Merge two spreadsheets on an ID column, the VLOOKUP job, and see how each row matched.
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Use this when the user wants to stack or append many spreadsheets into one: "combine multiple csv files into one", "merge 12 monthly excel files", "combine excel files with different column names", "append these exports into one sheet", "combine all sheets into one". Takes 1 to 24 CSV, TSV or .xlsx files (or pasted tables). Aligns columns by identical name, then same name with different case or spacing, then a synonym table (Amt = Amount, Txn Date = Date, Memo = Description), then fuzzy spelling matches that are listed for confirmation; a specific column is not folded into a more general one (Spouse First Name stays separate from First Name). Adds a Source file column, decides day/month order once per file, reads EU number formats, removes total rows and repeated headers (listed), and reports each column decision. Returns an Excel workbook (Combined, Column mapping, Files, Excluded rows, Summary) and a CSV. Does not join files side by side on an ID (use join_spreadsheets) and does not do mail merge.
The spreadsheets to stack, 1 to 24 CSV, TSV or .xlsx files in order, e.g. jan.csv, feb.csv, mar.csv. One workbook alone stacks all of its sheets.
Only when no files are attached: pasted tables to stack, e.g. [{"name":"Jan","csv":"Date,Amt\n1/5/2025,12.50"}].
Stack every sheet of each workbook instead of only the first sheet with data. Default: true when a single workbook is given, otherwise false.
Your column decisions: source header -> output column, e.g. {"Amt":"Amount","Txn Date":"Date"}. Overrides automatic matching.
Day/month order for numeric dates: auto (default) decides once per file from the data and says when it had to assume US month/day; MDY or DMY forces it for all files. Example: DMY.
Only if the headings were detected wrongly: the header row number used for EVERY file (counting non-blank rows in a CSV, sheet rows in Excel), e.g. 4.
Default true: in short category-style columns, spellings that differ only by case (Revenue vs revenue) become the spelling seen first (first file wins); each change is listed. false keeps values as typed.
Default false: rows identical in every column are counted and reported but kept. true drops the repeats (e.g. overlapping monthly exports).
Use this when the user wants to stack or append many spreadsheets into one: "combine multiple csv files into one", "merge 12 monthly excel files", "combine excel files with different column names", "append these exports into one sheet", "combine all sheets into one". Takes 1 to 24 CSV, TSV or .xlsx files (or pasted tables). Aligns columns by identical name, then same name with different case or spacing, then a synonym table (Amt = Amount, Txn Date = Date, Memo = Description), then fuzzy spelling matches that are listed for confirmation; a specific column is not folded into a more general one (Spouse First Name stays separate from First Name). Adds a Source file column, decides day/month order once per file, reads EU number formats, removes total rows and repeated headers (listed), and reports each column decision. Returns an Excel workbook (Combined, Column mapping, Files, Excluded rows, Summary) and a CSV. Does not join files side by side on an ID (use join_spreadsheets) and does not do mail merge.
| Argument | Type | Description |
|---|---|---|
| files | array | The spreadsheets to stack, 1 to 24 CSV, TSV or .xlsx files in order, e.g. jan.csv, feb.csv, mar.csv. One workbook alone stacks all of its sheets. |
| tables | array | Only when no files are attached: pasted tables to stack, e.g. [{"name":"Jan","csv":"Date,Amt\n1/5/2025,12.50"}]. |
| all_sheets | boolean | Stack every sheet of each workbook instead of only the first sheet with data. Default: true when a single workbook is given, otherwise false. |
| column_map | object | Your column decisions: source header -> output column, e.g. {"Amt":"Amount","Txn Date":"Date"}. Overrides automatic matching. |
| date_order | string | Day/month order for numeric dates: auto (default) decides once per file from the data and says when it had to assume US month/day; MDY or DMY forces it for all files. Example: DMY. |
| header_row | integer | Only if the headings were detected wrongly: the header row number used for EVERY file (counting non-blank rows in a CSV, sheet rows in Excel), e.g. 4. |
| unify_case | boolean | Default true: in short category-style columns, spellings that differ only by case (Revenue vs revenue) become the spelling seen first (first file wins); each change is listed. false keeps values as typed. |
| remove_duplicate_rows | boolean | Default false: rows identical in every column are counted and reported but kept. true drops the repeats (e.g. overlapping monthly exports). |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"files": {
"type": "array",
"items": {
"type": "object",
"required": [
"download_url",
"file_id"
],
"properties": {
"file_id": {
"type": "string",
"description": "ChatGPT file id, e.g. file_abc123."
},
"file_name": {
"type": "string",
"description": "Original file name if known, e.g. statement.pdf."
},
"mime_type": {
"type": "string",
"description": "Media type if known, e.g. application/pdf."
},
"download_url": {
"type": "string",
"description": "Temporary download link for the file, supplied by ChatGPT."
}
}
},
"maxItems": 24,
"minItems": 1,
"description": "The spreadsheets to stack, 1 to 24 CSV, TSV or .xlsx files in order, e.g. jan.csv, feb.csv, mar.csv. One workbook alone stacks all of its sheets."
},
"tables": {
"type": "array",
"items": {
"type": "object",
"required": [
"name",
"csv"
],
"properties": {
"csv": {
"type": "string",
"maxLength": 200000,
"description": "The table as CSV or tab-separated text with a header row, e.g. \"Date,Amount\\n01/05/2025,12.50\"."
},
"name": {
"type": "string",
"maxLength": 80,
"description": "A label for this table, e.g. January."
}
}
},
"maxItems": 24,
"minItems": 1,
"description": "Only when no files are attached: pasted tables to stack, e.g. [{\"name\":\"Jan\",\"csv\":\"Date,Amt\\n1/5/2025,12.50\"}]."
},
"all_sheets": {
"type": "boolean",
"description": "Stack every sheet of each workbook instead of only the first sheet with data. Default: true when a single workbook is given, otherwise false."
},
"column_map": {
"type": "object",
"description": "Your column decisions: source header -> output column, e.g. {\"Amt\":\"Amount\",\"Txn Date\":\"Date\"}. Overrides automatic matching.",
"propertyNames": {
"type": "string",
"maxLength": 80
},
"additionalProperties": {
"type": "string",
"maxLength": 80
}
},
"date_order": {
"enum": [
"auto",
"MDY",
"DMY"
],
"type": "string",
"description": "Day/month order for numeric dates: auto (default) decides once per file from the data and says when it had to assume US month/day; MDY or DMY forces it for all files. Example: DMY."
},
"header_row": {
"type": "integer",
"maximum": 1000,
"minimum": 1,
"description": "Only if the headings were detected wrongly: the header row number used for EVERY file (counting non-blank rows in a CSV, sheet rows in Excel), e.g. 4."
},
"unify_case": {
"type": "boolean",
"description": "Default true: in short category-style columns, spellings that differ only by case (Revenue vs revenue) become the spelling seen first (first file wins); each change is listed. false keeps values as typed."
},
"remove_duplicate_rows": {
"type": "boolean",
"description": "Default false: rows identical in every column are counted and reported but kept. true drops the repeats (e.g. overlapping monthly exports)."
}
}
}Use this when the user wants to merge, match or VLOOKUP two spreadsheets on a shared ID column: "vlookup two spreadsheets", "merge two excel files by customer ID", "match orders to customers", "why are some rows not matching", "find which IDs are missing from the other file". Attach both files (CSV, TSV or .xlsx; or one workbook with two sheets) or paste both tables. Left join by default (all left rows kept); inner and full joins are available. Auto-detects the key column and explains why (override with left_key/right_key, or give a composite key). Key clean-ups are applied in order and each is counted: spaces, case, look-alike characters, Excel number formats (12345.0, 1.2345E+05), separators, leading zeros (C00123 = C123), letter prefix used by one file only; turn any off with skip_normalizations. Reports unmatched rows on both sides with a likely reason and closest key, duplicate keys with fan-out counts, and returns an Excel workbook (Merged, Unmatched left, Unmatched right, Duplicates, Summary) plus a merged CSV. Does not do mail merge (letters, labels, emails), does not compare two versions of one file cell by cell, and does not edit the original files.
| Argument | Type | Description |
|---|---|---|
| left_key | any | Key column name(s) in the left file; leave out to auto-detect. Use a list for a composite key, e.g. "customer_id" or ["First Name","Last Name"]. |
| join_type | string | left (default, like VLOOKUP): keep every left row and add matching right columns. inner: only rows found in both. full: everything from both files, matched where possible. Example: left. |
| left_file | object | The main file whose rows you keep (CSV, TSV or .xlsx), e.g. orders.csv. A workbook with two sheets can be passed alone: sheet 1 is joined to sheet 2. |
| right_key | any | Key column name(s) in the right file; leave out to auto-detect. Use a list for a composite key, e.g. "Customer ID" or ["First Name","Last Name"]. |
| duplicates | string | When a key appears more than once in the right file: all (default) keeps every match and warns about the extra rows; first keeps only the first match, like VLOOKUP. Example: first. |
| left_sheet | string | Sheet name in the left workbook, e.g. Orders. Default: the first sheet with data. |
| left_table | string | Only when no file is attached: the left (main) table pasted as CSV or tab-separated text with a header row, e.g. "order_id,customer_id,amount\nSO-1,C123,40.00". |
| right_file | object | The lookup file whose columns are added (CSV, TSV or .xlsx), e.g. customers.xlsx. |
| right_sheet | string | Sheet name in the right workbook, e.g. Customers. Default: the first sheet with data (or the second sheet when both tables are in one workbook). |
| right_table | string | Only when no file is attached: the right (lookup) table pasted as CSV or tab-separated text with a header row, e.g. "customer_id,name\nC00123,Acme Supply". |
| left_header_row | integer | Only if the headings were detected wrongly: the row number of the left file's header (counting non-blank rows in a CSV, sheet rows in Excel), e.g. 4. |
| right_header_row | integer | Only if the headings were detected wrongly: the row number of the right file's header, e.g. 3. |
| skip_normalizations | array | Key clean-ups to turn OFF when IDs that differ only that way are really different, e.g. ["case"] for case-sensitive IDs or ["zeros"] when 0123 and 123 are different codes. Options: trim, case, unicode, excel, separators, zeros, prefix. |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {
"left_key": {
"anyOf": [
{
"type": "string",
"maxLength": 120
},
{
"type": "array",
"items": {
"type": "string",
"maxLength": 120
},
"maxItems": 4,
"minItems": 1
}
],
"description": "Key column name(s) in the left file; leave out to auto-detect. Use a list for a composite key, e.g. \"customer_id\" or [\"First Name\",\"Last Name\"]."
},
"join_type": {
"enum": [
"left",
"inner",
"full"
],
"type": "string",
"description": "left (default, like VLOOKUP): keep every left row and add matching right columns. inner: only rows found in both. full: everything from both files, matched where possible. Example: left."
},
"left_file": {
"type": "object",
"required": [
"download_url",
"file_id"
],
"properties": {
"file_id": {
"type": "string",
"description": "ChatGPT file id, e.g. file_abc123."
},
"file_name": {
"type": "string",
"description": "Original file name if known, e.g. statement.pdf."
},
"mime_type": {
"type": "string",
"description": "Media type if known, e.g. application/pdf."
},
"download_url": {
"type": "string",
"description": "Temporary download link for the file, supplied by ChatGPT."
}
},
"description": "The main file whose rows you keep (CSV, TSV or .xlsx), e.g. orders.csv. A workbook with two sheets can be passed alone: sheet 1 is joined to sheet 2."
},
"right_key": {
"anyOf": [
{
"type": "string",
"maxLength": 120
},
{
"type": "array",
"items": {
"type": "string",
"maxLength": 120
},
"maxItems": 4,
"minItems": 1
}
],
"description": "Key column name(s) in the right file; leave out to auto-detect. Use a list for a composite key, e.g. \"Customer ID\" or [\"First Name\",\"Last Name\"]."
},
"duplicates": {
"enum": [
"all",
"first"
],
"type": "string",
"description": "When a key appears more than once in the right file: all (default) keeps every match and warns about the extra rows; first keeps only the first match, like VLOOKUP. Example: first."
},
"left_sheet": {
"type": "string",
"maxLength": 100,
"description": "Sheet name in the left workbook, e.g. Orders. Default: the first sheet with data."
},
"left_table": {
"type": "string",
"maxLength": 400000,
"description": "Only when no file is attached: the left (main) table pasted as CSV or tab-separated text with a header row, e.g. \"order_id,customer_id,amount\\nSO-1,C123,40.00\"."
},
"right_file": {
"type": "object",
"required": [
"download_url",
"file_id"
],
"properties": {
"file_id": {
"type": "string",
"description": "ChatGPT file id, e.g. file_abc123."
},
"file_name": {
"type": "string",
"description": "Original file name if known, e.g. statement.pdf."
},
"mime_type": {
"type": "string",
"description": "Media type if known, e.g. application/pdf."
},
"download_url": {
"type": "string",
"description": "Temporary download link for the file, supplied by ChatGPT."
}
},
"description": "The lookup file whose columns are added (CSV, TSV or .xlsx), e.g. customers.xlsx."
},
"right_sheet": {
"type": "string",
"maxLength": 100,
"description": "Sheet name in the right workbook, e.g. Customers. Default: the first sheet with data (or the second sheet when both tables are in one workbook)."
},
"right_table": {
"type": "string",
"maxLength": 400000,
"description": "Only when no file is attached: the right (lookup) table pasted as CSV or tab-separated text with a header row, e.g. \"customer_id,name\\nC00123,Acme Supply\"."
},
"left_header_row": {
"type": "integer",
"maximum": 1000,
"minimum": 1,
"description": "Only if the headings were detected wrongly: the row number of the left file's header (counting non-blank rows in a CSV, sheet rows in Excel), e.g. 4."
},
"right_header_row": {
"type": "integer",
"maximum": 1000,
"minimum": 1,
"description": "Only if the headings were detected wrongly: the row number of the right file's header, e.g. 3."
},
"skip_normalizations": {
"type": "array",
"items": {
"enum": [
"trim",
"case",
"unicode",
"excel",
"separators",
"zeros",
"prefix"
],
"type": "string"
},
"maxItems": 7,
"description": "Key clean-ups to turn OFF when IDs that differ only that way are really different, e.g. [\"case\"] for case-sensitive IDs or [\"zeros\"] when 0123 and 123 are different codes. Options: trim, case, unicode, excel, separators, zeros, prefix."
}
}
}