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# Learned User Preferences Pattern
# Adaptive patterns that evolve based on user behavior
user_profile:
id: "example_user"
created: "2025-01-31"
last_updated: "2025-01-31"
sessions_analyzed: 0
learned_preferences:
communication_style:
verbosity_preference: "balanced" # minimal, balanced, detailed
technical_depth: "high" # low, medium, high
symbol_usage_comfort: "high" # low, medium, high
abbreviation_tolerance: "medium" # low, medium, high
workflow_patterns:
preferred_thinking_mode: "--think-hard"
mcp_server_preferences:
- "serena" # Most frequently beneficial
- "sequential" # High success rate
- "context7" # Frequently requested
mode_activation_frequency:
task_management: 0.8 # High usage
token_efficiency: 0.6 # Medium usage
brainstorming: 0.3 # Low usage
introspection: 0.4 # Medium usage
project_type_expertise:
python: 0.9 # High proficiency
react: 0.7 # Good proficiency
javascript: 0.8 # High proficiency
documentation: 0.6 # Medium proficiency
performance_preferences:
speed_vs_quality: "quality_focused" # speed_focused, balanced, quality_focused
compression_tolerance: 0.7 # How much compression user accepts
context_size_preference: "medium" # small, medium, large
learning_insights:
effective_patterns:
- pattern: "serena + morphllm hybrid"
success_rate: 0.92
context: "large refactoring tasks"
- pattern: "sequential + context7"
success_rate: 0.88
context: "complex debugging"
- pattern: "magic + context7"
success_rate: 0.85
context: "UI component creation"
ineffective_patterns:
- pattern: "playwright without setup"
success_rate: 0.3
context: "testing without proper configuration"
improvement: "always check test environment first"
optimization_opportunities:
- area: "context compression"
current_efficiency: 0.6
target_efficiency: 0.8
strategy: "increase abbreviation usage"
- area: "mcp coordination"
current_efficiency: 0.7
target_efficiency: 0.85
strategy: "better server selection logic"
adaptive_thresholds:
mode_activation:
brainstorming: 0.6 # Lowered from 0.7 due to user preference
task_management: 0.9 # Raised from 0.8 due to frequent use
token_efficiency: 0.65 # Adjusted based on tolerance
introspection: 0.5 # Lowered due to user comfort with meta-analysis
mcp_server_confidence:
serena: 0.65 # Lowered due to high success rate
sequential: 0.75 # Standard
context7: 0.7 # Slightly lowered due to frequent success
magic: 0.85 # Standard
morphllm: 0.7 # Lowered due to hybrid usage success
playwright: 0.9 # Raised due to setup issues
personalization_rules:
communication:
- "Use technical terminology freely"
- "Provide implementation details"
- "Include performance considerations"
- "Balance symbol usage with clarity"
workflow:
- "Prefer serena for analysis tasks"
- "Use sequential for complex problems"
- "Always validate with quality gates"
- "Optimize for long-term maintainability"
error_handling:
- "Provide detailed error context"
- "Suggest multiple solutions"
- "Include learning opportunities"
- "Track error patterns for prevention"
continuous_learning:
feedback_integration:
explicit_feedback: true
implicit_feedback: true # Based on user actions
outcome_tracking: true
pattern_evolution:
refinement_frequency: "weekly"
adaptation_rate: 0.1
stability_threshold: 0.95
quality_metrics:
user_satisfaction_score: 0.0 # To be measured
task_completion_rate: 0.0 # To be measured
efficiency_improvement: 0.0 # To be measured