get_headers
Extract column headers from Excel or CSV files to understand data structure and prepare for analysis.
Instructions
Get the column headers (first row) of a file
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| filePath | Yes | Path to the CSV or Excel file | |
| sheet | No | Sheet name for Excel files (optional) |
Implementation Reference
- src/handlers/data-operations.ts:222-265 (handler)Implementation of the getHeaders handler function that reads the first row (headers) from a CSV/Excel file and returns it as JSON.
async getHeaders(args: ToolArgs): Promise<ToolResponse> { try { const { filePath, sheet } = args; const data = await readFileContent(filePath, sheet); if (data.length === 0) { return { content: [ { type: 'text', text: JSON.stringify({ success: false, error: 'File is empty', }, null, 2), }, ], }; } return { content: [ { type: 'text', text: JSON.stringify({ success: true, headers: data[0], }, null, 2), }, ], }; } catch (error) { return { content: [ { type: 'text', text: JSON.stringify({ success: false, error: error instanceof Error ? error.message : 'Unknown error occurred', }, null, 2), }, ], }; } } - src/index.ts:146-162 (schema)JSON schema definition for the 'get_headers' tool, including input parameters filePath (required) and sheet (optional).
name: 'get_headers', description: 'Get the column headers (first row) of a file', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath'], }, }, - src/index.ts:1205-1206 (registration)Dispatch registration in the CallToolRequestSchema handler that maps the 'get_headers' tool name to the dataOpsHandler.getHeaders method.
case 'get_headers': return await this.dataOpsHandler.getHeaders(toolArgs); - src/index.ts:68-1190 (registration)Overall tool list registration via setRequestHandler(ListToolsRequestSchema) that includes the get_headers tool schema.
this.server.setRequestHandler(ListToolsRequestSchema, async () => ({ tools: [ // Basic Data Tools { name: 'read_file', description: 'Read an entire CSV or Excel file with optional chunking for large files', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional, defaults to first sheet)', }, offset: { type: 'number', description: 'Starting row index for chunked reading (0-based, optional)', }, limit: { type: 'number', description: 'Maximum number of rows to return (optional, enables chunking)', }, }, required: ['filePath'], }, }, { name: 'get_cell', description: 'Get the value of a specific cell using A1 notation', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, cell: { type: 'string', description: 'Cell address in A1 notation (e.g., "A1", "B5")', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'cell'], }, }, { name: 'get_range', description: 'Get values from a range of cells', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, startCell: { type: 'string', description: 'Start cell in A1 notation (e.g., "A1")', }, endCell: { type: 'string', description: 'End cell in A1 notation (e.g., "D10")', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'startCell', 'endCell'], }, }, { name: 'get_headers', description: 'Get the column headers (first row) of a file', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath'], }, }, { name: 'search', description: 'Search for cells containing a specific value', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, searchValue: { type: 'string', description: 'Value to search for', }, exact: { type: 'boolean', description: 'Whether to match exactly or contains (default: false)', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'searchValue'], }, }, { name: 'filter_rows', description: 'Filter rows based on column values', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, column: { type: 'string', description: 'Column name or index (0-based)', }, condition: { type: 'string', description: 'Condition: equals, contains, greater_than, less_than', enum: ['equals', 'contains', 'greater_than', 'less_than'], }, value: { type: 'string', description: 'Value to compare against', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'column', 'condition', 'value'], }, }, { name: 'aggregate', description: 'Perform aggregation operations on a column', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, column: { type: 'string', description: 'Column name or index (0-based)', }, operation: { type: 'string', description: 'Aggregation operation', enum: ['sum', 'average', 'count', 'min', 'max'], }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'column', 'operation'], }, }, // Chunked Reading Tools { name: 'read_file_chunked', description: 'Read large files in manageable chunks to avoid token limits', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, chunkIndex: { type: 'number', description: 'Chunk index to read (0-based, defaults to 0)', default: 0, }, chunkSize: { type: 'number', description: 'Number of rows per chunk (optional, auto-calculated if not provided)', }, }, required: ['filePath'], }, }, { name: 'get_file_info', description: 'Analyze file size and get chunking recommendations', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath'], }, }, // Analytics Tools { name: 'statistical_analysis', description: 'Perform comprehensive statistical analysis on a column', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, column: { type: 'string', description: 'Column name or index (0-based)', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'column'], }, }, { name: 'correlation_analysis', description: 'Calculate correlation between two numeric columns', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, column1: { type: 'string', description: 'First column name or index (0-based)', }, column2: { type: 'string', description: 'Second column name or index (0-based)', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'column1', 'column2'], }, }, { name: 'data_profile', description: 'Generate comprehensive data profiling report for all columns', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath'], }, }, { name: 'pivot_table', description: 'Create pivot table with grouping and aggregation', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file', }, groupBy: { type: 'string', description: 'Column to group by', }, aggregateColumn: { type: 'string', description: 'Column to aggregate', }, operation: { type: 'string', description: 'Aggregation operation', enum: ['sum', 'average', 'count', 'min', 'max'], }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, }, required: ['filePath', 'groupBy', 'aggregateColumn', 'operation'], }, }, // Financial Analysis Tools (CFO-Level) { name: 'dcf_analysis', description: 'Perform Discounted Cash Flow (DCF) valuation analysis for investment evaluation', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file with cash flow data' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, assumptions: { type: 'object', description: 'DCF assumptions (optional)', properties: { initialInvestment: { type: 'number', description: 'Initial investment amount (negative)' }, growthRate: { type: 'number', description: 'Annual growth rate (0.15 = 15%)' }, discountRate: { type: 'number', description: 'Discount rate/WACC (0.12 = 12%)' }, terminalMultiple: { type: 'number', description: 'Terminal value multiple (8x)' }, projectionYears: { type: 'number', description: 'Number of projection years' } } } }, required: ['filePath'] } }, { name: 'budget_variance_analysis', description: 'Analyze budget vs actual performance with variance calculations', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file with budget and actual data' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, actualColumn: { type: 'string', description: 'Column name or index containing actual values' }, budgetColumn: { type: 'string', description: 'Column name or index containing budget values' } }, required: ['filePath', 'actualColumn', 'budgetColumn'] } }, { name: 'ratio_analysis', description: 'Perform comprehensive financial ratio analysis with industry benchmarks', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file with financial statement data' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' } }, required: ['filePath'] } }, { name: 'scenario_modeling', description: 'Perform what-if scenario analysis with multiple assumptions', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file with base data' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, scenarios: { type: 'array', description: 'Array of scenario definitions', items: { type: 'object', properties: { name: { type: 'string', description: 'Scenario name' }, assumptions: { type: 'object', description: 'Key-value pairs of assumption changes', additionalProperties: { type: 'number' } } }, required: ['name', 'assumptions'] } } }, required: ['filePath', 'scenarios'] } }, { name: 'trend_analysis', description: 'Analyze time series trends, growth rates, seasonality, and forecasting for sales and performance data', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file with time series data' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, dateColumn: { type: 'string', description: 'Column name or index containing date/time values' }, valueColumn: { type: 'string', description: 'Column name or index containing numeric values to analyze' }, periods: { type: 'number', description: 'Number of future periods to forecast (default: 12)', default: 12 } }, required: ['filePath', 'dateColumn', 'valueColumn'] } }, // File Operations Tools { name: 'write_file', description: 'Write data to a new CSV or Excel file (supports multiple sheets for Excel)', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path for the new file (must end with .csv, .xlsx, or .xls)', }, data: { type: 'array', description: 'Array of arrays representing rows of data (single sheet mode)', items: { type: 'array', }, }, headers: { type: 'array', description: 'Optional headers for the first row (single sheet mode)', items: { type: 'string', }, }, sheet: { type: 'string', description: 'Sheet name for Excel files (single sheet mode, defaults to "Sheet1")', }, sheets: { type: 'array', description: 'Array of sheet objects for multi-sheet Excel files', items: { type: 'object', properties: { name: { type: 'string', description: 'Sheet name', }, data: { type: 'array', description: 'Array of arrays representing rows of data', items: { type: 'array', }, }, headers: { type: 'array', description: 'Optional headers for the first row', items: { type: 'string', }, }, }, required: ['name', 'data'], }, }, }, required: ['filePath'], }, }, { name: 'add_sheet', description: 'Add a new sheet to an existing Excel file', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the existing Excel file (.xlsx or .xls)', }, sheetName: { type: 'string', description: 'Name for the new sheet', }, data: { type: 'array', description: 'Array of arrays representing rows of data', items: { type: 'array', }, }, headers: { type: 'array', description: 'Optional headers for the first row', items: { type: 'string', }, }, position: { type: 'number', description: 'Position to insert the sheet (0-based index, optional)', }, }, required: ['filePath', 'sheetName', 'data'], }, }, { name: 'write_multi_sheet', description: 'Create a complex Excel file with multiple sheets, formulas, and inter-sheet references', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path for the new Excel file (must end with .xlsx or .xls)', }, sheets: { type: 'array', description: 'Array of sheet definitions', items: { type: 'object', properties: { name: { type: 'string', description: 'Sheet name', }, data: { type: 'array', description: 'Array of arrays representing rows of data', items: { type: 'array', }, }, headers: { type: 'array', description: 'Optional headers for the first row', items: { type: 'string', }, }, formulas: { type: 'array', description: 'Array of formula definitions', items: { type: 'object', properties: { cell: { type: 'string', description: 'Cell address in A1 notation (e.g., "A1", "B5")', }, formula: { type: 'string', description: 'Excel formula (e.g., "=SUM(A1:A10)", "=Sheet1!A1+Sheet2!B2")', }, }, required: ['cell', 'formula'], }, }, }, required: ['name', 'data'], }, }, sheetReferences: { type: 'boolean', description: 'Enable inter-sheet formula references (default: true)', }, }, required: ['filePath', 'sheets'], }, }, { name: 'export_analysis', description: 'Export analysis results (pivot tables, statistics, etc.) to a new file', inputSchema: { type: 'object', properties: { analysisType: { type: 'string', description: 'Type of analysis to export', enum: ['pivot_table', 'statistical_analysis', 'correlation', 'data_profile'], }, sourceFile: { type: 'string', description: 'Path to the source data file', }, outputFile: { type: 'string', description: 'Path for the output file', }, analysisParams: { type: 'object', description: 'Parameters for the analysis (depends on analysisType)', }, }, required: ['analysisType', 'sourceFile', 'outputFile', 'analysisParams'], }, }, { name: 'format_cells', description: 'Apply formatting to Excel cells (fonts, colors, borders, alignment)', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the Excel file (.xlsx or .xls)', }, range: { type: 'string', description: 'Cell range in A1 notation (e.g., "A1", "A1:C5", "B2:D10")', }, styling: { type: 'object', description: 'Formatting options to apply', properties: { font: { type: 'object', description: 'Font styling options', properties: { bold: { type: 'boolean', description: 'Make text bold' }, italic: { type: 'boolean', description: 'Make text italic' }, underline: { type: 'boolean', description: 'Underline text' }, size: { type: 'number', description: 'Font size (e.g., 12, 14, 16)' }, color: { type: 'string', description: 'Font color in ARGB format (e.g., "FFFF0000" for red)' }, name: { type: 'string', description: 'Font name (e.g., "Arial", "Times New Roman")' } } }, fill: { type: 'object', description: 'Background fill options', properties: { color: { type: 'string', description: 'Background color in ARGB format (e.g., "FFFFFF00" for yellow)' }, pattern: { type: 'string', description: 'Fill pattern (default: "solid")' } } }, border: { type: 'object', description: 'Border styling options', properties: { style: { type: 'string', description: 'Border style: thin, medium, thick, dotted, dashed' }, color: { type: 'string', description: 'Border color in ARGB format (e.g., "FF000000" for black)' }, top: { type: 'boolean', description: 'Apply border to top (default: true)' }, bottom: { type: 'boolean', description: 'Apply border to bottom (default: true)' }, left: { type: 'boolean', description: 'Apply border to left (default: true)' }, right: { type: 'boolean', description: 'Apply border to right (default: true)' } } }, alignment: { type: 'object', description: 'Text alignment options', properties: { horizontal: { type: 'string', description: 'Horizontal alignment: left, center, right, justify' }, vertical: { type: 'string', description: 'Vertical alignment: top, middle, bottom' }, wrapText: { type: 'boolean', description: 'Wrap text within cell' }, textRotation: { type: 'number', description: 'Text rotation angle in degrees' } } }, numberFormat: { type: 'string', description: 'Number format (e.g., "$#,##0.00", "0.00%", "mm/dd/yyyy")' } } }, sheet: { type: 'string', description: 'Sheet name (optional, defaults to first sheet)', }, }, required: ['filePath', 'range', 'styling'], }, }, { name: 'auto_fit_columns', description: 'Automatically adjust column widths to fit content in Excel files', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the Excel file (.xlsx or .xls)', }, sheet: { type: 'string', description: 'Sheet name (optional, defaults to all sheets)', }, columns: { type: 'array', description: 'Specific columns to auto-fit (optional, defaults to all columns). Can be column letters (e.g., ["A", "B"]) or numbers (e.g., [1, 2])', items: { oneOf: [ { type: 'string', description: 'Column letter (e.g., "A", "B", "C")' }, { type: 'number', description: 'Column number (1-based, e.g., 1, 2, 3)' } ] } }, minWidth: { type: 'number', description: 'Minimum column width (default: 10)', default: 10 }, maxWidth: { type: 'number', description: 'Maximum column width (default: 60)', default: 60 }, padding: { type: 'number', description: 'Extra padding to add to calculated width (default: 2)', default: 2 } }, required: ['filePath'], }, }, // AI-Powered Tools { name: 'evaluate_formula', description: 'Evaluate an Excel formula with given context', inputSchema: { type: 'object', properties: { formula: { type: 'string', description: 'Excel formula to evaluate (e.g., "=SUM(A1:A10)", "=VLOOKUP(B2,C:D,2,FALSE)")', }, context: { type: 'object', description: 'Cell values and ranges for formula evaluation (optional)', additionalProperties: true, }, }, required: ['formula'], }, }, { name: 'parse_natural_language', description: 'Convert natural language to Excel formula or command', inputSchema: { type: 'object', properties: { query: { type: 'string', description: 'Natural language query (e.g., "sum all sales", "find duplicates", "average by category")', }, filePath: { type: 'string', description: 'Path to file for context (optional)', }, provider: { type: 'string', description: 'Preferred AI provider: anthropic, openai, deepseek, gemini, or local (optional)', enum: ['anthropic', 'openai', 'deepseek', 'gemini', 'local'], }, }, required: ['query'], }, }, { name: 'explain_formula', description: 'Explain what an Excel formula does in plain English', inputSchema: { type: 'object', properties: { formula: { type: 'string', description: 'Excel formula to explain (e.g., "=VLOOKUP(A2,B:C,2,FALSE)")', }, provider: { type: 'string', description: 'Preferred AI provider: anthropic, openai, deepseek, gemini, or local (optional)', enum: ['anthropic', 'openai', 'deepseek', 'gemini', 'local'], }, }, required: ['formula'], }, }, { name: 'ai_provider_status', description: 'Check status of available AI providers', inputSchema: { type: 'object', properties: {}, }, }, { name: 'smart_data_analysis', description: 'AI-powered analysis suggestions for your data', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file to analyze', }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)', }, provider: { type: 'string', description: 'Preferred AI provider: anthropic, openai, deepseek, gemini, or local (optional)', enum: ['anthropic', 'openai', 'deepseek', 'gemini', 'local'], }, }, required: ['filePath'], }, }, // Validation Tools (legacy - to be refactored) { name: 'validate_data_consistency', description: 'Cross-validate data integrity across related files', inputSchema: { type: 'object', properties: { primaryFile: { type: 'string', description: 'Path to the primary data file to validate' }, referenceFiles: { type: 'array', items: { type: 'string' }, description: 'Array of reference file paths for validation' }, validationRules: { type: 'array', items: { type: 'string', enum: ['referential_integrity', 'data_completeness', 'value_ranges'] }, description: 'Specific validation rules to apply (optional, defaults to all)' }, keyColumns: { type: 'array', items: { type: 'string' }, description: 'Specific columns to validate for referential integrity (optional)' }, autoDetectRelationships: { type: 'boolean', description: 'Automatically detect column relationships (default: true)' }, tolerance: { type: 'number', description: 'Tolerance for numeric validations (default: 0.01)' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, reportFormat: { type: 'string', enum: ['summary', 'detailed'], description: 'Format of validation report (default: detailed)' } }, required: ['primaryFile', 'referenceFiles'] } }, // Bulk Operations Tools (legacy - to be refactored) { name: 'bulk_aggregate_multi_files', description: 'Aggregate same column across multiple files in parallel', inputSchema: { type: 'object', properties: { filePaths: { type: 'array', items: { type: 'string' }, description: 'Array of file paths to process' }, column: { type: 'string', description: 'Column name or index (0-based) to aggregate' }, operation: { type: 'string', enum: ['sum', 'average', 'count', 'min', 'max'], description: 'Aggregation operation' }, consolidate: { type: 'boolean', description: 'Whether to return consolidated result or per-file breakdown (default: true)' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' }, filters: { type: 'array', description: 'Optional filters to apply before aggregation', items: { type: 'object', properties: { column: { type: 'string' }, condition: { type: 'string', enum: ['equals', 'contains', 'greater_than', 'less_than', 'not_equals'] }, value: { type: ['string', 'number'] } }, required: ['column', 'condition', 'value'] } } }, required: ['filePaths', 'column', 'operation'] } }, { name: 'bulk_filter_multi_files', description: 'Filter data across multiple files with optional export', inputSchema: { type: 'object', properties: { filePaths: { type: 'array', items: { type: 'string' }, description: 'Array of file paths to process' }, filters: { type: 'array', description: 'Filters to apply to the data', items: { type: 'object', properties: { column: { type: 'string' }, condition: { type: 'string', enum: ['equals', 'contains', 'greater_than', 'less_than', 'not_equals'] }, value: { type: ['string', 'number'] } }, required: ['column', 'condition', 'value'] } }, outputMode: { type: 'string', enum: ['count', 'export', 'summary'], description: 'How to return results: count only, export to file, or summary with counts' }, outputPath: { type: 'string', description: 'Output file path (required when outputMode is "export")' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' } }, required: ['filePaths', 'filters', 'outputMode'] } }, // Excel Workflow Tools { name: 'find_duplicates', description: 'Find and manage duplicate rows in Excel/CSV files with multiple strategies', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file' }, columns: { type: 'array', items: { type: 'string' }, description: 'Columns to check for duplicates (empty = all columns)' }, action: { type: 'string', enum: ['highlight', 'remove', 'export_duplicates', 'report_only'], description: 'What to do with duplicates (default: report_only)' }, keepFirst: { type: 'boolean', description: 'Keep first occurrence when removing (default: true)' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' } }, required: ['filePath'] } }, { name: 'data_cleaner', description: 'Batch data cleaning operations with intelligent detection of common data quality issues', inputSchema: { type: 'object', properties: { filePath: { type: 'string', description: 'Path to the CSV or Excel file' }, operations: { type: 'array', items: { type: 'string', enum: [ 'trim_whitespace', 'fix_dates', 'standardize_numbers', 'remove_empty_rows', 'standardize_phone_formats', 'standardize_names', 'remove_special_chars', 'fix_currency' ] }, description: 'Array of cleaning operations to apply' }, preview: { type: 'boolean', description: 'Show preview before applying changes (default: false)' }, sheet: { type: 'string', description: 'Sheet name for Excel files (optional)' } }, required: ['filePath'] } }, { name: 'vlookup_helper', description: 'Intelligent VLOOKUP setup and execution with error handling and fuzzy matching', inputSchema: { type: 'object', properties: { sourceFile: { type: 'string', description: 'File with data that needs lookup values' }, lookupFile: { type: 'string', description: 'File to lookup values from' }, lookupColumn: { type: 'string', description: 'Column name or index to match on' }, returnColumns: { type: 'array', items: { type: 'string' }, description: 'Columns to return from lookup table (empty = all except lookup column)' }, fuzzyMatch: { type: 'boolean', description: 'Enable fuzzy string matching for lookups (default: false)' }, handleErrors: { type: 'boolean', description: 'Auto-handle #N/A errors with fallbacks (default: true)' }, sourceSheet: { type: 'string', description: 'Sheet name for source Excel file (optional)' }, lookupSheet: { type: 'string', description: 'Sheet name for lookup Excel file (optional)' } }, required: ['sourceFile', 'lookupFile', 'lookupColumn'] } }, ], })); - src/index.ts:13-13 (registration)Import of DataOperationsHandler class used for get_headers handler.
import { DataOperationsHandler } from './handlers/data-operations';