NomenAK da0a356eec 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

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# Mode detection patterns for SuperClaude-Lite
mode_detection:
brainstorming:
enabled: true
trigger_patterns:
- "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
task_management:
enabled: true
trigger_patterns:
- "multiple.*tasks"
- "complex.*system"
- "build.*comprehensive"
- "coordinate.*work"
- "large-scale.*operation"
- "manage.*operations"
- "comprehensive.*refactoring"
- "authentication.*system"
confidence_threshold: 0.7
auto_activate: true
auto_activation_thresholds:
file_count: 3
complexity_score: 0.4
token_efficiency:
enabled: true
trigger_patterns:
- "brief"
- "concise"
- "compressed"
- "efficient.*output"
- "token.*optimization"
- "short.*response"
- "running.*low.*context"
confidence_threshold: 0.75
auto_activate: true
introspection:
enabled: true
trigger_patterns:
- "analyze.*reasoning"
- "examine.*decision"
- "reflect.*on"
- "meta.*cognitive"
- "thinking.*process"
- "reasoning.*process"
- "decision.*made"
confidence_threshold: 0.6
auto_activate: true