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da0a356eec
Revolutionary transformation from hardcoded Python intelligence to hot-reloadable YAML patterns, enabling dynamic configuration without code changes. ## Phase 1: Foundation Intelligence Complete ### YAML Intelligence Patterns (6 files) - intelligence_patterns.yaml: Multi-dimensional pattern recognition with adaptive learning - mcp_orchestration.yaml: Server selection decision trees with load balancing - hook_coordination.yaml: Parallel execution patterns with dependency resolution - performance_intelligence.yaml: Resource zones and auto-optimization triggers - validation_intelligence.yaml: Health scoring and proactive diagnostic patterns - user_experience.yaml: Project detection and smart UX adaptations ### Python Infrastructure Enhanced (4 components) - intelligence_engine.py: Generic YAML pattern interpreter with hot-reload - learning_engine.py: Enhanced with YAML intelligence integration - yaml_loader.py: Added intelligence configuration helper methods - validate_system.py: New YAML-driven validation with health scoring ### Key Features Implemented - Hot-reload intelligence: Update patterns without code changes or restarts - Declarative configuration: All intelligence logic expressed in YAML - Graceful fallbacks: System works correctly even with missing YAML files - Multi-pattern coordination: Intelligent recommendations from multiple sources - Health scoring: Component-weighted validation with predictive diagnostics - Generic architecture: Single engine consumes all intelligence pattern types ### Testing Results ✅ All components integrate correctly ✅ Hot-reload mechanism functional ✅ Graceful error handling verified ✅ YAML-driven validation operational ✅ Health scoring system working (detected real system issues) This enables users to modify intelligence behavior by editing YAML files, add new pattern types without coding, and hot-reload improvements in real-time. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
308 lines
9.2 KiB
YAML
308 lines
9.2 KiB
YAML
# MCP Orchestration Configuration
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# Intelligent server selection, coordination, and load balancing patterns
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# Enables smart MCP server orchestration based on context and performance
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# Metadata
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version: "1.0.0"
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last_updated: "2025-01-06"
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description: "MCP server orchestration intelligence patterns"
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# Server Selection Intelligence
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server_selection:
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decision_tree:
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# UI/Design Operations
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- name: "ui_component_operations"
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conditions:
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keywords: ["component", "ui", "design", "frontend", "jsx", "tsx", "css"]
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OR:
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- operation_type: ["build", "implement", "design"]
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- file_extensions: [".jsx", ".tsx", ".vue", ".css", ".scss"]
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primary_server: "magic"
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support_servers: ["context7"]
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coordination_mode: "parallel"
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confidence: 0.9
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# Analysis and Architecture Operations
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- name: "complex_analysis"
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conditions:
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AND:
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- complexity_score: ">0.7"
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- operation_type: ["analyze", "review", "debug", "troubleshoot"]
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OR:
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- file_count: ">10"
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- keywords: ["architecture", "system", "complex"]
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primary_server: "sequential"
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support_servers: ["context7", "serena"]
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coordination_mode: "sequential"
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confidence: 0.85
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# Code Refactoring and Transformation
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- name: "code_refactoring"
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conditions:
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AND:
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- operation_type: ["refactor", "transform", "modify"]
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OR:
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- file_count: ">5"
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- complexity_score: ">0.5"
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- keywords: ["refactor", "cleanup", "optimize"]
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primary_server: "serena"
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support_servers: ["morphllm", "sequential"]
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coordination_mode: "hybrid"
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confidence: 0.8
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# Documentation and Learning
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- name: "documentation_operations"
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conditions:
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keywords: ["document", "explain", "guide", "tutorial", "learn"]
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OR:
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- operation_type: ["document", "explain"]
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- file_extensions: [".md", ".rst", ".txt"]
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primary_server: "context7"
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support_servers: ["sequential"]
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coordination_mode: "sequential"
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confidence: 0.85
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# Testing and Validation
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- name: "testing_operations"
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conditions:
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keywords: ["test", "validate", "check", "verify", "e2e"]
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OR:
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- operation_type: ["test", "validate"]
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- file_patterns: ["*test*", "*spec*", "*e2e*"]
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primary_server: "playwright"
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support_servers: ["sequential", "magic"]
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coordination_mode: "parallel"
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confidence: 0.8
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# Fast Edits and Transformations
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- name: "fast_edits"
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conditions:
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AND:
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- complexity_score: "<0.4"
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- file_count: "<5"
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operation_type: ["edit", "modify", "fix", "update"]
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primary_server: "morphllm"
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support_servers: ["serena"]
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coordination_mode: "fallback"
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confidence: 0.7
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# Fallback Strategy
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fallback_chain:
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default_primary: "sequential"
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fallback_sequence: ["context7", "serena", "morphllm", "magic", "playwright"]
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fallback_threshold: 3.0 # seconds timeout
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# Load Balancing Intelligence
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load_balancing:
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health_monitoring:
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# Server health check configuration
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check_interval: 30 # seconds
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timeout: 5 # seconds
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retry_count: 3
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health_metrics:
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- response_time
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- error_rate
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- request_queue_size
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- availability_percentage
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performance_thresholds:
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# Performance-based routing thresholds
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response_time:
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excellent: 500 # ms
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good: 1000 # ms
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warning: 2000 # ms
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critical: 5000 # ms
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error_rate:
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excellent: 0.01 # 1%
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good: 0.03 # 3%
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warning: 0.05 # 5%
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critical: 0.15 # 15%
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queue_size:
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excellent: 0
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good: 2
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warning: 5
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critical: 10
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routing_strategies:
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# Load balancing algorithms
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primary_strategy: "weighted_performance"
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strategies:
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round_robin:
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description: "Distribute requests evenly across healthy servers"
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weight_factor: "equal"
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weighted_performance:
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description: "Route based on server performance metrics"
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weight_factors:
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response_time: 0.4
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error_rate: 0.3
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availability: 0.3
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least_connections:
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description: "Route to server with fewest active connections"
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connection_tracking: true
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performance_based:
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description: "Route to best-performing server"
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performance_window: 300 # seconds
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# Cross-Server Coordination
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coordination_patterns:
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sequential_coordination:
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# When servers work in sequence
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patterns:
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- name: "analysis_then_implementation"
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sequence: ["sequential", "morphllm"]
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trigger: {operation: "implement", analysis_required: true}
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- name: "research_then_build"
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sequence: ["context7", "magic"]
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trigger: {operation: "build", research_required: true}
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- name: "plan_then_execute"
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sequence: ["sequential", "serena", "morphllm"]
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trigger: {complexity: ">0.7", operation: "refactor"}
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parallel_coordination:
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# When servers work simultaneously
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patterns:
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- name: "ui_with_docs"
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parallel: ["magic", "context7"]
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trigger: {operation: "build", component_type: "ui"}
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synchronization: "merge_results"
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- name: "test_with_validation"
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parallel: ["playwright", "sequential"]
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trigger: {operation: "test", validation_required: true}
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synchronization: "wait_all"
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hybrid_coordination:
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# Mixed coordination patterns
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patterns:
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- name: "comprehensive_refactoring"
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phases:
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- phase: 1
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servers: ["sequential"] # Analysis
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wait_for_completion: true
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- phase: 2
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servers: ["serena", "morphllm"] # Parallel execution
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synchronization: "coordinate_changes"
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# Dynamic Server Capabilities
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capability_assessment:
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dynamic_capabilities:
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# Assess server capabilities in real-time
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assessment_interval: 60 # seconds
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capability_metrics:
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- processing_speed
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- accuracy_score
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- specialization_match
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- current_load
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capability_mapping:
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# Map operations to server capabilities
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magic:
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specializations: ["ui", "components", "design", "frontend"]
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performance_profile: "medium_latency_high_quality"
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optimal_load: 3
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sequential:
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specializations: ["analysis", "debugging", "complex_reasoning"]
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performance_profile: "high_latency_high_quality"
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optimal_load: 2
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context7:
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specializations: ["documentation", "learning", "research"]
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performance_profile: "low_latency_medium_quality"
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optimal_load: 5
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serena:
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specializations: ["refactoring", "large_codebases", "semantic_analysis"]
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performance_profile: "medium_latency_high_precision"
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optimal_load: 3
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morphllm:
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specializations: ["fast_edits", "transformations", "pattern_matching"]
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performance_profile: "low_latency_medium_quality"
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optimal_load: 4
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playwright:
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specializations: ["testing", "validation", "browser_automation"]
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performance_profile: "high_latency_specialized"
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optimal_load: 2
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# Error Handling and Recovery
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error_handling:
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retry_strategies:
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# Server error retry patterns
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exponential_backoff:
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initial_delay: 1 # seconds
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max_delay: 60 # seconds
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multiplier: 2
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max_retries: 3
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graceful_degradation:
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# Fallback when servers fail
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degradation_levels:
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- level: 1
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strategy: "use_secondary_server"
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performance_impact: "minimal"
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- level: 2
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strategy: "reduce_functionality"
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performance_impact: "moderate"
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- level: 3
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strategy: "basic_operation_only"
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performance_impact: "significant"
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circuit_breaker:
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# Circuit breaker pattern for failing servers
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failure_threshold: 5 # failures before opening circuit
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recovery_timeout: 30 # seconds before attempting recovery
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half_open_requests: 3 # test requests during recovery
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# Performance Optimization
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performance_optimization:
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caching:
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# Server response caching
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enable_response_caching: true
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cache_duration: 300 # seconds
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max_cache_size: 100 # responses
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cache_key_strategy: "operation_context_hash"
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request_optimization:
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# Request batching and optimization
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enable_request_batching: true
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batch_size: 3
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batch_timeout: 1000 # ms
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predictive_routing:
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# Predict optimal server based on patterns
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enable_prediction: true
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prediction_model: "pattern_based"
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prediction_confidence_threshold: 0.7
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# Monitoring and Analytics
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monitoring:
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metrics_collection:
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# Collect orchestration metrics
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collect_routing_decisions: true
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collect_performance_metrics: true
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collect_error_patterns: true
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retention_days: 30
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analytics:
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# Server orchestration analytics
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routing_accuracy_tracking: true
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performance_trend_analysis: true
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optimization_recommendations: true
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alerts:
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# Alert thresholds
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high_error_rate: 0.1 # 10%
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slow_response_time: 5000 # ms
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server_unavailable: true |