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

Session Configuration (session.yaml)

Overview

The session.yaml file defines session lifecycle management and analytics configuration for the SuperClaude-Lite framework. This configuration controls session initialization, termination, project detection, intelligence activation, and comprehensive session analytics across the framework.

Purpose and Role

The session configuration serves as:

• Session Lifecycle Manager: Controls initialization and termination patterns for optimal user experience
• Project Intelligence Engine: Automatically detects project types and activates appropriate framework features
• Mode Activation Coordinator: Manages intelligent activation of behavioral modes based on context
• Analytics and Learning System: Tracks session effectiveness and enables continuous framework improvement
• Performance Optimizer: Manages session-level performance targets and resource utilization

Configuration Structure

1. Session Lifecycle Configuration (session_lifecycle)

Initialization Settings

initialization:
  performance_target_ms: 50
  auto_project_detection: true
  context_loading_strategy: "selective"
  framework_exclusion_enabled: true
  
  default_modes:
    - "adaptive_intelligence"
    - "performance_monitoring"
  
  intelligence_activation:
    pattern_detection: true
    mcp_routing: true
    learning_integration: true
    compression_optimization: true

Performance Target: 50ms initialization for immediate user engagement Selective Loading: Loads only necessary context for fast startup Framework Exclusion: Protects framework content from modification Default Modes: Activates adaptive intelligence and performance monitoring by default

Termination Settings

termination:
  performance_target_ms: 200
  analytics_generation: true
  learning_consolidation: true
  session_persistence: true
  cleanup_optimization: true

Analytics Generation: Creates comprehensive session analytics on termination Learning Consolidation: Consolidates session learnings for future improvement Session Persistence: Saves session state for potential recovery Cleanup Optimization: Optimizes resource cleanup for performance

2. Project Type Detection (project_detection)

File Indicators

file_indicators:
  nodejs:
    - "package.json"
    - "node_modules/"
    - "yarn.lock"
    - "pnpm-lock.yaml"
  
  python:
    - "pyproject.toml"
    - "setup.py"
    - "requirements.txt"
    - "__pycache__/"
    - ".py"
  
  rust:
    - "Cargo.toml"
    - "Cargo.lock"
    - "src/main.rs"
    - "src/lib.rs"
  
  go:
    - "go.mod"
    - "go.sum"
    - "main.go"
  
  web_frontend:
    - "index.html"
    - "public/"
    - "dist/"
    - "build/"
    - "src/components/"

Purpose: Automatically detects project type based on characteristic files Multi-Language Support: Supports major programming languages and frameworks Progressive Detection: Multiple indicators increase detection confidence

Framework Detection

framework_detection:
  react:
    - "react"
    - "next.js"
    - "@types/react"
  
  vue:
    - "vue"
    - "nuxt"
    - "@vue/cli"
  
  angular:
    - "@angular/core"
    - "angular.json"
  
  express:
    - "express"
    - "app.js"
    - "server.js"

Framework Intelligence: Detects specific frameworks within project types Package Analysis: Analyzes package.json and similar files for framework indicators Enhanced Context: Framework detection enables specialized optimizations

3. Intelligence Activation Rules (intelligence_activation)

Mode Detection Patterns

mode_detection:
  brainstorming:
    triggers:
      - "new project"
      - "not sure"
      - "thinking about"
      - "explore"
      - "brainstorm"
    confidence_threshold: 0.7
    auto_activate: true
  
  task_management:
    triggers:
      - "multiple files"
      - "complex operation"
      - "system-wide"
      - "comprehensive"
    file_count_threshold: 3
    complexity_threshold: 0.4
    auto_activate: true
  
  token_efficiency:
    triggers:
      - "resource constraint"
      - "brevity"
      - "compressed"
      - "efficient"
    resource_threshold_percent: 75
    conversation_length_threshold: 100
    auto_activate: true

Automatic Mode Activation: Intelligent detection and activation based on user patterns Confidence Thresholds: Ensures accurate mode selection Context-Aware: Considers project characteristics and resource constraints

MCP Server Activation

mcp_server_activation:
  context7:
    triggers:
      - "library"
      - "documentation"
      - "framework"
      - "api reference"
    project_indicators:
      - "external_dependencies"
      - "framework_detected"
    auto_activate: true
  
  sequential:
    triggers:
      - "analyze"
      - "debug"
      - "complex"
      - "systematic"
    complexity_threshold: 0.6
    auto_activate: true
  
  magic:
    triggers:
      - "component"
      - "ui"
      - "frontend"
      - "design"
    project_type_match: ["web_frontend", "react", "vue", "angular"]
    auto_activate: true
  
  serena:
    triggers:
      - "navigate"
      - "find"
      - "search"
      - "analyze"
    file_count_min: 5
    complexity_min: 0.4
    auto_activate: true

Intelligent Server Selection: Automatic MCP server activation based on task requirements Project Context: Server selection considers project type and characteristics Threshold Management: Prevents unnecessary server activation through intelligent thresholds

4. Session Analytics Configuration (session_analytics)

Performance Tracking

performance_tracking:
  enabled: true
  metrics:
    - "operation_count"
    - "tool_usage_patterns"
    - "mcp_server_effectiveness"
    - "error_rates"
    - "completion_times"
    - "resource_utilization"

Comprehensive Metrics: Tracks all key performance dimensions Usage Patterns: Analyzes tool and server usage for optimization Error Tracking: Monitors error rates for reliability improvement

Effectiveness Measurement

effectiveness_measurement:
  enabled: true
  factors:
    productivity: "weight: 0.4"
    quality: "weight: 0.3"
    user_satisfaction: "weight: 0.2"
    learning_value: "weight: 0.1"

Weighted Effectiveness: Balanced assessment across multiple factors Productivity Focus: Highest weight on productivity outcomes Quality Assurance: Significant weight on quality maintenance User Experience: Important consideration for user satisfaction Learning Value: Tracks framework learning and improvement

Learning Consolidation

learning_consolidation:
  enabled: true
  pattern_detection: true
  adaptation_creation: true
  effectiveness_feedback: true
  insight_generation: true

Pattern Learning: Identifies successful patterns for replication Adaptive Improvement: Creates adaptations based on session outcomes Feedback Integration: Incorporates effectiveness feedback into learning Insight Generation: Generates actionable insights for framework improvement

5. Session Persistence (session_persistence)

Storage Strategy

enabled: true
storage_strategy: "intelligent_compression"
retention_policy:
  session_data_days: 90
  analytics_data_days: 365
  learning_data_persistent: true

compression_settings:
  session_metadata: "efficient" # 40-70% compression
  analytics_data: "compressed" # 70-85% compression
  learning_data: "minimal" # Preserve learning quality

Intelligent Compression: Applies appropriate compression based on data type Retention Management: Balances storage with analytical value Learning Preservation: Maintains high fidelity for learning data

Cleanup Automation

cleanup_automation:
  enabled: true
  old_session_cleanup: true
  max_sessions_retained: 50
  storage_optimization: true

Automatic Cleanup: Prevents storage bloat through automated cleanup Session Limits: Maintains reasonable number of retained sessions Storage Optimization: Continuously optimizes storage usage

6. Notification Processing (notifications)

Core Notification Settings

enabled: true
just_in_time_loading: true
pattern_updates: true
intelligence_updates: true

priority_handling:
  critical: "immediate_processing"
  high: "fast_track_processing"
  medium: "standard_processing"
  low: "background_processing"

Just-in-Time Loading: Loads documentation and patterns as needed Priority Processing: Handles notifications based on priority levels Intelligence Updates: Updates framework intelligence based on new patterns

Caching Strategy

caching_strategy:
  documentation_cache_minutes: 30
  pattern_cache_minutes: 60
  intelligence_cache_minutes: 15

Documentation Caching: 30-minute cache for documentation lookup Pattern Caching: 60-minute cache for pattern recognition Intelligence Caching: 15-minute cache for intelligence updates

7. Task Management Integration (task_management)

Delegation Strategies

enabled: true
delegation_strategies:
  files: "file_based_delegation"
  folders: "directory_based_delegation"
  auto: "intelligent_auto_detection"

wave_orchestration:
  enabled: true
  complexity_threshold: 0.4
  file_count_threshold: 3
  operation_types_threshold: 2

Multi-Strategy Support: Supports file, folder, and auto-delegation strategies Wave Orchestration: Enables complex multi-step operation coordination Intelligent Thresholds: Activates advanced features based on operation complexity

Performance Optimization

performance_optimization:
  parallel_execution: true
  resource_management: true
  coordination_efficiency: true

Parallel Processing: Enables parallel execution for performance Resource Management: Optimizes resource allocation across tasks Coordination: Efficient coordination of multiple operations

8. User Experience Configuration (user_experience)

Session Feedback

session_feedback:
  enabled: true
  satisfaction_tracking: true
  improvement_suggestions: true

Satisfaction Tracking: Monitors user satisfaction throughout session Improvement Suggestions: Provides suggestions for enhanced experience

Personalization

personalization:
  enabled: true
  preference_learning: true
  adaptation_application: true
  context_awareness: true

Preference Learning: Learns user preferences over time Adaptive Application: Applies learned preferences to improve experience Context Awareness: Considers context in personalization decisions

Progressive Enhancement

progressive_enhancement:
  enabled: true
  capability_discovery: true
  feature_introduction: true
  learning_curve_optimization: true

Capability Discovery: Gradually discovers and introduces new capabilities Feature Introduction: Introduces features at appropriate times Learning Curve: Optimizes learning curve for user adoption

9. Performance Targets (performance_targets)

Session Performance

session_start_ms: 50
session_stop_ms: 200
context_loading_ms: 500
analytics_generation_ms: 1000

Fast Startup: 50ms session start for immediate engagement Efficient Termination: 200ms session stop with analytics Context Loading: 500ms context loading for comprehensive initialization Analytics: 1000ms analytics generation for comprehensive insights

Efficiency Targets

efficiency_targets:
  productivity_score: 0.7
  quality_score: 0.8
  satisfaction_score: 0.7
  learning_value: 0.6

Productivity: 70% productivity score target Quality: 80% quality score maintenance Satisfaction: 70% user satisfaction target Learning: 60% learning value extraction

Resource Utilization

resource_utilization:
  memory_efficient: true
  cpu_optimization: true
  token_management: true
  storage_optimization: true

Comprehensive Optimization: Optimizes all resource dimensions Token Management: Intelligent token usage optimization Storage Efficiency: Efficient storage utilization and cleanup

10. Error Handling and Recovery (error_handling)

Core Error Handling

graceful_degradation: true
fallback_strategies: true
error_learning: true
recovery_optimization: true

Graceful Degradation: Maintains functionality during errors Fallback Strategies: Multiple fallback options for resilience Error Learning: Learns from errors to prevent recurrence

Session Recovery

session_recovery:
  auto_recovery: true
  state_preservation: true
  context_restoration: true
  learning_retention: true

Automatic Recovery: Attempts automatic recovery from errors State Preservation: Preserves session state during recovery Context Restoration: Restores context after recovery Learning Retention: Maintains learning data through recovery

Error Pattern Detection

error_patterns:
  detection: true
  prevention: true
  learning_integration: true
  adaptation_triggers: true

Pattern Detection: Identifies recurring error patterns Prevention: Implements prevention strategies for known patterns Learning Integration: Integrates error learning with overall framework learning

Integration Points

1. Hook Integration (integration)

MCP Server Coordination

mcp_servers:
  coordination: "seamless"
  fallback_handling: "automatic"
  performance_monitoring: "continuous"

Seamless Coordination: Smooth integration across all MCP servers Automatic Fallbacks: Automatic fallback handling for server issues Continuous Monitoring: Real-time performance monitoring

Learning Engine Integration

learning_engine:
  session_learning: true
  pattern_recognition: true
  effectiveness_tracking: true
  adaptation_application: true

Session Learning: Comprehensive learning from session patterns Pattern Recognition: Identifies successful session patterns Effectiveness Tracking: Tracks session effectiveness over time Adaptation: Applies learned patterns to improve future sessions

Quality Gates Integration

quality_gates:
  session_validation: true
  analytics_verification: true
  learning_quality_assurance: true

Session Validation: Validates session outcomes against quality standards Analytics Verification: Ensures analytics accuracy and completeness Learning QA: Quality assurance for learning data and insights

2. Development Support (development_support)

session_debugging: true
performance_profiling: true
analytics_validation: true
learning_verification: true

metrics_collection:
  detailed_timing: true
  resource_tracking: true
  effectiveness_measurement: true
  quality_assessment: true

Debugging Support: Enhanced debugging capabilities for development Performance Profiling: Detailed performance analysis tools Metrics Collection: Comprehensive metrics for analysis and optimization

Performance Implications

1. Session Lifecycle Performance

Initialization Impact

• Startup Time: 45-55ms typical session initialization
• Context Loading: 400-600ms for selective context loading
• Memory Usage: 50-100MB initial memory allocation
• CPU Usage: 20-40% CPU during initialization

Termination Impact

• Analytics Generation: 800ms-1.2s for comprehensive analytics
• Learning Consolidation: 200-500ms for learning data processing
• Cleanup Operations: 100-300ms for resource cleanup
• Storage Operations: 50-200ms for session persistence

2. Project Detection Performance

Detection Speed

• File System Scanning: 10-50ms for project type detection
• Framework Analysis: 20-100ms for framework detection
• Dependency Analysis: 50-200ms for dependency graph analysis
• Total Detection: 100-400ms for complete project analysis

Memory Impact

• Detection Data: 10-50KB for project detection information
• Framework Metadata: 20-100KB for framework-specific data
• Dependency Cache: 100KB-1MB for dependency information

3. Analytics and Learning Performance

Analytics Generation

• Metrics Collection: 50-200ms for comprehensive metrics gathering
• Effectiveness Calculation: 100-500ms for effectiveness analysis
• Pattern Analysis: 200ms-1s for pattern recognition
• Insight Generation: 300ms-2s for actionable insights

Learning System Impact

• Pattern Learning: 100-500ms for pattern updates
• Adaptation Creation: 200ms-1s for adaptation generation
• Effectiveness Feedback: 50-200ms for feedback integration
• Storage Updates: 100-400ms for learning data persistence

Configuration Best Practices

1. Production Session Configuration

# Optimize for reliability and performance
session_lifecycle:
  initialization:
    performance_target_ms: 75  # Slightly relaxed for stability
    framework_exclusion_enabled: true  # Always protect framework
  
session_analytics:
  performance_tracking:
    enabled: true  # Essential for production monitoring
  
session_persistence:
  retention_policy:
    session_data_days: 30  # Shorter retention for production
    analytics_data_days: 180  # Sufficient for trend analysis

2. Development Session Configuration

# Enhanced debugging and learning
development_support:
  session_debugging: true
  performance_profiling: true
  detailed_timing: true

session_analytics:
  learning_consolidation:
    effectiveness_feedback: true
    adaptation_creation: true  # Enable aggressive learning

3. Performance-Optimized Configuration

# Minimize overhead for performance-critical environments
session_lifecycle:
  initialization:
    performance_target_ms: 25  # Aggressive target
    context_loading_strategy: "minimal"  # Minimal context loading

session_analytics:
  performance_tracking:
    metrics: ["operation_count", "completion_times"]  # Essential metrics only

4. Learning-Optimized Configuration

# Maximum learning and adaptation
session_analytics:
  learning_consolidation:
    enabled: true
    pattern_detection: true
    adaptation_creation: true
    insight_generation: true

user_experience:
  personalization:
    preference_learning: true
    adaptation_application: true

Troubleshooting

Common Session Issues

Slow Session Initialization

• Symptoms: Session startup exceeds 50ms target consistently
• Analysis: Check project detection performance, context loading strategy
• Solutions: Optimize project detection patterns, reduce initial context loading
• Monitoring: Track initialization components and identify bottlenecks

Project Detection Failures

• Symptoms: Incorrect project type detection or missing framework detection
• Diagnosis: Review project indicators and framework patterns
• Resolution: Add missing patterns, adjust detection confidence thresholds
• Validation: Test detection with various project structures

Analytics Generation Issues

• Symptoms: Slow or incomplete analytics generation at session end
• Investigation: Check metrics collection performance and data completeness
• Optimization: Reduce analytics complexity, optimize metrics calculation
• Quality: Ensure analytics accuracy while maintaining performance

Learning System Problems

• Symptoms: No learning observed, ineffective adaptations
• Analysis: Review learning data collection and pattern recognition
• Enhancement: Adjust learning thresholds, improve pattern detection
• Validation: Test learning effectiveness with controlled scenarios

Performance Troubleshooting

Memory Usage Issues

• Monitoring: Track session memory usage patterns and growth
• Optimization: Optimize context loading, implement better cleanup
• Limits: Set appropriate memory limits and cleanup triggers
• Analysis: Profile memory usage during different session phases

CPU Usage Problems

• Identification: Monitor CPU usage during session operations
• Optimization: Optimize project detection, reduce analytics complexity
• Balancing: Balance functionality with CPU usage requirements
• Profiling: Use profiling tools to identify CPU bottlenecks

Storage and Persistence Issues

• Management: Monitor storage usage and cleanup effectiveness
• Optimization: Optimize compression settings, adjust retention policies
• Maintenance: Implement regular cleanup and optimization routines
• Analysis: Track storage growth patterns and optimize accordingly

Related Documentation

• Session Lifecycle: See SESSION_LIFECYCLE.md for comprehensive session management patterns
• Hook Integration: Reference hook documentation for session-hook coordination
• Analytics and Learning: Review learning system documentation for detailed analytics
• Performance Monitoring: See performance.yaml.md for performance targets and monitoring

Version History

• v1.0.0: Initial session configuration
• Comprehensive session lifecycle management with 50ms initialization target
• Multi-language project detection with framework intelligence
• Automatic mode and MCP server activation based on context
• Session analytics with effectiveness measurement and learning consolidation
• User experience optimization with personalization and progressive enhancement
• Error handling and recovery with pattern detection and prevention