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SuperClaude/Framework-Hooks/config/orchestrator.yaml

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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>
2025-08-06 13:26:04 +02:00
# Orchestrator routing patterns
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
routing_patterns:
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>
2025-08-06 13:26:04 +02:00
context7:
triggers:
- "library.*documentation"
- "framework.*patterns"
- "react|vue|angular"
- "official.*way"
- "React Query"
- "integrate.*library"
capabilities: ["documentation", "patterns", "integration"]
priority: "medium"
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
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>
2025-08-06 13:26:04 +02:00
sequential:
triggers:
- "analyze.*complex"
- "debug.*systematic"
- "troubleshoot.*bottleneck"
- "investigate.*root"
- "debug.*why"
- "detailed.*analysis"
- "running.*slowly"
- "performance.*bottleneck"
- "bundle.*size"
capabilities: ["analysis", "debugging", "systematic"]
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
priority: "high"
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>
2025-08-06 13:26:04 +02:00
magic:
triggers:
- "component.*ui"
- "responsive.*modal"
- "navigation.*component"
- "mobile.*friendly"
- "responsive.*dashboard"
- "charts.*real-time"
- "build.*dashboard"
capabilities: ["ui", "components", "responsive"]
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
priority: "medium"
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>
2025-08-06 13:26:04 +02:00
playwright:
triggers:
- "test.*workflow"
- "browser.*automation"
- "cross-browser.*testing"
- "performance.*testing"
- "end-to-end.*tests"
- "checkout.*flow"
- "e2e.*tests"
capabilities: ["testing", "automation", "e2e"]
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
priority: "medium"
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>
2025-08-06 13:26:04 +02:00
morphllm:
triggers:
- "edit.*file"
- "simple.*modification"
- "quick.*change"
capabilities: ["editing", "modification"]
priority: "low"
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
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>
2025-08-06 13:26:04 +02:00
serena:
triggers:
- "refactor.*codebase"
- "complex.*analysis"
- "multi.*file"
- "refactor.*entire"
- "new.*API.*patterns"
capabilities: ["refactoring", "semantic", "large-scale"]
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
priority: "high"
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>
2025-08-06 13:26:04 +02:00
# Auto-activation thresholds
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
auto_activation:
complexity_thresholds:
enable_delegation:
file_count: 3
directory_count: 2
complexity_score: 0.4
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>
2025-08-06 13:26:04 +02:00
enable_sequential:
complexity_score: 0.6
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
enable_validation:
risk_level: ["high", "critical"]
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>
2025-08-06 13:26:04 +02:00
# Hybrid intelligence selection
hybrid_intelligence:
morphllm_vs_serena:
morphllm_criteria:
file_count_max: 10
complexity_max: 0.6
preferred_operations: ["edit", "modify", "simple_refactor"]
serena_criteria:
file_count_min: 5
complexity_min: 0.4
preferred_operations: ["refactor", "analyze", "extract", "move"]
# Performance optimization
SuperClaude V4 Beta: Major framework restructuring - Restructured core framework components - Added new Agents, MCP servers, and Modes documentation - Introduced SuperClaude-Lite minimal implementation - Enhanced Commands with session management capabilities - Added comprehensive Hooks system with Python integration - Removed legacy setup and profile components - Updated .gitignore to exclude Tests/, ClaudeDocs/, and .serena/ - Consolidated configuration into SuperClaude/Config/ - Added Templates for consistent component creation This is the initial commit for the V4 Beta branch containing all recent framework improvements and architectural changes. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-05 13:59:17 +02:00
performance_optimization:
resource_management:
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>
2025-08-06 13:26:04 +02:00
token_threshold_percent: 75
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