feat(cell validation): add comprehensive data validation capabilities (#37)

- Add cell_validation.py module for Excel data validation metadata extraction
- Implement get_data_validation_for_cell() and get_all_validation_ranges()
- Include validation metadata in read_data_from_excel responses automatically
- Add get_data_validation_info MCP tool for validation rule summaries
- Resolve range references in list validations to actual cell values
- Support all validation types: list, whole, decimal, date, time, textLength
- Include operators (between, notBetween, equal, greaterThan, etc.) in metadata

This allows LLMs to understand Excel validation constraints including
dropdown options, numeric ranges, date constraints, and text length limits.

TOOLS.md

@@ -337,3 +337,23 @@ validate_excel_range(
 - `start_cell`: Starting cell of range
 - `end_cell`: Optional ending cell of range
 - Returns: Validation result message
+
+### get_data_validation_info
+
+Get data validation rules and metadata for a worksheet.
+
+```python
+get_data_validation_info(filepath: str, sheet_name: str) -> str
+```
+
+- `filepath`: Path to Excel file
+- `sheet_name`: Target worksheet name
+- Returns: JSON string containing all data validation rules with metadata including:
+  - Validation type (list, whole, decimal, date, time, textLength)
+  - Operator (between, notBetween, equal, greaterThan, lessThan, etc.)
+  - Allowed values for list validations (resolved from ranges)
+  - Formula constraints for numeric/date validations
+  - Cell ranges where validation applies
+  - Prompt and error messages
+
+**Note**: The `read_data_from_excel` tool automatically includes validation metadata for individual cells when available.