential-thinking
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Purpose: 複雑な推論と段階的分析
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Category: Reasoning Engine
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Auto-Managed: false (明示的使用)
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PM Agent Role: Commander modeで複雑タスク分析
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Capabilities:
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- 段階的推論
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- 仮説検証
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- 複雑な問題分解
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- システム設計分析
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Lifecycle:
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Start: 何もしない
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During: 複雑分析時に使用
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End: 分析結果を返す
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Cleanup: 自動
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Usage Pattern:
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Use Cases:
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- アーキテクチャ設計
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- 複雑なバグ分析
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- システム設計レビュー
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- トレードオフ分析
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NOT for:
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- 単純なタスク
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- 直感的に解決できる問題
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- コード生成(分析のみ)
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Trigger Conditions:
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- Keywords: "design", "architecture", "analyze tradeoffs"
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- Complexity: Multi-component system analysis
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- Uncertainty: Multiple valid approaches exist
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Example:
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Task: "Design microservices architecture for authentication"
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→ Sequential: Step-by-step design analysis
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→ PM Agent: Document design decisions in docs/patterns/
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```
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#### Context7 MCP
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```yaml
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Name: context7
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Purpose: 公式ドキュメントとライブラリパターン参照
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Category: Documentation Reference
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Auto-Managed: false (明示的使用)
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PM Agent Role: Pre-Implementation Confidence Check
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Capabilities:
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- 公式ドキュメント検索
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- ライブラリベストプラクティス
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- API仕様確認
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- フレームワークパターン
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Lifecycle:
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Start: 何もしない
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During: ドキュメント参照時に使用
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End: 情報を返す
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Cleanup: 自動
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Usage Pattern:
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Use Cases:
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- ライブラリの使い方確認
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- ベストプラクティス参照
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- API仕様確認
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- 公式パターン学習
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NOT for:
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- プロジェクト固有ドキュメント(docs/使用)
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- 社内ドキュメント
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- カスタム実装パターン
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Trigger Conditions:
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- Pre-Implementation: Confidence check時
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- Keywords: "official docs", "best practices", "how to use [library]"
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- New Library: 初めて使うライブラリ
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Example:
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Task: "Implement JWT authentication with jose library"
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→ Context7: Fetch jose official docs and patterns
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→ PM Agent: Verify implementation against official patterns
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```
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#### Tavily MCP
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```yaml
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Name: tavily
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Purpose: Web検索とリアルタイム情報取得
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Category: Research
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Auto-Managed: false (明示的使用)
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PM Agent Role: Research modeで情報収集
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Capabilities:
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- Web検索
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- 最新情報取得
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- 技術記事検索
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- エラーメッセージ検索
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Lifecycle:
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Start: 何もしない
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During: 研究・調査時に使用
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End: 検索結果を返す
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Cleanup: 自動
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Usage Pattern:
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Use Cases:
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- 最新のライブラリバージョン確認
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- エラーメッセージの解決策検索
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- 技術トレンド調査
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- 公式ドキュメント検索(Context7にない場合)
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NOT for:
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- プロジェクト内情報(Grep使用)
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- コードベース検索(Serena使用)
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- 過去の会話(Mindbase使用)
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Trigger Conditions:
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- Keywords: "search", "latest", "current"
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- Error: Unknown error message
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- Research: New technology investigation
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Example:
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Task: "Find latest Next.js 15 App Router patterns"
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→ Tavily: Search web for latest patterns
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→ PM Agent: Document findings in docs/patterns/
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```
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## MCP Selection Matrix
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### By Task Type
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```yaml
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Code Understanding:
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Primary: Serena MCP
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Secondary: Grep (simple searches)
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Example: "Find all authentication-related symbols"
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Complex Analysis:
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Primary: Sequential MCP
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Secondary: Native reasoning (simple cases)
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Example: "Design authentication architecture"
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Documentation Reference:
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Primary: Context7 MCP
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Secondary: Tavily (if not in Context7)
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Example: "How to use React Server Components"
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Research & Investigation:
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Primary: Tavily MCP
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Secondary: Context7 (official docs)
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Example: "Latest security best practices 2025"
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Memory & History:
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Primary: Mindbase MCP (automatic)
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Secondary: None (fully automated)
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Example: N/A (transparent)
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Task Management:
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Primary: TodoWrite (built-in)
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Secondary: None
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Example: Track multi-step implementation
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```
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### By Complexity Level
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```yaml
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Simple (1-2 files, clear path):
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MCPs: None (native tools sufficient)
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Tools: Read, Edit, Grep, Bash
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Medium (3-10 files, some complexity):
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MCPs: Context7 (if new library)
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Tools: MultiEdit, Glob, Grep
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Complex (>10 files, architectural changes):
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MCPs: Serena + Sequential
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Coordination: PM Agent Commander mode
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Tools: Task delegation, parallel execution
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Research (information gathering):
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MCPs: Tavily + Context7
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Mode: DeepResearch mode
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Tools: WebFetch (selective)
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```
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## PM Agent Integration Rules
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### Session Lifecycle
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```yaml
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Session Start:
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Auto-Execute:
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1. git status && git branch
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2. Read CLAUDE.md
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3. Read docs/patterns/*.md (latest 5)
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4. Mindbase auto-load (automatic)
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MCPs Used:
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- Mindbase: Automatic (no explicit call)
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- Others: None (wait for task)
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Output: 📍 [branch] | [status] | 🧠 [token]%
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Pre-Implementation:
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Auto-Execute:
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1. Read relevant docs/patterns/
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2. Read relevant docs/mistakes/
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3. Confidence check
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MCPs Used:
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- Context7: If new library (automatic)
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- Serena: If complex refactor (automatic)
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Decision:
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High Confidence (>90%): Proceed
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Medium (70-89%): Present options
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Low (<70%): Stop, request clarification
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During Implementation:
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Manual Trigger:
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- TodoWrite: Progress tracking
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- Serena: Code understanding (if needed)
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- Sequential: Complex analysis (if needed)
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MCPs Used:
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- Serena: On code complexity trigger
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- Sequential: On analysis keyword
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- Context7: On documentation need
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Post-Implementation:
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Auto-Execute:
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1. Self-evaluation (Four Questions)
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2. Pattern extraction
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3. Documentation update
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MCPs Used:
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- Mindbase: Automatic save
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- Others: None (file-based documentation)
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Output:
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- Success → docs/patterns/
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- Failure → docs/mistakes/
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- Global → CLAUDE.md
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```
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### MCP Activation Triggers
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```yaml
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Serena MCP:
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Auto-Trigger Keywords:
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- "refactor"
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- "analyze code structure"
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- "find all usages"
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- "symbol tracking"
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Auto-Trigger Conditions:
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- File count > 10
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- Cross-file changes
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- Symbol renaming
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- Dependency analysis
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Manual Override: --serena flag
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Sequential MCP:
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Auto-Trigger Keywords:
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- "design"
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- "architecture"
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- "analyze tradeoffs"
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- "complex problem"
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Auto-Trigger Conditions:
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- System design task
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- Multiple valid approaches
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- Uncertainty in implementation
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- Architectural decision
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Manual Override: --seq flag
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Context7 MCP:
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Auto-Trigger Keywords:
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- "official docs"
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- "best practices"
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- "how to use [library]"
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- New library detected
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Auto-Trigger Conditions:
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- Pre-Implementation confidence check
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- New library in package.json
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- Framework pattern needed
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Manual Override: --c7 flag
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Tavily MCP:
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Auto-Trigger Keywords:
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- "search"
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- "latest"
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- "current trends"
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- "find error solution"
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Auto-Trigger Conditions:
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- Research mode active
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- Unknown error message
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- Latest version check
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Manual Override: --tavily flag
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```
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## Anti-Patterns (禁止事項)
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### DO NOT
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```yaml
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❌ Mindbaseを明示的に操作:
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Reason: 完全自動管理、PM Agentは触らない
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Instead: 何もしない(自動で動く)
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❌ Serenaをタスク管理に使用:
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Reason: コード理解専用
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Instead: TodoWrite使用
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❌ write_memory() / read_memory() 使用:
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Reason: Serenaはコード理解専用、タスク管理ではない
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Instead: TodoWrite + docs/
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❌ docs/memory/ ディレクトリ作成:
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Reason: Mindbaseと重複
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Instead: docs/patterns/ と docs/mistakes/ 使用
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❌ 全タスクでSequential使用:
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Reason: トークン浪費
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Instead: 複雑分析時のみ
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❌ Context7をプロジェクトドキュメントに使用:
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Reason: 公式ドキュメント専用
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Instead: Read docs/ 使用
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```
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## Best Practices
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### Efficient MCP Usage
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```yaml
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✅ Right Tool for Right Job:
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Simple → Native tools (Read, Edit, Grep)
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Medium → Context7 (new library)
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Complex → Serena + Sequential
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✅ Lazy Evaluation:
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Don't preload MCPs
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Activate only when needed
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Let PM Agent auto-trigger
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✅ Clear Separation:
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Memory: Mindbase (automatic)
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Knowledge: docs/ (file-based)
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Progress: TodoWrite (session)
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Code: Serena (understanding)
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✅ Documentation First:
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Pre-Implementation: Context7 + docs/patterns/
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During: TodoWrite tracking
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Post: docs/patterns/ or docs/mistakes/
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```
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## Testing & Validation
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### MCP Integration Tests
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```yaml
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Test Cases:
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1. Mindbase Auto-Load:
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- Start session
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- Verify past context loaded automatically
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- No explicit mindbase calls
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2. Serena Code Understanding:
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- Task: "Refactor auth across 15 files"
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- Verify Serena auto-triggered
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- Verify symbol tracking used
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3. Sequential Complex Analysis:
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- Task: "Design microservices architecture"
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- Verify Sequential auto-triggered
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- Verify step-by-step reasoning
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4. Context7 Documentation:
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- Task: "Implement with new library"
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- Verify Context7 auto-triggered
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- Verify official docs referenced
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5. Tavily Research:
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- Task: "Find latest security patterns"
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- Verify Tavily auto-triggered
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- Verify web search executed
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```
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## Migration Checklist
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```yaml
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From Old System:
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- [ ] Remove docs/memory/ references
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- [ ] Remove write_memory() / read_memory() calls
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- [ ] Remove MODE_Task_Management.md memory sections
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- [ ] Update pm-agent.md with new MCP policy
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To New System:
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- [ ] Add MCP integration policy docs
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- [ ] Update pm-agent.md triggers
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- [ ] Add auto-activation logic
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- [ ] Test MCP selection matrix
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- [ ] Validate anti-patterns enforcement
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```
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## References
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- PM Agent: `~/.claude/superclaude/agents/pm-agent.md`
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- Modes: `~/.claude/superclaude/modes/MODE_*.md`
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- Rules: `~/.claude/superclaude/framework/rules.md`
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- Memory Cleanup: `docs/architecture/pm-agent-responsibility-cleanup.md`
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