Sheets

Output:

{
  "spreadsheet_token": "T4mHsrFyzhXrj0tVzRslUGx8gkA",
  "sheets": [
    {
      "sheet_id": "abc123",
      "title": "Sheet1",
      "index": 0,
      "row_count": 100,
      "column_count": 10
    },
    {
      "sheet_id": "def456",
      "title": "Sheet2",
      "index": 1,
      "hidden": true,
      "row_count": 50,
      "column_count": 5
    }
  ],
  "count": 2
}

Fields:

• sheet_id: The unique ID of the sheet (use this with --sheet flag)
• title: Display name of the sheet
• index: Position of the sheet (0-indexed)
• hidden: Whether the sheet is hidden in the UI
• row_count / column_count: Dimensions of the sheet

Read Sheet Data

tools/bin/lark sheet read <spreadsheet_token> [--sheet <sheet_id>] [--range A1:Z100]

Reads cell values from a Lark spreadsheet.

Options:

• --sheet: Sheet ID to read from (default: first sheet by index)
• --range: Cell range to read (e.g., A1:Z100). Default: all data up to 1000 rows

Output:

{
  "spreadsheet_token": "T4mHsrFyzhXrj0tVzRslUGx8gkA",
  "sheet_id": "abc123",
  "range": "abc123!A1:D10",
  "row_count": 10,
  "column_count": 4,
  "values": [
    ["Header1", "Header2", "Header3", "Header4"],
    ["Value1", "Value2", 123, true],
    ["Row2Val1", null, 456, false]
  ]
}

Note: Cell values preserve their types (string, number, boolean). Empty cells may appear as null or be omitted from rows. Some cells with rich formatting may return structured objects instead of plain values.

Cells containing file attachments return structured objects like:

{
  "fileToken": "JwhmbXFVeoeIkixnmMKlguhzgLe",
  "mimeType": "application/pdf",
  "size": 930948,
  "text": "Contract.pdf",
  "type": "attachment"
}

Use the fileToken with sheet download to download these attachments.

Download Cell Attachments

tools/bin/lark sheet download <file_token> --spreadsheet <spreadsheet_token> -o <output_path>

Downloads a file attachment embedded in a spreadsheet cell. The file_token is the fileToken from sheet read output.

Options:

• --spreadsheet: Spreadsheet token the attachment belongs to (required)
• -o / --output: Output file path (required)

Output:

{
  "file_token": "JwhmbXFVeoeIkixnmMKlguhzgLe",
  "filename": "/tmp/contract.pdf",
  "content_type": "application/pdf",
  "size": 930948
}

Extracting IDs from URLs

The spreadsheet_token is from the spreadsheet URL:

• URL: https://xxx.larksuite.com/sheets/T4mHsrFyzhXrj0tVzRslUGx8gkA
• Token: T4mHsrFyzhXrj0tVzRslUGx8gkA

The sheet_id can be found in the URL query parameter:

• URL: https://xxx.larksuite.com/sheets/T4mHsrFyzhXrj0tVzRslUGx8gkA?sheet=abc123
• Sheet ID: abc123

Which Command to Use

Workflow Examples

Get Overview of a Spreadsheet

# List all sheets first
LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet list T4mHsrFyzhXrj0tVzRslUGx8gkA

# Then read specific sheet
LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read T4mHsrFyzhXrj0tVzRslUGx8gkA --sheet abc123 --range A1:D20

Read Header Row Only

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read T4mHsrFyzhXrj0tVzRslUGx8gkA --range A1:Z1

Read First 50 Rows of Specific Sheet

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read T4mHsrFyzhXrj0tVzRslUGx8gkA --sheet def456 --range A1:Z50

Efficient Extraction with jq

For large spreadsheets, use jq to extract specific data without loading everything into context.

Get Column Headers

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read <token> --range A1:Z1 | jq '.values[0]'

Get Row Count

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read <token> | jq '.row_count'

Extract Specific Column (Column B)

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read <token> | jq '[.values[] | .[1]]'

Find Rows Matching a Value

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read <token> | jq '[.values[] | select(.[0] == "SearchValue")]'

Get First N Rows

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark sheet read <token> | jq '.values[:10]'

Output Format

All commands output JSON. Format appropriately when presenting to user.

Error Handling

Errors return JSON:

{
  "error": true,
  "code": "ERROR_CODE",
  "message": "Description"
}

Common error codes:

• AUTH_ERROR - Need to run lark auth login
• SCOPE_ERROR - Missing documents permissions. Run lark auth login --add --scopes documents
• API_ERROR - Lark API issue (often permissions)
• NO_SHEETS - Spreadsheet has no sheets

Required Permissions

This skill requires the documents scope group (uses drive:drive:readonly). If you see a SCOPE_ERROR, the user needs to add documents permissions:

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark auth login --add --scopes documents

To check current permissions:

LARK_CONFIG_DIR=tools/lark/.lark tools/bin/lark auth status

Limitations

• Maximum 1000 rows read by default (use --range for specific cells)
• Column letters limited to A-Z (26 columns) when auto-detecting range
• Rich text cells may return structured objects instead of plain strings
• Some merged cells may have unexpected value placement