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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>
322 lines
10 KiB
YAML
322 lines
10 KiB
YAML
# Hook Coordination Configuration
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# Intelligent hook execution patterns, dependency resolution, and optimization
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# Enables smart coordination of all Framework-Hooks lifecycle events
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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: "Hook coordination and execution intelligence patterns"
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# Hook Execution Patterns
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execution_patterns:
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parallel_execution:
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# Independent hooks that can run simultaneously
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groups:
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- name: "independent_analysis"
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hooks: ["compression_engine", "pattern_detection"]
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description: "Compression and pattern analysis can run independently"
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max_parallel: 2
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timeout: 5000 # ms
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- name: "intelligence_gathering"
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hooks: ["mcp_intelligence", "learning_engine"]
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description: "MCP and learning intelligence can run in parallel"
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max_parallel: 2
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timeout: 3000 # ms
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- name: "background_optimization"
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hooks: ["performance_monitor", "cache_management"]
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description: "Performance monitoring and cache operations"
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max_parallel: 2
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timeout: 2000 # ms
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sequential_execution:
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# Hooks that must run in specific order
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chains:
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- name: "session_lifecycle"
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sequence: ["session_start", "pre_tool_use", "post_tool_use", "stop"]
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description: "Core session lifecycle must be sequential"
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mandatory: true
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break_on_error: true
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- name: "context_preparation"
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sequence: ["session_start", "context_loading", "pattern_detection"]
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description: "Context must be prepared before pattern analysis"
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conditional: {session_type: "complex"}
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- name: "optimization_chain"
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sequence: ["compression_engine", "performance_monitor", "learning_engine"]
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description: "Optimization workflow sequence"
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trigger: {optimization_mode: true}
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conditional_execution:
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# Hooks that execute based on context conditions
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rules:
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- hook: "compression_engine"
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conditions:
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- resource_usage: ">0.75"
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- conversation_length: ">50"
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- enable_compression: true
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priority: "high"
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- hook: "pattern_detection"
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conditions:
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- complexity_score: ">0.5"
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- enable_pattern_analysis: true
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OR:
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- operation_type: ["analyze", "review", "debug"]
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priority: "medium"
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- hook: "mcp_intelligence"
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conditions:
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- mcp_servers_available: true
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- operation_requires_mcp: true
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priority: "high"
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- hook: "learning_engine"
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conditions:
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- learning_enabled: true
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- session_type: ["interactive", "complex"]
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priority: "medium"
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- hook: "performance_monitor"
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conditions:
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- performance_monitoring: true
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OR:
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- complexity_score: ">0.7"
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- resource_usage: ">0.8"
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priority: "low"
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# Dependency Resolution
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dependency_resolution:
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hook_dependencies:
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# Define dependencies between hooks
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session_start:
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requires: []
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provides: ["session_context", "initial_state"]
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pre_tool_use:
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requires: ["session_context"]
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provides: ["tool_context", "pre_analysis"]
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depends_on: ["session_start"]
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compression_engine:
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requires: ["session_context"]
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provides: ["compression_config", "optimized_context"]
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optional_depends: ["session_start"]
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pattern_detection:
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requires: ["session_context"]
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provides: ["detected_patterns", "pattern_insights"]
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optional_depends: ["session_start", "compression_engine"]
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mcp_intelligence:
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requires: ["tool_context", "detected_patterns"]
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provides: ["mcp_recommendations", "server_selection"]
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depends_on: ["pre_tool_use"]
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optional_depends: ["pattern_detection"]
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post_tool_use:
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requires: ["tool_context", "tool_results"]
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provides: ["post_analysis", "performance_metrics"]
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depends_on: ["pre_tool_use"]
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learning_engine:
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requires: ["post_analysis", "performance_metrics"]
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provides: ["learning_insights", "adaptations"]
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depends_on: ["post_tool_use"]
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optional_depends: ["mcp_intelligence", "pattern_detection"]
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stop:
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requires: ["session_context"]
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provides: ["session_summary", "cleanup_status"]
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depends_on: ["session_start"]
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optional_depends: ["learning_engine", "post_tool_use"]
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resolution_strategies:
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# How to resolve dependency conflicts
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missing_dependency:
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strategy: "graceful_degradation"
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fallback: "skip_optional"
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circular_dependency:
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strategy: "break_weakest_link"
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priority_order: ["session_start", "pre_tool_use", "post_tool_use", "stop"]
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timeout_handling:
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strategy: "continue_without_dependency"
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timeout_threshold: 10000 # ms
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# Performance Optimization
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performance_optimization:
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execution_optimization:
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# Optimize hook execution based on context
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fast_path:
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conditions:
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- complexity_score: "<0.3"
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- operation_type: ["simple", "basic"]
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- resource_usage: "<0.5"
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optimizations:
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- skip_non_essential_hooks: true
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- reduce_analysis_depth: true
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- enable_aggressive_caching: true
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- parallel_where_possible: true
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comprehensive_path:
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conditions:
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- complexity_score: ">0.7"
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- operation_type: ["complex", "analysis"]
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- accuracy_priority: "high"
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optimizations:
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- enable_all_hooks: true
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- deep_analysis_mode: true
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- cross_hook_coordination: true
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- detailed_logging: true
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resource_management:
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# Manage resource usage across hooks
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resource_budgets:
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cpu_budget: 80 # percent
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memory_budget: 70 # percent
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time_budget: 15000 # ms total
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resource_allocation:
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session_lifecycle: 30 # percent of budget
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intelligence_hooks: 40 # percent
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optimization_hooks: 30 # percent
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caching_strategies:
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# Hook result caching
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cacheable_hooks:
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- hook: "pattern_detection"
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cache_key: ["session_context", "operation_type"]
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cache_duration: 300 # seconds
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- hook: "mcp_intelligence"
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cache_key: ["operation_context", "available_servers"]
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cache_duration: 600 # seconds
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- hook: "compression_engine"
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cache_key: ["context_size", "compression_level"]
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cache_duration: 1800 # seconds
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# Context-Aware Execution
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context_awareness:
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operation_context:
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# Adapt execution based on operation context
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context_patterns:
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- context_type: "ui_development"
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hook_priorities: ["mcp_intelligence", "pattern_detection", "compression_engine"]
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preferred_execution: "fast_parallel"
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- context_type: "code_analysis"
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hook_priorities: ["pattern_detection", "mcp_intelligence", "learning_engine"]
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preferred_execution: "comprehensive_sequential"
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- context_type: "performance_optimization"
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hook_priorities: ["performance_monitor", "compression_engine", "pattern_detection"]
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preferred_execution: "resource_optimized"
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user_preferences:
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# Adapt to user preferences and patterns
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preference_patterns:
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- user_type: "performance_focused"
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optimizations: ["aggressive_caching", "parallel_execution", "skip_optional"]
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- user_type: "quality_focused"
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optimizations: ["comprehensive_analysis", "detailed_validation", "full_coordination"]
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- user_type: "speed_focused"
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optimizations: ["fast_path", "minimal_hooks", "cached_results"]
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# Error Handling and Recovery
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error_handling:
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error_recovery:
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# Hook failure recovery strategies
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recovery_strategies:
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- error_type: "timeout"
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recovery: "continue_without_hook"
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log_level: "warning"
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- error_type: "dependency_missing"
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recovery: "graceful_degradation"
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log_level: "info"
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- error_type: "critical_failure"
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recovery: "abort_and_cleanup"
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log_level: "error"
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resilience_patterns:
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# Make hook execution resilient
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resilience_features:
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retry_failed_hooks: true
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max_retries: 2
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retry_backoff: "exponential" # linear, exponential
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graceful_degradation: true
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fallback_to_basic: true
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preserve_essential_hooks: ["session_start", "stop"]
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error_isolation: true
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prevent_error_cascade: true
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maintain_session_integrity: true
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# Hook Lifecycle Management
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lifecycle_management:
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hook_states:
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# Track hook execution states
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state_tracking:
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- pending
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- initializing
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- running
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- completed
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- failed
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- skipped
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- timeout
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lifecycle_events:
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# Events during hook execution
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event_handlers:
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before_hook_execution:
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actions: ["validate_dependencies", "check_resources", "prepare_context"]
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after_hook_execution:
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actions: ["update_metrics", "cache_results", "trigger_dependent_hooks"]
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hook_failure:
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actions: ["log_error", "attempt_recovery", "notify_dependent_hooks"]
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monitoring:
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# Monitor hook execution
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performance_tracking:
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track_execution_time: true
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track_resource_usage: true
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track_success_rate: true
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track_dependency_resolution: true
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health_monitoring:
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hook_health_checks: true
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dependency_health_checks: true
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performance_degradation_detection: true
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# Dynamic Configuration
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dynamic_configuration:
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adaptive_execution:
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# Adapt execution patterns based on performance
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adaptation_triggers:
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- performance_degradation: ">20%"
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action: "switch_to_fast_path"
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- error_rate: ">10%"
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action: "enable_resilience_mode"
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- resource_pressure: ">90%"
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action: "reduce_hook_scope"
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learning_integration:
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# Learn from hook execution patterns
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learning_features:
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learn_optimal_execution_order: true
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learn_user_preferences: true
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learn_performance_patterns: true
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adapt_to_project_context: true |