File Organization AI Assistant

File Organization AI Assistant

Version: 1.0.0 Created: 2026-01-05 Category: workspace-hub Related Skills: knowledge-base-system, compliance-check

Overview

AI-driven file organization following FILE_ORGANIZATION_STANDARDS.md. Proposes folder structure when 5+ files accumulate, waits for approval, then executes organization with import updates.

Trigger Conditions

Propose organization when:

• 5+ files of similar type in one directory
• Logical grouping emerges (analysis, validation, etc.)
• Module complexity requires separation
• Code duplication suggests shared functionality

Organization Workflow

Step 1: Recognize Need

def check_organization_needed(directory):
    """Detect when organization is needed."""
    files = list(directory.glob('*.py'))

    if len(files) >= 5:
        # Analyze for patterns
        patterns = detect_patterns(files)
        if patterns:
            return propose_structure(patterns)

    return None

Step 2: Propose Structure

AI: "I notice 12 files related to data analysis. I propose:

data_analysis/
├── processing/    # Data processing (4 files)
├── validation/    # Data validation (3 files)
├── visualization/ # Plotting and charts (3 files)
└── reporting/     # Report generation (2 files)

Each subfolder organized by function.
Should I proceed with this organization?"

Step 3: Wait for Approval

user_approval = wait_for_approval()

if not user_approval:
    return  # Don't proceed

# Only proceed after explicit approval
organize_files(proposed_structure)

Step 4: Execute Organization

def organize_files(structure):
    """Organize files and update imports."""
    for folder, files in structure.items():
        # Create subfolder
        folder_path = create_folder(folder)

        # Move files
        for file in files:
            move_file(file, folder_path)

        # Update imports in moved files
        update_imports(files)

        # Update imports in files that reference moved files
        update_referencing_files(files)

    # Commit with clear message
    git_commit(f"Organize {module_name} into subfolders\n\n{structure_description}")

Naming Conventions

Domain-Driven (Top Level)

Good:

• marine_analysis/ (domain: marine engineering)
• data_processing/ (domain: data operations)
• authentication/ (domain: user auth)

Bad:

• python_files/ (technical, not domain)
• misc/ (unclear purpose)

Functional (Subfolders)

marine_analysis/
├── loads/         # Load calculations
├── stress/        # Stress analysis
├── validation/    # Result validation
└── reporting/     # Report generation

Standard Structures

Python Module

module_name/
├── __init__.py
├── core/          # Core functionality
│   ├── __init__.py
│   └── processor.py
├── models/        # Data models
│   ├── __init__.py
│   └── schema.py
├── utils/         # Module utilities
│   ├── __init__.py
│   └── helpers.py
└── io/            # Input/​output
    ├── __init__.py
    └── readers.py

Test Organization (Mirror src/)

tests/
├── unit/
│   └── module_name/
│       ├── test_core.py
│       └── test_utils.py
├── integration/
│   └── test_pipeline.py
└── fixtures/
    └── sample_data.csv

Import Update Automation

def update_imports(file_path, old_path, new_path):
    """Update imports after file move."""
    content = file_path.read_text()

    # Update relative imports
    old_import = f"from {old_path}"
    new_import = f"from {new_path}"
    content = content.replace(old_import, new_import)

    # Update absolute imports
    old_import = f"import {old_path}"
    new_import = f"import {new_path}"
    content = content.replace(old_import, new_import)

    file_path.write_text(content)

Validation

Before organizing:

• Identified 5+ files for organization
• Recognized clear pattern or domain
• Folder depth won't exceed 5 levels
• Prepared clear proposal with rationale

After organizing:

• All imports updated
• All tests still passing
• Documentation updated
• Git commit with clear message

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Remember: Good organization emerges naturally. Wait until patterns are clear! 📁