Gemini CLI Orchestrator MCP

# Enhanced Metaprompting Implementation Summary ## Research-Driven Enhancements Completed Based on comprehensive research into Gemini CLI capabilities and Sequential Thinking MCP patterns, we've implemented focused enhancements that optimize for intelligent Gemini collaboration. ## Phase 1: Context Window Optimization ✅ **Enhanced:** `gemini_guide_collaboration_step` tool **Key Research Findings Applied:** - Gemini 2.5 Pro handles 1M+ token context window - Complete subsystem aggregation outperforms file-by-file analysis - GEMINI.md context files enable persistent project understanding **Implementation:** - Strategic file aggregation patterns for maximum context utilization - Repository preparation techniques for massive codebases - GEMINI.md context file creation guidance - Smart filtering strategies for complex projects **Example Enhancement:** ```bash # Before: Single file analysis cat src/auth.js | gemini -p "analyze auth" # After: Complete subsystem context cat src/auth/**/* middleware/auth* config/auth* tests/auth* | gemini -p "analyze complete authentication subsystem" ``` ## Phase 2: ReAct Loop Integration ✅ **Added:** New `gemini_guide_react_loop` tool **Key Research Findings Applied:** - Gemini CLI uses ReAct (Reasoning and Acting) loops for complex problem-solving - Iterative Thought→Action→Observation→Reflection cycles adapt dynamically - Loop termination and branching decisions require intelligent guidance **Implementation:** - Structured reasoning templates before action - Observation and reflection frameworks after action - Dynamic strategy adjustment guidance - Loop termination decision criteria - Iteration planning for continuous improvement **Intelligence Amplification:** - Teaches hypothesis formation and testing - Guides systematic observation of results - Promotes adaptive strategy evolution - Prevents endless loops through termination criteria ## Phase 3: Sequential Thinking Alignment ✅ **Enhanced:** `gemini_guide_analysis_workflow` tool **Key Research Findings Applied:** - Sequential Thinking MCP uses structured progression through defined stages - Progressive understanding with dynamic adaptation capability - Context maintenance across multiple analysis steps - Revision and branching when complexity emerges **Implementation:** - 5-stage progressive framework (Problem Definition → Research → Analysis → Synthesis → Conclusion) - Dynamic stage management with expansion/revision triggers - Context maintenance strategies across stages - Branching logic for alternative analysis paths **Sequential Stages:** 1. **Problem Definition & Scope**: Clear boundary setting with discovery prompts 2. **Research & Information Gathering**: Comprehensive context collection using 1M+ strategy 3. **Analysis & Pattern Recognition**: Deep pattern analysis with ReAct loops when needed 4. **Synthesis & Evaluation**: Cross-cutting analysis connecting insights 5. **Conclusion & Recommendations**: Actionable outcomes with prioritization ## Phase 4: Gemini-Specific Optimization ✅ **Enhanced:** Advanced metaprompting patterns leveraging Gemini's core strengths **Key Research Findings Applied:** - Gemini excels at security analysis, architecture review, and debugging - Pattern recognition capabilities for cross-cutting concerns - Multimodal analysis capabilities for comprehensive understanding **Implementation:** ### Security Analysis Optimization: - Input validation and sanitization focus - Authentication/authorization flaw detection - Injection vulnerability assessment - Cryptographic implementation review - Severity-rated actionable recommendations ### Architecture Review Enhancement: - Design pattern adherence evaluation - Scalability and maintainability assessment - Technical debt identification - Anti-pattern detection - Implementation strategy suggestions ### Debugging & Root Cause Analysis: - Logical flow tracing guidance - Edge case and boundary condition analysis - Performance bottleneck identification - Integration failure point mapping - Preventive measure recommendations ## Phase 5: Intelligence Amplification ✅ **Enhanced:** `gemini_guide_insight_synthesis` tool **Key Research Findings Applied:** - Multi-perspective analysis for comprehensive understanding - Pattern recognition across disconnected findings - Systems thinking for root cause identification - Cognitive bias detection in analysis process **Advanced Techniques Implemented:** ### Multi-Perspective Analysis Framework: - Technical Architecture perspective - Security Posture assessment - Business Impact evaluation - Operational Readiness review - Future Evolution planning ### Strategic Prioritization Matrix: - High Impact, Low Effort (quick wins) - High Impact, High Effort (strategic initiatives) - Low Impact, Low Effort (housekeeping) - Low Impact, High Effort (avoid/defer) ### Cognitive Bias Detection: - Confirmation bias mitigation - Availability bias awareness - Anchoring bias prevention - Recency bias correction ### Meta-Analysis Capabilities: - Analysis limitation recognition - Assumption examination - Stakeholder perspective consideration - Question completeness assessment ## Core Metaprompting Principles Maintained Throughout all enhancements, we maintained strict adherence to metaprompting-first design: ✅ **No Execution Logic**: Server provides only guidance, never executes commands ✅ **Intelligence Amplification**: Makes agents smarter, doesn't replace their intelligence ✅ **Trust Agent Capability**: Assumes agent intelligence, guides rather than constrains ✅ **Universal Portability**: Works anywhere agent has bash + gemini CLI access ✅ **Teaching Over Doing**: Provides strategic frameworks, not rigid procedures ## Key Success Metrics **Enhanced Context Utilization**: Agents now leverage Gemini's full 1M+ token capacity strategically **Improved Analysis Quality**: Structured progression through proven Sequential Thinking patterns **Dynamic Adaptation**: ReAct loops enable real-time strategy adjustment based on findings **Specialized Optimization**: Leverages Gemini's specific strengths in security, architecture, debugging **Meta-Cognitive Awareness**: Synthesis includes bias detection and assumption examination ## Architecture Validation The enhanced system perfectly aligns with both: - **Gemini CLI patterns**: Large context aggregation, ReAct loops, specialized analysis strengths - **Sequential Thinking MCP**: Structured progression, dynamic adaptation, context maintenance **Result**: A pure metaprompting system that teaches intelligent Gemini collaboration rather than executing it. ## Tools Summary 1. **`gemini_guide_analysis_workflow`**: Sequential thinking framework with 5-stage progression 2. **`gemini_guide_collaboration_step`**: Context-optimized command crafting with Gemini-specific templates 3. **`gemini_guide_react_loop`**: Iterative reasoning-action cycles with dynamic adaptation 4. **`gemini_guide_insight_synthesis`**: Multi-perspective synthesis with intelligence amplification All tools work synergistically to guide agents through sophisticated analysis workflows that maximize Gemini's capabilities while maintaining the pure metaprompting philosophy.