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feat: Implement YAML-first declarative intelligence architecture
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>
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Framework-Hooks/config/user_experience.yaml
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Framework-Hooks/config/user_experience.yaml
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# User Experience Intelligence Configuration
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# UX optimization, project detection, and user-centric intelligence patterns
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# Enables intelligent user experience through smart defaults and proactive assistance
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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: "User experience optimization and project intelligence patterns"
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# Project Type Detection
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project_detection:
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detection_patterns:
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# Detect project types based on files and structure
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frontend_frameworks:
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react_project:
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file_indicators:
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- "package.json"
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- "*.tsx"
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- "*.jsx"
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- "react" # in package.json dependencies
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directory_indicators:
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- "src/components"
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- "public"
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- "node_modules"
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confidence_threshold: 0.8
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recommendations:
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mcp_servers: ["magic", "context7", "playwright"]
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compression_level: "minimal"
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performance_focus: "ui_responsiveness"
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vue_project:
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file_indicators:
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- "package.json"
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- "*.vue"
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- "vue.config.js"
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- "vue" # in dependencies
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directory_indicators:
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- "src/components"
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- "src/views"
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confidence_threshold: 0.8
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recommendations:
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mcp_servers: ["magic", "context7"]
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compression_level: "standard"
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angular_project:
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file_indicators:
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- "angular.json"
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- "*.component.ts"
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- "@angular" # in dependencies
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directory_indicators:
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- "src/app"
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- "e2e"
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confidence_threshold: 0.9
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recommendations:
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mcp_servers: ["magic", "context7", "playwright"]
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backend_frameworks:
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python_project:
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file_indicators:
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- "requirements.txt"
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- "pyproject.toml"
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- "setup.py"
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- "*.py"
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directory_indicators:
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- "src"
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- "tests"
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- "__pycache__"
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confidence_threshold: 0.7
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recommendations:
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mcp_servers: ["serena", "sequential", "context7"]
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compression_level: "standard"
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validation_level: "enhanced"
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node_backend:
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file_indicators:
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- "package.json"
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- "*.js"
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- "express" # in dependencies
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- "server.js"
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directory_indicators:
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- "routes"
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- "controllers"
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- "middleware"
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confidence_threshold: 0.8
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recommendations:
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mcp_servers: ["sequential", "context7", "serena"]
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data_science:
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jupyter_project:
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file_indicators:
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- "*.ipynb"
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- "requirements.txt"
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- "conda.yml"
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directory_indicators:
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- "notebooks"
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- "data"
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confidence_threshold: 0.9
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recommendations:
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mcp_servers: ["sequential", "context7"]
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compression_level: "minimal"
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analysis_depth: "comprehensive"
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documentation:
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docs_project:
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file_indicators:
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- "*.md"
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- "docs/"
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- "README.md"
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- "mkdocs.yml"
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directory_indicators:
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- "docs"
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- "documentation"
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confidence_threshold: 0.8
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recommendations:
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mcp_servers: ["context7", "sequential"]
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focus_areas: ["clarity", "completeness"]
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# User Preference Intelligence
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user_preferences:
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preference_learning:
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# Learn user preferences from behavior patterns
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interaction_patterns:
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command_preferences:
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track_command_usage: true
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track_flag_preferences: true
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track_workflow_patterns: true
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learning_window: 100 # operations
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performance_preferences:
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speed_vs_quality_preference:
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indicators: ["timeout_tolerance", "quality_acceptance", "performance_complaints"]
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classification: ["speed_focused", "quality_focused", "balanced"]
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detail_level_preference:
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indicators: ["verbose_mode_usage", "summary_requests", "detail_requests"]
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classification: ["concise", "detailed", "adaptive"]
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preference_adaptation:
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# Adapt behavior based on learned preferences
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adaptation_strategies:
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speed_focused_user:
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optimizations: ["aggressive_caching", "parallel_execution", "reduced_analysis"]
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ui_changes: ["shorter_responses", "quick_suggestions", "minimal_explanations"]
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quality_focused_user:
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optimizations: ["comprehensive_analysis", "detailed_validation", "thorough_documentation"]
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ui_changes: ["detailed_responses", "comprehensive_suggestions", "full_explanations"]
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efficiency_focused_user:
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optimizations: ["smart_defaults", "workflow_automation", "predictive_suggestions"]
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ui_changes: ["proactive_help", "automated_optimizations", "efficiency_tips"]
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# Proactive User Assistance
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proactive_assistance:
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intelligent_suggestions:
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# Provide intelligent suggestions based on context
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optimization_suggestions:
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- trigger: {repeated_operations: ">5", same_pattern: true}
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suggestion: "Consider creating a script or alias for this repeated operation"
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confidence: 0.8
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category: "workflow_optimization"
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- trigger: {performance_issues: "detected", duration: ">3_sessions"}
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suggestion: "Performance optimization recommendations available"
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action: "show_performance_guide"
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confidence: 0.9
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category: "performance"
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- trigger: {error_pattern: "recurring", count: ">3"}
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suggestion: "Automated error recovery pattern available"
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action: "enable_auto_recovery"
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confidence: 0.85
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category: "error_prevention"
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contextual_help:
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# Provide contextual help and guidance
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help_triggers:
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- context: {new_user: true, session_count: "<5"}
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help_type: "onboarding_guidance"
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content: "Getting started tips and best practices"
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- context: {error_rate: ">10%", recent_errors: ">3"}
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help_type: "troubleshooting_assistance"
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content: "Common error solutions and debugging tips"
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- context: {complex_operation: true, user_expertise: "beginner"}
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help_type: "step_by_step_guidance"
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content: "Detailed guidance for complex operations"
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# Smart Defaults Intelligence
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smart_defaults:
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context_aware_defaults:
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# Generate smart defaults based on context
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project_based_defaults:
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react_project:
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default_mcp_servers: ["magic", "context7"]
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default_compression: "minimal"
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default_analysis_depth: "ui_focused"
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default_validation: "component_focused"
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python_project:
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default_mcp_servers: ["serena", "sequential"]
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default_compression: "standard"
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default_analysis_depth: "comprehensive"
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default_validation: "enhanced"
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documentation_project:
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default_mcp_servers: ["context7"]
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default_compression: "minimal"
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default_analysis_depth: "content_focused"
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default_validation: "readability_focused"
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dynamic_configuration:
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# Dynamically adjust configuration
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configuration_adaptation:
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performance_based:
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triggers:
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- condition: {system_performance: "high"}
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adjustments: {analysis_depth: "comprehensive", features: "all_enabled"}
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- condition: {system_performance: "low"}
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adjustments: {analysis_depth: "essential", features: "performance_focused"}
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user_expertise_based:
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triggers:
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- condition: {user_expertise: "expert"}
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adjustments: {verbosity: "minimal", automation: "high", warnings: "reduced"}
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- condition: {user_expertise: "beginner"}
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adjustments: {verbosity: "detailed", automation: "guided", warnings: "comprehensive"}
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# Error Recovery Intelligence
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error_recovery:
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intelligent_error_handling:
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# Smart error handling and recovery
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error_classification:
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user_errors:
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- type: "syntax_error"
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recovery: "suggest_correction"
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user_guidance: "detailed"
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- type: "configuration_error"
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recovery: "auto_fix_with_approval"
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user_guidance: "educational"
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- type: "workflow_error"
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recovery: "suggest_alternative_approach"
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user_guidance: "workflow_tips"
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system_errors:
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- type: "performance_degradation"
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recovery: "automatic_optimization"
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user_notification: "informational"
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- type: "resource_exhaustion"
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recovery: "resource_management_mode"
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user_notification: "status_update"
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- type: "service_unavailable"
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recovery: "graceful_fallback"
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user_notification: "service_status"
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recovery_learning:
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# Learn from error recovery patterns
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recovery_effectiveness:
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track_recovery_success: true
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learn_recovery_patterns: true
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improve_recovery_strategies: true
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user_recovery_preferences:
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learn_preferred_recovery: true
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adapt_recovery_approach: true
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personalize_error_handling: true
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# User Expertise Detection
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expertise_detection:
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expertise_indicators:
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# Detect user expertise level
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behavioral_indicators:
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command_proficiency:
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indicators: ["advanced_flags", "complex_operations", "custom_configurations"]
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weight: 0.4
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error_recovery_ability:
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indicators: ["self_correction", "minimal_help_needed", "independent_problem_solving"]
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weight: 0.3
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workflow_sophistication:
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indicators: ["efficient_workflows", "automation_usage", "advanced_patterns"]
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weight: 0.3
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expertise_adaptation:
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# Adapt interface based on expertise
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beginner_adaptations:
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interface: ["detailed_explanations", "step_by_step_guidance", "comprehensive_warnings"]
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defaults: ["safe_options", "guided_workflows", "educational_mode"]
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intermediate_adaptations:
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interface: ["balanced_explanations", "contextual_help", "smart_suggestions"]
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defaults: ["optimized_workflows", "intelligent_automation", "performance_focused"]
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expert_adaptations:
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interface: ["minimal_explanations", "advanced_options", "efficiency_focused"]
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defaults: ["maximum_automation", "performance_optimization", "minimal_interruptions"]
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# User Satisfaction Intelligence
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satisfaction_intelligence:
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satisfaction_tracking:
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# Track user satisfaction indicators
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satisfaction_metrics:
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task_completion_rate:
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weight: 0.3
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target_threshold: 0.85
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error_resolution_speed:
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weight: 0.25
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target_threshold: "fast"
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feature_adoption_rate:
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weight: 0.2
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target_threshold: 0.6
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user_feedback_sentiment:
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weight: 0.25
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target_threshold: "positive"
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satisfaction_optimization:
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# Optimize for user satisfaction
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optimization_strategies:
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low_satisfaction_triggers:
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- trigger: {completion_rate: "<0.7"}
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action: "simplify_workflows"
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priority: "high"
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- trigger: {error_rate: ">15%"}
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action: "improve_error_prevention"
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priority: "critical"
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- trigger: {feature_adoption: "<0.3"}
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action: "improve_feature_discoverability"
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priority: "medium"
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# Personalization Engine
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personalization:
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adaptive_interface:
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# Personalize interface based on user patterns
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interface_personalization:
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layout_preferences:
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learn_preferred_layouts: true
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adapt_information_density: true
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customize_interaction_patterns: true
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content_personalization:
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learn_content_preferences: true
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adapt_explanation_depth: true
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customize_suggestion_types: true
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workflow_optimization:
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# Optimize workflows for individual users
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personal_workflow_learning:
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common_task_patterns: true
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workflow_efficiency_analysis: true
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personalized_shortcuts: true
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workflow_recommendations:
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suggest_workflow_improvements: true
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recommend_automation_opportunities: true
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provide_efficiency_insights: true
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# Accessibility Intelligence
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accessibility:
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adaptive_accessibility:
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# Adapt interface for accessibility needs
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accessibility_detection:
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detect_accessibility_needs: true
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learn_accessibility_preferences: true
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adapt_interface_accordingly: true
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inclusive_design:
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# Ensure inclusive user experience
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inclusive_features:
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multiple_interaction_modes: true
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flexible_interface_scaling: true
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comprehensive_keyboard_support: true
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screen_reader_optimization: true
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