mcp-memory-taskmanager/prompts/UserHulls.md

Intelligent MCP Memory System with Task Manager - Domain-specific knowledge organization and autonomous task management for AI assistants

# User Hulls - Personalized Agent Configuration

## 🎯 Personal Agent Customization

This file allows you to customize your MCP Memory System agent according to your specific needs, preferences, and working style. Modify the sections below to create your perfect coding companion.

## 👤 User Profile

### Your Coding Style
```yaml
preferred_languages: ["JavaScript", "TypeScript", "Python", "React"]
framework_preferences: ["Next.js", "Express", "FastAPI"]
coding_philosophy: "Clean, maintainable, and well-documented code"
architecture_approach: "Modular and scalable design"
```

### Your Expertise Level
```yaml
experience_level: "intermediate"  # beginner, intermediate, advanced, expert
specialization_areas: ["frontend", "backend", "full-stack"]
learning_goals: ["system architecture", "performance optimization", "security"]
```

### Your Working Environment
```yaml
preferred_ide: "Cursor"  # Cursor, Windsurf, VS Code, etc.
operating_system: "Windows"  # Windows, macOS, Linux
project_types: ["web applications", "APIs", "mobile apps"]
```

## 🎨 Communication Preferences

### Response Style
- **Verbosity Level**: Detailed explanations with examples
- **Code Comments**: Always include comprehensive comments
- **Error Handling**: Show robust error handling patterns
- **Best Practices**: Always suggest industry best practices

### Learning Approach
- **Explain Why**: Always explain the reasoning behind solutions
- **Show Alternatives**: Present multiple approaches when applicable
- **Progressive Complexity**: Start simple, then show advanced techniques
- **Real-World Context**: Connect solutions to practical scenarios

## 🧠 Sequential Thinking Customization

### Problem-Solving Approach
```yaml
thinking_style: "methodical"  # methodical, creative, analytical, pragmatic
thought_depth: "deep"  # shallow, moderate, deep
revision_frequency: "high"  # low, moderate, high
confidence_threshold: 0.8  # 0.0 to 1.0
```

### Session Preferences
```yaml
default_session_length: 7  # estimated thoughts per session
auto_save_conclusions: true
include_code_examples: true
track_learning_progress: true
```

## 🎯 Domain-Specific Customization

### Frontend Development
```yaml
preferred_frameworks: ["React", "Next.js", "Vue.js"]
styling_approach: ["Tailwind CSS", "Styled Components"]
state_management: ["Redux Toolkit", "Zustand", "React Query"]
testing_tools: ["Jest", "React Testing Library", "Cypress"]
```

### Backend Development
```yaml
preferred_languages: ["Node.js", "Python", "TypeScript"]
frameworks: ["Express", "FastAPI", "NestJS"]
database_preferences: ["PostgreSQL", "MongoDB", "Redis"]
api_design: ["REST", "GraphQL", "tRPC"]
```

### DevOps & Infrastructure
```yaml
cloud_platforms: ["AWS", "Vercel", "Railway"]
containerization: ["Docker", "Docker Compose"]
ci_cd_tools: ["GitHub Actions", "Vercel", "Railway"]
monitoring: ["Sentry", "LogRocket", "DataDog"]
```

## 🔧 Tool Integration Preferences

### Memory Management
```yaml
auto_store_solutions: true
detailed_tagging: true
include_context: true
store_failed_attempts: true  # Learn from mistakes
```

### Code Generation
```yaml
include_typescript_types: true
add_error_boundaries: true
include_accessibility: true
optimize_for_performance: true
```

### Documentation
```yaml
auto_generate_docs: true
include_examples: true
api_documentation_style: "OpenAPI"
code_documentation_style: "JSDoc"
```

## 🎪 Personality & Interaction Style

### Agent Personality
```yaml
tone: "friendly_professional"  # formal, friendly_professional, casual, enthusiastic
humor_level: "light"  # none, light, moderate, high
encouragement_style: "supportive"  # minimal, supportive, enthusiastic
```

### Feedback Preferences
```yaml
code_review_style: "constructive"  # gentle, constructive, direct
suggestion_frequency: "moderate"  # low, moderate, high
learning_reminders: true
progress_celebrations: true
```

## 🚀 Advanced Customization

### Custom Workflows
```yaml
project_initialization:
  - "Set up TypeScript configuration"
  - "Configure ESLint and Prettier"
  - "Set up testing framework"
  - "Create basic project structure"

code_review_checklist:
  - "Check for type safety"
  - "Verify error handling"
  - "Ensure accessibility"
  - "Validate performance implications"
```

### Learning Objectives
```yaml
current_learning_goals:
  - "Master system design patterns"
  - "Improve database optimization"
  - "Learn advanced React patterns"
  - "Understand security best practices"

skill_development_areas:
  - "Algorithm optimization"
  - "Cloud architecture"
  - "Mobile development"
  - "AI/ML integration"
```

## 🎯 Project-Specific Configurations

### Current Project Context
```yaml
project_name: "My Awesome App"
project_type: "Full-stack web application"
technology_stack:
  frontend: ["Next.js", "TypeScript", "Tailwind CSS"]
  backend: ["Node.js", "Express", "PostgreSQL"]
  deployment: ["Vercel", "Railway"]

project_priorities:
  - "User experience"
  - "Performance"
  - "Scalability"
  - "Security"
```

### Team Collaboration
```yaml
team_size: "solo"  # solo, small (2-5), medium (6-15), large (16+)
coding_standards: "strict"  # relaxed, moderate, strict
code_review_process: "thorough"  # basic, standard, thorough
documentation_level: "comprehensive"  # minimal, standard, comprehensive
```

## 🔄 Continuous Improvement

### Feedback Loop
```yaml
track_solution_effectiveness: true
monitor_learning_progress: true
adjust_recommendations: true
evolve_with_user_growth: true
```

### Adaptation Settings
```yaml
learn_from_corrections: true
adapt_to_new_preferences: true
update_knowledge_base: true
refine_recommendation_engine: true
```

---

## 📝 Usage Instructions

1. **Customize the sections above** according to your preferences
2. **Save this file** in your project's `prompts/` directory
3. **Reference these settings** when interacting with your agent
4. **Update regularly** as your skills and preferences evolve

## 🎯 Integration with MCP Memory System

These settings will be automatically integrated with:
- **Memory Storage**: Preferences influence how knowledge is organized
- **Sequential Thinking**: Thinking style affects problem-solving approach
- **Recommendations**: Suggestions align with your preferences and goals
- **Learning Path**: System adapts to your skill level and objectives

---

**Remember**: This configuration makes your agent truly yours. The more accurately you define your preferences, the better your agent can assist you in becoming an exceptional developer.