SuperClaude/Framework-Hooks/docs/Configuration/intelligence_patterns.yaml.md

# Intelligence Patterns Configuration (`intelligence_patterns.yaml`)

## Overview

The `intelligence_patterns.yaml` file defines core learning intelligence patterns for SuperClaude Framework-Hooks. This configuration enables multi-dimensional pattern recognition, adaptive learning, and intelligent behavior adaptation.

## Purpose and Role

This configuration provides:
- **Pattern Recognition**: Multi-dimensional analysis of operation patterns
- **Adaptive Learning**: Dynamic learning rate and confidence adjustment
- **Behavior Intelligence**: Context-aware decision making and optimization
- **Performance Intelligence**: Success pattern recognition and optimization

## Key Configuration Areas

### 1. Pattern Recognition
- **Multi-Dimensional Analysis**: Context type, complexity, operation type, performance
- **Signature Generation**: Unique pattern identification for caching and learning
- **Pattern Clustering**: Groups similar patterns for behavioral optimization
- **Similarity Thresholds**: Controls pattern matching sensitivity

### 2. Adaptive Learning
- **Dynamic Learning Rates**: Confidence-based learning rate adjustment (0.1-1.0)
- **Confidence Scoring**: Multi-factor confidence assessment
- **Learning Windows**: Time-based and operation-based learning boundaries
- **Adaptation Strategies**: How the system adapts to new patterns

### 3. Intelligence Behaviors
- **Context Intelligence**: Situation-aware decision making
- **Performance Intelligence**: Success pattern recognition and replication
- **User Intelligence**: User behavior pattern learning and adaptation
- **System Intelligence**: System performance pattern optimization

## Configuration Structure

The file includes detailed configurations for:
- Learning intelligence parameters and thresholds
- Pattern recognition algorithms and clustering
- Confidence scoring and adaptation strategies
- Intelligence behavior definitions and triggers

## Integration Points

### Hook Integration
- Pattern recognition runs during hook execution
- Learning updates occur post-operation
- Intelligence behaviors influence hook coordination

### Performance Integration
- Performance patterns inform optimization decisions
- Success patterns guide resource allocation
- Failure patterns trigger adaptation strategies

## Usage Guidelines

This is an advanced configuration file that controls the core learning and intelligence capabilities of the Framework-Hooks system. Most users should not need to modify these settings, as they are tuned for optimal performance across different use cases.

## Related Documentation

- **Hook Coordination**: `hook_coordination.yaml.md` for execution patterns
- **Performance**: `performance.yaml.md` for performance optimization
- **User Experience**: `user_experience.yaml.md` for user-focused intelligence