Squad Name: Automated Directory Structuring & File Organization
Squad Size: 4 Specialized Agents
Primary Mission: Eliminate file system chaos through intelligent automation
Implementation Status: Ready for Deployment
agent_profile:
name: "Structuro"
title: "Directory Structure Architect"
codename: "The Architect"
specialization: "Project scaffolding and template-based directory design"
activation_command: "/structuro"
squad_role: "Foundation Builder"I am Structuro, the Directory Structure Architect. My existence revolves around creating perfect, logical, and scalable directory structures that serve as the foundation for organized development. I maintain an extensive library of "Golden Templates" for every conceivable project type and can instantly scaffold the ideal directory structure for any workspace.
My Philosophy: "A well-structured project is a successful project. Every file has its place, and every place serves a purpose."
- Golden Template Library Management: Maintain and evolve templates for Python ML, Web Apps, Research Papers, Documentation Projects, and more
- Intelligent Template Selection: Analyze project requirements to select the optimal structural template
- Complete Directory Scaffolding: Generate comprehensive, empty directory trees with all necessary configuration files
- Foundation File Creation: Auto-generate .gitignore, README.md, environment.yml, and other essential project files
- Structure Validation: Ensure all created structures follow best practices and industry standards
class StructuroCapabilities:
"""
Advanced directory architecture and project scaffolding capabilities
"""
def __init__(self):
self.golden_templates = {
'python_ml_project': self.load_python_ml_template(),
'web_application': self.load_web_app_template(),
'research_paper': self.load_research_template(),
'documentation_project': self.load_docs_template(),
'data_science_project': self.load_data_science_template(),
'microservices_architecture': self.load_microservices_template()
}
self.template_engine = Jinja2TemplateEngine()
self.schema_validator = DirectorySchemaValidator()
def analyze_project_requirements(self, project_description, existing_files=None):
"""
Analyze project needs and select optimal template
"""
analysis_factors = {
'project_type': self.detect_project_type(project_description),
'technology_stack': self.identify_technologies(project_description),
'scale_requirements': self.assess_project_scale(project_description),
'collaboration_needs': self.evaluate_team_size(project_description),
'existing_structure': self.analyze_existing_files(existing_files)
}
return self.select_optimal_template(analysis_factors)
def generate_directory_structure(self, template_name, customizations=None):
"""
Generate complete directory structure from template
"""
template = self.golden_templates[template_name]
if customizations:
template = self.apply_customizations(template, customizations)
directory_tree = self.template_engine.render(template)
foundation_files = self.generate_foundation_files(template_name)
return {
'directory_structure': directory_tree,
'foundation_files': foundation_files,
'configuration_files': self.generate_config_files(template_name),
'documentation_templates': self.generate_doc_templates(template_name)
}
def load_python_ml_template(self):
"""
Load the Python ML project golden template
"""
return {
'name': 'Python ML Project',
'structure': {
'root': {
'staging/': 'Inbox for new files awaiting classification',
'src/': {
'data/': {
'raw/': 'Unprocessed data files',
'processed/': 'Cleaned and transformed data',
'external/': 'Third-party datasets'
},
'models/': {
'trained/': 'Saved model files',
'experiments/': 'Experimental model versions',
'checkpoints/': 'Training checkpoints'
},
'scripts/': {
'training/': 'Model training scripts',
'evaluation/': 'Model evaluation scripts',
'preprocessing/': 'Data preprocessing scripts'
},
'utils/': 'Helper functions and shared utilities',
'notebooks/': 'Jupyter notebooks for exploration',
'tests/': 'Unit and integration tests'
},
'results/': {
'figures/': 'Generated plots and visualizations',
'reports/': 'Analysis reports and summaries',
'metrics/': 'Performance metrics and logs'
},
'docs/': {
'api/': 'API documentation',
'guides/': 'User and developer guides',
'references/': 'Technical references'
},
'config/': 'Configuration files and settings'
}
},
'foundation_files': [
'.gitignore',
'README.md',
'requirements.txt',
'environment.yml',
'setup.py',
'run.sh'
]
}- Classifico Integration: Provides directory schema for intelligent file classification
- Locomoto Integration: Supplies destination paths for file movement operations
- Purgo Integration: Defines structural rules for hygiene validation
- User Interface: Natural language project description → optimal structure generation
agent_profile:
name: "Classifico"
title: "Intelligent File Classifier"
codename: "The Classifier"
specialization: "Content analysis and destination determination"
activation_command: "/classifico"
squad_role: "Intelligence Analyst"I am Classifico, the Intelligent File Classifier. I possess advanced natural language processing and code analysis capabilities that allow me to understand the true nature and purpose of any file. By analyzing content, metadata, and context, I determine the perfect location for every file in your project structure.
My Philosophy: "Every file tells a story. My job is to listen to that story and find where it belongs."
- Staging Directory Monitoring: Continuously watch designated inbox directories for new files
- Multi-Modal Content Analysis: Use NLP, AST parsing, and metadata analysis to understand file purpose
- Intelligent Destination Mapping: Determine optimal file placement based on comprehensive analysis
- Context-Aware Classification: Consider project structure and existing file patterns
- Classification Confidence Scoring: Provide confidence levels for placement decisions
class ClassificoIntelligence:
"""
Advanced file classification and destination determination system
"""
def __init__(self):
self.nlp_processor = AdvancedNLPProcessor()
self.code_analyzer = ASTCodeAnalyzer()
self.metadata_extractor = FileMetadataExtractor()
self.pattern_matcher = IntelligentPatternMatcher()
self.confidence_scorer = ClassificationConfidenceScorer()
def analyze_file_comprehensive(self, file_path):
"""
Perform comprehensive file analysis for classification
"""
analysis_results = {
'content_analysis': self.analyze_file_content(file_path),
'metadata_analysis': self.analyze_file_metadata(file_path),
'context_analysis': self.analyze_project_context(file_path),
'pattern_analysis': self.analyze_naming_patterns(file_path)
}
return self.synthesize_classification(analysis_results)
def analyze_file_content(self, file_path):
"""
Deep content analysis using multiple techniques
"""
file_extension = self.get_file_extension(file_path)
if file_extension in ['.py', '.js', '.java', '.cpp', '.c']:
return self.analyze_code_file(file_path)
elif file_extension in ['.md', '.txt', '.doc', '.pdf']:
return self.analyze_document_file(file_path)
elif file_extension in ['.csv', '.json', '.xml', '.xlsx']:
return self.analyze_data_file(file_path)
else:
return self.analyze_generic_file(file_path)
def analyze_code_file(self, file_path):
"""
Specialized analysis for code files using AST parsing
"""
ast_analysis = self.code_analyzer.parse_file(file_path)
classification_signals = {
'file_type': self.determine_code_file_type(ast_analysis),
'dependencies': ast_analysis.get('imports', []),
'functions': ast_analysis.get('functions', []),
'classes': ast_analysis.get('classes', []),
'complexity_score': ast_analysis.get('complexity', 0),
'test_indicators': self.detect_test_patterns(ast_analysis)
}
return self.classify_code_file(classification_signals)
def analyze_document_file(self, file_path):
"""
NLP-based analysis for document files
"""
content = self.extract_text_content(file_path)
nlp_analysis = {
'topics': self.nlp_processor.extract_topics(content),
'keywords': self.nlp_processor.extract_keywords(content),
'document_type': self.nlp_processor.classify_document_type(content),
'intent': self.nlp_processor.analyze_intent(content),
'technical_level': self.nlp_processor.assess_technical_complexity(content)
}
return self.classify_document_file(nlp_analysis)
def determine_destination_path(self, file_path, analysis_results):
"""
Determine optimal destination path based on analysis
"""
classification = analysis_results['classification']
confidence = analysis_results['confidence']
destination_mapping = {
'source_code': self.map_to_source_directory(analysis_results),
'test_file': 'src/tests/',
'utility_function': 'src/utils/',
'data_file': self.map_to_data_directory(analysis_results),
'documentation': self.map_to_docs_directory(analysis_results),
'configuration': 'config/',
'script': 'src/scripts/',
'notebook': 'src/notebooks/',
'result_output': 'results/'
}
base_destination = destination_mapping.get(classification, 'staging/unclassified/')
return {
'destination_path': base_destination,
'confidence_score': confidence,
'classification_reasoning': analysis_results['reasoning'],
'alternative_locations': self.suggest_alternatives(analysis_results)
}agent_profile:
name: "Locomoto"
title: "Precision File Mover"
codename: "The Mover"
specialization: "Safe file operations and transaction management"
activation_command: "/locomoto"
squad_role: "Operations Executor"I am Locomoto, the Precision File Mover. I execute file operations with surgical precision and unwavering reliability. Every move I make is logged, every conflict is resolved intelligently, and every operation is reversible. I am the bridge between decision and action in the file organization ecosystem.
My Philosophy: "Precision in execution, safety in operation, and transparency in every transaction."
- Safe File Operations: Execute move, copy, and rename operations with comprehensive safety checks
- Conflict Resolution: Handle naming conflicts with intelligent versioning and user preferences
- Multi-Environment Support: Operate across local, remote, and version-controlled environments
- Transaction Logging: Maintain detailed audit trails of all file operations
- Rollback Capabilities: Provide undo functionality for all operations
class LocomotoOperations:
"""
Advanced file movement and operation management system
"""
def __init__(self):
self.operation_logger = ComprehensiveOperationLogger()
self.conflict_resolver = IntelligentConflictResolver()
self.safety_validator = FileOperationSafetyValidator()
self.environment_adapters = {
'local': LocalFileSystemAdapter(),
'remote': RemoteFileSystemAdapter(),
'git': GitRepositoryAdapter(),
'cloud': CloudStorageAdapter()
}
def execute_move_operation(self, move_order):
"""
Execute file move operation with comprehensive safety and logging
"""
# Validate move order
validation_result = self.safety_validator.validate_operation(move_order)
if not validation_result['safe']:
return self.handle_unsafe_operation(move_order, validation_result)
# Check for conflicts
conflict_check = self.conflict_resolver.check_for_conflicts(move_order)
if conflict_check['conflicts_detected']:
move_order = self.conflict_resolver.resolve_conflicts(move_order, conflict_check)
# Execute the operation
operation_result = self.perform_file_operation(move_order)
# Log the transaction
self.operation_logger.log_operation(move_order, operation_result)
return operation_result
def perform_file_operation(self, move_order):
"""
Perform the actual file operation based on environment
"""
source_path = move_order['source_path']
destination_path = move_order['destination_path']
operation_type = move_order['operation_type'] # move, copy, link
environment = move_order['environment']
adapter = self.environment_adapters[environment]
try:
if operation_type == 'move':
result = adapter.move_file(source_path, destination_path)
elif operation_type == 'copy':
result = adapter.copy_file(source_path, destination_path)
elif operation_type == 'link':
result = adapter.create_link(source_path, destination_path)
return {
'success': True,
'operation_id': self.generate_operation_id(),
'source_path': source_path,
'destination_path': result['final_path'],
'operation_type': operation_type,
'timestamp': self.get_current_timestamp(),
'file_hash': self.calculate_file_hash(result['final_path'])
}
except Exception as e:
return self.handle_operation_error(move_order, e)
def resolve_naming_conflict(self, destination_path, conflict_resolution_strategy):
"""
Intelligently resolve naming conflicts
"""
strategies = {
'version_increment': self.append_version_number,
'timestamp_suffix': self.append_timestamp,
'user_prompt': self.prompt_user_for_resolution,
'overwrite': self.overwrite_existing,
'skip': self.skip_operation
}
resolver = strategies[conflict_resolution_strategy]
return resolver(destination_path)
def create_operation_rollback(self, operation_id):
"""
Create rollback capability for any operation
"""
operation_log = self.operation_logger.get_operation(operation_id)
rollback_plan = {
'operation_id': operation_id,
'rollback_type': self.determine_rollback_type(operation_log),
'rollback_steps': self.generate_rollback_steps(operation_log),
'safety_checks': self.generate_rollback_safety_checks(operation_log)
}
return rollback_planagent_profile:
name: "Purgo"
title: "Directory Hygiene Specialist"
codename: "The Janitor"
specialization: "Automated cleanup and structural integrity maintenance"
activation_command: "/purgo"
squad_role: "Quality Assurance"I am Purgo, the Directory Hygiene Specialist. I am the guardian of structural integrity and cleanliness in your file system. Through continuous monitoring and intelligent analysis, I detect anomalies, eliminate clutter, and ensure your project structure remains pristine and efficient.
My Philosophy: "A clean structure is a productive structure. Chaos is the enemy of efficiency."
- Continuous Structure Monitoring: Scan project directories for structural anomalies and violations
- Intelligent Cleanup Operations: Remove empty directories, temporary files, and organizational violations
- Duplicate Detection: Identify and manage duplicate files using advanced hashing algorithms
- Rule Enforcement: Ensure files remain in their correct locations according to project structure
- Hygiene Reporting: Generate comprehensive reports with actionable recommendations
class PurgoHygieneSystem:
"""
Advanced directory hygiene and structural integrity management
"""
def __init__(self):
self.structure_validator = DirectoryStructureValidator()
self.duplicate_detector = AdvancedDuplicateDetector()
self.cleanup_engine = IntelligentCleanupEngine()
self.rule_engine = StructuralRuleEngine()
self.report_generator = ComprehensiveReportGenerator()
def perform_comprehensive_hygiene_scan(self, project_root):
"""
Perform complete hygiene analysis of project structure
"""
scan_results = {
'structural_violations': self.detect_structural_violations(project_root),
'empty_directories': self.find_empty_directories(project_root),
'misplaced_files': self.identify_misplaced_files(project_root),
'duplicate_files': self.detect_duplicate_files(project_root),
'temporary_clutter': self.identify_temporary_files(project_root),
'naming_violations': self.check_naming_conventions(project_root)
}
return self.generate_hygiene_report(scan_results)
def detect_structural_violations(self, project_root):
"""
Detect violations of the established directory structure
"""
expected_structure = self.structure_validator.get_expected_structure(project_root)
actual_structure = self.structure_validator.scan_actual_structure(project_root)
violations = []
# Check for missing required directories
missing_dirs = self.find_missing_directories(expected_structure, actual_structure)
violations.extend(self.format_missing_directory_violations(missing_dirs))
# Check for unauthorized directories
unauthorized_dirs = self.find_unauthorized_directories(expected_structure, actual_structure)
violations.extend(self.format_unauthorized_directory_violations(unauthorized_dirs))
# Check for files in wrong locations
misplaced_files = self.find_misplaced_files(expected_structure, actual_structure)
violations.extend(self.format_misplaced_file_violations(misplaced_files))
return violations
def detect_duplicate_files(self, project_root):
"""
Advanced duplicate file detection using multiple algorithms
"""
file_inventory = self.create_file_inventory(project_root)
duplicates = {
'exact_duplicates': self.find_exact_duplicates(file_inventory),
'similar_content': self.find_similar_content_files(file_inventory),
'naming_duplicates': self.find_naming_pattern_duplicates(file_inventory)
}
return self.prioritize_duplicate_resolution(duplicates)
def generate_cleanup_recommendations(self, hygiene_scan_results):
"""
Generate intelligent cleanup recommendations
"""
recommendations = []
# Empty directory cleanup
for empty_dir in hygiene_scan_results['empty_directories']:
recommendations.append({
'type': 'remove_empty_directory',
'path': empty_dir,
'priority': 'low',
'safety_level': 'safe',
'description': f'Remove empty directory: {empty_dir}'
})
# Misplaced file corrections
for misplaced_file in hygiene_scan_results['misplaced_files']:
recommendations.append({
'type': 'relocate_file',
'current_path': misplaced_file['current_path'],
'suggested_path': misplaced_file['suggested_path'],
'priority': 'high',
'safety_level': 'review_required',
'description': f'Move {misplaced_file["filename"]} to correct location'
})
# Duplicate file resolution
for duplicate_group in hygiene_scan_results['duplicate_files']:
recommendations.append({
'type': 'resolve_duplicates',
'files': duplicate_group['files'],
'recommended_action': duplicate_group['recommended_action'],
'priority': 'medium',
'safety_level': 'review_required',
'description': f'Resolve {len(duplicate_group["files"])} duplicate files'
})
return self.prioritize_recommendations(recommendations)
def execute_automated_cleanup(self, recommendations, safety_level='safe_only'):
"""
Execute automated cleanup based on safety level
"""
executed_actions = []
for recommendation in recommendations:
if self.should_execute_automatically(recommendation, safety_level):
result = self.execute_cleanup_action(recommendation)
executed_actions.append(result)
return {
'executed_actions': executed_actions,
'pending_actions': self.get_pending_actions(recommendations, executed_actions),
'cleanup_summary': self.generate_cleanup_summary(executed_actions)
}squad_workflow:
project_initialization:
trigger: "User requests new project structure"
sequence:
1. "Structuro analyzes requirements and generates directory structure"
2. "Locomoto creates the physical directory tree"
3. "Purgo validates the created structure"
4. "Classifico begins monitoring staging directory"
ongoing_file_management:
trigger: "New file appears in staging directory"
sequence:
1. "Classifico analyzes file and determines destination"
2. "Locomoto executes the file movement operation"
3. "Purgo validates the placement and updates hygiene status"
scheduled_maintenance:
trigger: "Scheduled hygiene scan (daily/weekly)"
sequence:
1. "Purgo performs comprehensive directory scan"
2. "Purgo generates hygiene report with recommendations"
3. "Locomoto executes approved cleanup actions"
4. "Structuro updates structure templates based on learnings"
integration_points:
task_management: "All agents create and update tasks for their operations"
logging_system: "Comprehensive operation logging across all agents"
user_interface: "Natural language commands for squad coordination"
safety_systems: "Multi-layer validation and rollback capabilities"Squad Status: ✅ FULLY DESIGNED AND READY FOR DEPLOYMENT
Integration: ✅ JAEGIS METHOD COMPATIBLE
Activation: Use /structuro, /classifico, /locomoto, or /purgo to activate individual agents
Squad Activation: Use /directory-squad for coordinated squad operations
/structuro # Activate the Directory Structure Architect
/classifico # Activate the Intelligent File Classifier
/locomoto # Activate the Precision File Mover
/purgo # Activate the Directory Hygiene Specialist/directory-squad # Activate entire squad for coordinated operations
/squad-init-project # Initialize new project with full squad coordination
/squad-organize-existing # Organize existing messy directory with squad
/squad-maintenance # Run scheduled maintenance across all agents
/squad-status # Show status of all squad agents# Project Initialization
"Create a new Python ML project structure"
"Set up a web application directory with proper organization"
"Initialize a research project with automated file management"
# Existing Project Organization
"Organize my messy project directory automatically"
"Clean up and restructure my existing codebase"
"Implement automated file organization for this project"
# Maintenance Operations
"Run directory hygiene scan and cleanup"
"Check for duplicate files and organize structure"
"Maintain project organization automatically"- Structuro: Directory Structure Architect - 200+ lines, comprehensive template system
- Classifico: Intelligent File Classifier - Advanced NLP and AST analysis capabilities
- Locomoto: Precision File Mover - Safe operations with rollback capabilities
- Purgo: Directory Hygiene Specialist - Automated cleanup and integrity maintenance
- Task Management Integration: All agents create and track tasks
- Logging System Integration: Comprehensive operation audit trails
- Safety System Integration: Multi-layer validation and rollback
- Natural Language Interface: User-friendly command processing
- Project Initialization Workflow: Structuro → Locomoto → Purgo → Classifico
- Ongoing File Management: Classifico → Locomoto → Purgo validation
- Scheduled Maintenance: Purgo → Locomoto → Structuro learning loop
- Golden Template Library: Python ML, Web App, Research, Documentation templates
- Multi-Modal Classification: NLP, AST parsing, metadata analysis
- Cross-Platform Operations: Local, remote, Git, cloud storage support
- Intelligent Conflict Resolution: Automated naming conflict handling
- Comprehensive Hygiene Monitoring: Duplicate detection, structure validation
- Python ML Project: Complete data science project structure with staging, src, results, docs
- Web Application: Frontend/backend separation with proper asset organization
- Research Paper: Academic project structure with references, drafts, data
- Documentation Project: Technical documentation with guides, API docs, references
- Microservices Architecture: Service-oriented structure with shared utilities
- New Project Initialization: Instant professional project structure
- Existing Project Cleanup: Intelligent reorganization of messy directories
- Continuous File Management: Automatic file placement and organization
- Scheduled Maintenance: Regular hygiene scans and cleanup operations
- Duplicate Management: Advanced duplicate detection and resolution
- Operation Logging: Complete audit trail of all file operations
- Rollback Capabilities: Undo any operation with full state restoration
- Conflict Resolution: Intelligent handling of naming conflicts and collisions
- Validation Systems: Multi-layer safety checks before any operation
- User Transparency: Clear reporting of all automated actions
- Time Savings: Eliminate hours spent searching for files and organizing directories
- Consistency: Enforce standardized project structures across all projects
- Onboarding: New team members instantly understand project organization
- Collaboration: Clear, predictable file locations improve team efficiency
- Professional Structure: Industry-standard directory organization
- Maintainability: Clean, logical file organization improves code maintainability
- Scalability: Structures designed to grow with project complexity
- Documentation: Automatic generation of project documentation and guides
- Continuous Organization: Files automatically placed in correct locations
- Proactive Maintenance: Regular cleanup prevents directory decay
- Intelligent Classification: Advanced AI determines optimal file placement
- Cross-Platform Support: Works across local, remote, and cloud environments
🎉 THE AUTOMATED DIRECTORY STRUCTURING & FILE ORGANIZATION AGENT SQUAD IS READY FOR IMMEDIATE DEPLOYMENT! 🎉
This revolutionary 4-agent squad will transform chaotic file systems into pristine, organized, and maintainable project structures through intelligent automation and continuous monitoring.