External/SuperClaude
1
0
Fork 0
mirror of https://github.com/SuperClaude-Org/SuperClaude_Framework.git synced 2025-12-29 16:16:08 +00:00
Code Issues Packages Projects Releases Wiki Activity
SuperClaude/Framework-Hooks/config/modes.yaml

59 lines
1.4 KiB
YAML
Raw Normal View History

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
# Mode detection patterns for SuperClaude-Lite
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
mode_detection:
brainstorming:
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
enabled: true
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
trigger_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
- "I want to build"
- "thinking about"
- "not sure"
- "maybe.*could"
- "brainstorm"
- "explore"
- "figure out"
- "unclear.*requirements"
- "ambiguous.*needs"
confidence_threshold: 0.7
auto_activate: true
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
task_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
enabled: true
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
trigger_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
- "multiple.*tasks"
- "complex.*system"
- "build.*comprehensive"
- "coordinate.*work"
- "large-scale.*operation"
- "manage.*operations"
- "comprehensive.*refactoring"
- "authentication.*system"
confidence_threshold: 0.7
auto_activate: true
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_thresholds:
file_count: 3
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
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
token_efficiency:
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
enabled: true
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
trigger_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
- "brief"
- "concise"
- "compressed"
- "efficient.*output"
- "token.*optimization"
- "short.*response"
- "running.*low.*context"
confidence_threshold: 0.75
auto_activate: true
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
introspection:
enabled: true
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
trigger_patterns:
- "analyze.*reasoning"
- "examine.*decision"
- "reflect.*on"
- "meta.*cognitive"
- "thinking.*process"
- "reasoning.*process"
- "decision.*made"
confidence_threshold: 0.6
auto_activate: true
Reference in New Issue Copy Permalink