mirror of
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refactor: PEP8 compliance - directory rename and code formatting (#425)
* fix(orchestration): add WebFetch auto-trigger for infrastructure configuration Problem: Infrastructure configuration changes (e.g., Traefik port settings) were being made based on assumptions without consulting official documentation, violating the 'Evidence > assumptions' principle in PRINCIPLES.md. Solution: - Added Infrastructure Configuration Validation section to MODE_Orchestration.md - Auto-triggers WebFetch for infrastructure tools (Traefik, nginx, Docker, etc.) - Enforces MODE_DeepResearch activation for investigation - BLOCKS assumption-based configuration changes Testing: Verified WebFetch successfully retrieves Traefik official docs (port 80 default) This prevents production outages from infrastructure misconfiguration by ensuring all technical recommendations are backed by official documentation. * feat: Add PM Agent (Project Manager Agent) for seamless orchestration Introduces PM Agent as the default orchestration layer that coordinates all sub-agents and manages workflows automatically. Key Features: - Default orchestration: All user interactions handled by PM Agent - Auto-delegation: Intelligent sub-agent selection based on task analysis - Docker Gateway integration: Zero-token baseline with dynamic MCP loading - Self-improvement loop: Automatic documentation of patterns and mistakes - Optional override: Users can specify sub-agents explicitly if desired Architecture: - Agent spec: SuperClaude/Agents/pm-agent.md - Command: SuperClaude/Commands/pm.md - Updated docs: README.md (15→16 agents), agents.md (new Orchestration category) User Experience: - Default: PM Agent handles everything (seamless, no manual routing) - Optional: Explicit --agent flag for direct sub-agent access - Both modes available simultaneously (no user downside) Implementation Status: - ✅ Specification complete - ✅ Documentation complete - ⏳ Prototype implementation needed - ⏳ Docker Gateway integration needed - ⏳ Testing and validation needed Refs: kazukinakai/docker-mcp-gateway (IRIS MCP Gateway integration) * feat: Add Agent Orchestration rules for PM Agent default activation Implements PM Agent as the default orchestration layer in RULES.md. Key Changes: - New 'Agent Orchestration' section (CRITICAL priority) - PM Agent receives ALL user requests by default - Manual override with @agent-[name] bypasses PM Agent - Agent Selection Priority clearly defined: 1. Manual override → Direct routing 2. Default → PM Agent → Auto-delegation 3. Delegation based on keywords, file types, complexity, context User Experience: - Default: PM Agent handles everything (seamless) - Override: @agent-[name] for direct specialist access - Transparent: PM Agent reports delegation decisions This establishes PM Agent as the orchestration layer while respecting existing auto-activation patterns and manual overrides. Next Steps: - Local testing in agiletec project - Iteration based on actual behavior - Documentation updates as needed * refactor(pm-agent): redesign as self-improvement meta-layer Problem Resolution: PM Agent's initial design competed with existing auto-activation for task routing, creating confusion about orchestration responsibilities and adding unnecessary complexity. Design Change: Redefined PM Agent as a meta-layer agent that operates AFTER specialist agents complete tasks, focusing on: - Post-implementation documentation and pattern recording - Immediate mistake analysis with prevention checklists - Monthly documentation maintenance and noise reduction - Pattern extraction and knowledge synthesis Two-Layer Orchestration System: 1. Task Execution Layer: Existing auto-activation handles task routing (unchanged) 2. Self-Improvement Layer: PM Agent meta-layer handles documentation (new) Files Modified: - SuperClaude/Agents/pm-agent.md: Complete rewrite with meta-layer design - Category: orchestration → meta - Triggers: All user interactions → Post-implementation, mistakes, monthly - Behavioral Mindset: Continuous learning system - Self-Improvement Workflow: BEFORE/DURING/AFTER/MISTAKE RECOVERY/MAINTENANCE - SuperClaude/Core/RULES.md: Agent Orchestration section updated - Split into Task Execution Layer + Self-Improvement Layer - Added orchestration flow diagram - Clarified PM Agent activates AFTER task completion - README.md: Updated PM Agent description - "orchestrates all interactions" → "ensures continuous learning" - Docs/User-Guide/agents.md: PM Agent section rewritten - Section: Orchestration Agent → Meta-Layer Agent - Expertise: Project orchestration → Self-improvement workflow executor - Examples: Task coordination → Post-implementation documentation - PR_DOCUMENTATION.md: Comprehensive PR documentation added - Summary, motivation, changes, testing, breaking changes - Two-layer orchestration system diagram - Verification checklist Integration Validated: Tested with agiletec project's self-improvement-workflow.md: ✅ PM Agent aligns with existing BEFORE/DURING/AFTER/MISTAKE RECOVERY phases ✅ Complements (not competes with) existing workflow ✅ agiletec workflow defines WHAT, PM Agent defines WHO executes it Breaking Changes: None - Existing auto-activation continues unchanged - Specialist agents unaffected - User workflows remain the same - New capability: Automatic documentation and knowledge maintenance Value Proposition: Transforms SuperClaude into a continuously learning system that accumulates knowledge, prevents recurring mistakes, and maintains fresh documentation without manual intervention. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add Claude Code conversation history management research Research covering .jsonl file structure, performance impact, and retention policies. Content: - Claude Code .jsonl file format and message types - Performance issues from GitHub (memory leaks, conversation compaction) - Retention policies (consumer vs enterprise) - Rotation recommendations based on actual data - File history snapshot tracking mechanics Source: Moved from agiletec project (research applicable to all Claude Code projects) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat: add Development documentation structure Phase 1: Documentation Structure complete - Add Docs/Development/ directory for development documentation - Add ARCHITECTURE.md - System architecture with PM Agent meta-layer - Add ROADMAP.md - 5-phase development plan with checkboxes - Add TASKS.md - Daily task tracking with progress indicators - Add PROJECT_STATUS.md - Current status dashboard and metrics - Add pm-agent-integration.md - Implementation guide for PM Agent mode This establishes comprehensive documentation foundation for: - System architecture understanding - Development planning and tracking - Implementation guidance - Progress visibility Related: #pm-agent-mode #documentation #phase-1 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat: PM Agent session lifecycle and PDCA implementation Phase 2: PM Agent Mode Integration (Design Phase) Commands/pm.md updates: - Add "Always-Active Foundation Layer" concept - Add Session Lifecycle (Session Start/During Work/Session End) - Add PDCA Cycle (Plan/Do/Check/Act) automation - Add Serena MCP Memory Integration (list/read/write_memory) - Document auto-activation triggers Agents/pm-agent.md updates: - Add Session Start Protocol (MANDATORY auto-activation) - Add During Work PDCA Cycle with example workflows - Add Session End Protocol with state preservation - Add PDCA Self-Evaluation Pattern - Add Documentation Strategy (temp → patterns/mistakes) - Add Memory Operations Reference Key Features: - Session start auto-activation for context restoration - 30-minute checkpoint saves during work - Self-evaluation with think_about_* operations - Systematic documentation lifecycle - Knowledge evolution to CLAUDE.md Implementation Status: - ✅ Design complete (Commands/pm.md, Agents/pm-agent.md) - ⏳ Implementation pending (Core components) - ⏳ Serena MCP integration pending Salvaged from mistaken development in ~/.claude directory Related: #pm-agent-mode #session-lifecycle #pdca-cycle #phase-2 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix: disable Serena MCP auto-browser launch Disable web dashboard and GUI log window auto-launch in Serena MCP server to prevent intrusive browser popups on startup. Users can still manually access the dashboard at http://localhost:24282/dashboard/ if needed. Changes: - Add CLI flags to Serena run command: - --enable-web-dashboard false - --enable-gui-log-window false - Ensures Git-tracked configuration (no reliance on ~/.serena/serena_config.yml) - Aligns with AIRIS MCP Gateway integration approach 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: rename directories to lowercase for PEP8 compliance - Rename superclaude/Agents -> superclaude/agents - Rename superclaude/Commands -> superclaude/commands - Rename superclaude/Core -> superclaude/core - Rename superclaude/Examples -> superclaude/examples - Rename superclaude/MCP -> superclaude/mcp - Rename superclaude/Modes -> superclaude/modes This change follows Python PEP8 naming conventions for package directories. * style: fix PEP8 violations and update package name to lowercase Changes: - Format all Python files with black (43 files reformatted) - Update package name from 'SuperClaude' to 'superclaude' in pyproject.toml - Fix import statements to use lowercase package name - Add missing imports (timedelta, __version__) - Remove old SuperClaude.egg-info directory PEP8 violations reduced from 2672 to 701 (mostly E501 line length due to black's 88 char vs flake8's 79 char limit). * docs: add PM Agent development documentation Add comprehensive PM Agent development documentation: - PM Agent ideal workflow (7-phase autonomous cycle) - Project structure understanding (Git vs installed environment) - Installation flow understanding (CommandsComponent behavior) - Task management system (current-tasks.md) Purpose: Eliminate repeated explanations and enable autonomous PDCA cycles 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat(pm-agent): add self-correcting execution and warning investigation culture ## Changes ### superclaude/commands/pm.md - Add "Self-Correcting Execution" section with root cause analysis protocol - Add "Warning/Error Investigation Culture" section enforcing zero-tolerance for dismissal - Define error detection protocol: STOP → Investigate → Hypothesis → Different Solution → Execute - Document anti-patterns (retry without understanding) and correct patterns (research-first) ### docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md - Add PDCA workflow hypothesis document for PM Agent autonomous enhancement ## Rationale PM Agent must never retry failed operations without understanding root causes. All warnings and errors require investigation via context7/WebFetch/documentation to ensure production-quality code and prevent technical debt accumulation. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat(installer): add airis-mcp-gateway MCP server option ## Changes - Add airis-mcp-gateway to MCP server options in installer - Configuration: GitHub-based installation via uvx - Repository: https://github.com/oraios/airis-mcp-gateway - Purpose: Dynamic MCP Gateway for zero-token baseline and on-demand tool loading ## Implementation Added to setup/components/mcp.py self.mcp_servers dictionary with: - install_method: github - install_command: uvx test installation - run_command: uvx runtime execution - required: False (optional server) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local> Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
kazuki nakai
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superclaude/core/BUSINESS_PANEL_EXAMPLES.md
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superclaude/core/BUSINESS_PANEL_EXAMPLES.md
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# BUSINESS_PANEL_EXAMPLES.md - Usage Examples and Integration Patterns
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## Basic Usage Examples
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### Example 1: Strategic Plan Analysis
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```bash
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/sc:business-panel @strategy_doc.pdf
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# Output: Discussion mode with Porter, Collins, Meadows, Doumont
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# Analysis focuses on competitive positioning, organizational capability,
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# system dynamics, and communication clarity
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```
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### Example 2: Innovation Assessment
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```bash
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/sc:business-panel "We're developing AI-powered customer service" --experts "christensen,drucker,godin"
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# Output: Discussion mode focusing on jobs-to-be-done, customer value,
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# and remarkability/tribe building
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```
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### Example 3: Risk Analysis with Debate
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```bash
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/sc:business-panel @risk_assessment.md --mode debate
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# Output: Debate mode with Taleb challenging conventional risk assessments,
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# other experts defending their frameworks, systems perspective on conflicts
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```
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### Example 4: Strategic Learning Session
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```bash
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/sc:business-panel "Help me understand competitive strategy" --mode socratic
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# Output: Socratic mode with strategic questions from multiple frameworks,
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# progressive questioning based on user responses
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```
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## Advanced Usage Patterns
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### Multi-Document Analysis
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```bash
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/sc:business-panel @market_research.pdf @competitor_analysis.xlsx @financial_projections.csv --synthesis-only
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# Comprehensive analysis across multiple documents with focus on synthesis
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```
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### Domain-Specific Analysis
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```bash
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/sc:business-panel @product_strategy.md --focus "innovation" --experts "christensen,drucker,meadows"
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# Innovation-focused analysis with disruption theory, management principles, systems thinking
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```
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### Structured Communication Focus
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```bash
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/sc:business-panel @exec_presentation.pptx --focus "communication" --structured
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# Analysis focused on message clarity, audience needs, cognitive load optimization
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```
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## Integration with SuperClaude Commands
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### Combined with /analyze
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```bash
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/analyze @business_model.md --business-panel
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# Technical analysis followed by business expert panel review
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```
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### Combined with /improve
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```bash
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/improve @strategy_doc.md --business-panel --iterative
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# Iterative improvement with business expert validation
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```
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### Combined with /design
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```bash
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/design business-model --business-panel --experts "drucker,porter,kim_mauborgne"
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# Business model design with expert guidance
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```
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## Expert Selection Strategies
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### By Business Domain
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```yaml
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strategy_planning:
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experts: ['porter', 'kim_mauborgne', 'collins', 'meadows']
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rationale: "Competitive analysis, blue ocean opportunities, execution excellence, systems thinking"
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innovation_management:
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experts: ['christensen', 'drucker', 'godin', 'meadows']
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rationale: "Disruption theory, systematic innovation, remarkability, systems approach"
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organizational_development:
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experts: ['collins', 'drucker', 'meadows', 'doumont']
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rationale: "Excellence principles, management effectiveness, systems change, clear communication"
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risk_management:
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experts: ['taleb', 'meadows', 'porter', 'collins']
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rationale: "Antifragility, systems resilience, competitive threats, disciplined execution"
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market_entry:
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experts: ['porter', 'christensen', 'godin', 'kim_mauborgne']
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rationale: "Industry analysis, disruption potential, tribe building, blue ocean creation"
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business_model_design:
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experts: ['christensen', 'drucker', 'kim_mauborgne', 'meadows']
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rationale: "Value creation, customer focus, value innovation, system dynamics"
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```
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### By Analysis Type
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```yaml
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comprehensive_audit:
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experts: "all"
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mode: "discussion → debate → synthesis"
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strategic_validation:
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experts: ['porter', 'collins', 'taleb']
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mode: "debate"
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learning_facilitation:
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experts: ['drucker', 'meadows', 'doumont']
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mode: "socratic"
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quick_assessment:
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experts: "auto-select-3"
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mode: "discussion"
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flags: "--synthesis-only"
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```
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## Output Format Variations
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### Executive Summary Format
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```bash
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/sc:business-panel @doc.pdf --structured --synthesis-only
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# Output:
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## 🎯 Strategic Assessment
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**💰 Financial Impact**: [Key economic drivers]
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**🏆 Competitive Position**: [Advantage analysis]
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**📈 Growth Opportunities**: [Expansion potential]
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**⚠️ Risk Factors**: [Critical threats]
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**🧩 Synthesis**: [Integrated recommendation]
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```
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### Framework-by-Framework Format
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```bash
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/sc:business-panel @doc.pdf --verbose
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# Output:
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## 📚 CHRISTENSEN - Disruption Analysis
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[Detailed jobs-to-be-done and disruption assessment]
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## 📊 PORTER - Competitive Strategy
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[Five forces and value chain analysis]
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## 🧩 Cross-Framework Synthesis
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[Integration and strategic implications]
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```
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### Question-Driven Format
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```bash
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/sc:business-panel @doc.pdf --questions
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# Output:
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## 🤔 Strategic Questions for Consideration
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**🔨 Innovation Questions** (Christensen):
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- What job is this being hired to do?
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**⚔️ Competitive Questions** (Porter):
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- What are the sustainable advantages?
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**🧭 Management Questions** (Drucker):
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- What should our business be?
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```
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## Integration Workflows
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### Business Strategy Development
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```yaml
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workflow_stages:
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stage_1: "/sc:business-panel @market_research.pdf --mode discussion"
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stage_2: "/sc:business-panel @competitive_analysis.md --mode debate"
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stage_3: "/sc:business-panel 'synthesize findings' --mode socratic"
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stage_4: "/design strategy --business-panel --experts 'porter,kim_mauborgne'"
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```
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### Innovation Pipeline Assessment
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```yaml
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workflow_stages:
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stage_1: "/sc:business-panel @innovation_portfolio.xlsx --focus innovation"
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stage_2: "/improve @product_roadmap.md --business-panel"
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stage_3: "/analyze @market_opportunities.pdf --business-panel --think"
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```
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### Risk Management Review
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```yaml
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workflow_stages:
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stage_1: "/sc:business-panel @risk_register.pdf --experts 'taleb,meadows,porter'"
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stage_2: "/sc:business-panel 'challenge risk assumptions' --mode debate"
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stage_3: "/implement risk_mitigation --business-panel --validate"
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```
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## Customization Options
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### Expert Behavior Modification
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```bash
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# Focus specific expert on particular aspect
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/sc:business-panel @doc.pdf --christensen-focus "disruption-potential"
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/sc:business-panel @doc.pdf --porter-focus "competitive-moats"
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# Adjust expert interaction style
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/sc:business-panel @doc.pdf --interaction "collaborative" # softer debate mode
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/sc:business-panel @doc.pdf --interaction "challenging" # stronger debate mode
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```
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### Output Customization
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```bash
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# Symbol density control
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/sc:business-panel @doc.pdf --symbols minimal # reduce symbol usage
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/sc:business-panel @doc.pdf --symbols rich # full symbol system
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# Analysis depth control
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/sc:business-panel @doc.pdf --depth surface # high-level overview
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/sc:business-panel @doc.pdf --depth detailed # comprehensive analysis
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```
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### Time and Resource Management
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```bash
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# Quick analysis for time constraints
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/sc:business-panel @doc.pdf --quick --experts-max 3
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# Comprehensive analysis for important decisions
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/sc:business-panel @doc.pdf --comprehensive --all-experts
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# Resource-aware analysis
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/sc:business-panel @doc.pdf --budget 10000 # token limit
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```
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## Quality Validation
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### Analysis Quality Checks
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```yaml
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authenticity_validation:
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voice_consistency: "Each expert maintains characteristic style"
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framework_fidelity: "Analysis follows authentic methodology"
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interaction_realism: "Expert dynamics reflect professional patterns"
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business_relevance:
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strategic_focus: "Analysis addresses real strategic concerns"
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actionable_insights: "Recommendations are implementable"
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evidence_based: "Conclusions supported by framework logic"
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integration_quality:
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synthesis_value: "Combined insights exceed individual analysis"
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framework_preservation: "Integration maintains framework distinctiveness"
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practical_utility: "Results support strategic decision-making"
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```
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### Performance Standards
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```yaml
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response_time:
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simple_analysis: "< 30 seconds"
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comprehensive_analysis: "< 2 minutes"
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multi_document: "< 5 minutes"
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token_efficiency:
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discussion_mode: "8-15K tokens"
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debate_mode: "10-20K tokens"
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socratic_mode: "12-25K tokens"
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synthesis_only: "3-8K tokens"
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accuracy_targets:
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framework_authenticity: "> 90%"
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strategic_relevance: "> 85%"
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actionable_insights: "> 80%"
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```
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