feat: Add AI coding guidelines and project overview to documentation

.github/instructions/copilot.instructions.md

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+applyTo: '**'
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+# AI Coding Guidelines for TheChart Project
+
+## Project Overview
+- **Project Name:** TheChart (Medication Tracker)
+- **Purpose:** Desktop application for tracking medications and pathologies.
+- **Tech Stack:** Python 3.x, Tkinter, Pandas, modular architecture.
+- **Key Features:**
+  - Add/edit/delete daily medication and pathology entries
+  - Visual graphs and charts
+  - Data export
+  - Keyboard shortcuts
+  - Theming support
+
+## Coding Guidelines
+
+### 1. Code Style
+- Follow PEP8 for Python code (indentation, naming, spacing).
+- Use type hints for all function signatures and variables where possible.
+- Use docstrings for all public methods and classes.
+- Prefer f-strings for string formatting.
+- Use snake_case for variables/functions, CamelCase for classes.
+- Keep lines under 88 characters.
+- Use descriptive names for variables and functions to enhance readability.
+- Avoid global variables; use class attributes or method parameters instead.
+- Use logging for debug/info messages instead of print statements.
+- Use .venv/bin/activate.fish as the virtual environment activation script.
+- The package manager is uv.
+- Use ruff for linting and formatting.
+
+### 2. Architecture & Structure
+- Maintain separation of concerns: UI, data management, and business logic in their respective modules.
+- Use manager classes (e.g., DataManager, UIManager, ThemeManager) for encapsulating related functionality.
+- UI elements and data columns must be generated dynamically based on current medicines/pathologies.
+- New medicines/pathologies should not require changes to main logic—use dynamic lists and keys.
+
+### 3. Error Handling
+- Use try/except for operations that may fail (file I/O, data parsing).
+- Show user-friendly error messages via messagebox dialogs.
+- Log errors and important actions using the logger.
+
+### 4. User Experience
+- Always update the status bar and provide feedback for user actions.
+- Use confirmation dialogs for destructive actions (e.g., deleting entries).
+- Support keyboard shortcuts for all major actions.
+- Keep the UI responsive and avoid blocking operations in the main thread.
+
+### 5. Data Handling
+- Use Pandas DataFrames for all data manipulation.
+- Always check for duplicate dates before adding new entries.
+- Store medicine doses as a string (e.g., "time:dose|time:dose") for each medicine.
+- Support dynamic addition/removal of medicines and pathologies.
+
+### 6. Testing & Robustness
+- Validate all user input before saving.
+- Ensure all UI elements are updated after data changes.
+- Use batch operations for updating UI elements (e.g., clearing and repopulating the table).
+
+### 7. Documentation
+- Keep code well-commented and maintain clear docstrings.
+- Document any non-obvious logic, especially dynamic UI/data handling.
+
+### 8. Performance
+- Use efficient methods for updating UI elements (e.g., batch delete/insert for Treeview).
+- Avoid unnecessary data reloads or UI refreshes.
+
+## When Generating or Reviewing Code
+- Respect the modular structure—add new logic to the appropriate manager or window class.
+- Do not hardcode medicine/pathology names—always use dynamic keys from the managers.
+- Preserve user feedback (status bar, dialogs) for all actions.
+- Maintain keyboard shortcut support for new features.
+- Ensure compatibility with the existing UI and data model.
+- Write clear, concise, and maintainable code with proper type hints and docstrings.
+
+---
+
+**Summary:**
+This project is a modular, extensible Tkinter application for tracking medication and pathology data. Code should be clean, dynamic, user-friendly, and robust, following PEP8 and the architectural patterns already established. All new features or changes should integrate seamlessly with the existing managers and UI paradigms.