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update_table_column_name_tool

Update column names in a Google Sheets table by specifying column indices and new names. Rename multiple columns at once with matching lists.

Instructions

Update column names in a table.

This tool updates existing column names in a table by their index.
The number of column indices must match the number of new column names.

Args:
    spreadsheet_name: Name of the spreadsheet
    sheet_name: Name of the sheet containing the table
    table_name: Name of the table to update column names in
    column_indices: List of column indices to update (0-based)
    new_column_names: List of new column names

Returns:
    JSON string with success status and update details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spreadsheet_nameYesThe name of the Google Spreadsheet
sheet_nameYesThe name of the sheet containing the table
table_nameYesName of the table to update column names in
column_indicesYesList of column indices to update (0-based)
new_column_namesYesList of new column names (must match column_indices count)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explains the matching requirement and return format (JSON with success status and details). However, it does not discuss whether the operation is reversible, potential side effects on formulas, or required permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two short paragraphs. The first sentence provides the main action, and the Args section is structured. Some redundancy exists but it remains clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all key aspects: action, parameters, constraint, and return value. With full schema coverage and an output schema, it is adequately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description does not add significant meaning beyond the schema. The matching constraint is already noted in the schema's new_column_names description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it updates column names in a table, specifies the method (by index), and includes a constraint (matching counts). This distinguishes it from siblings like update_table_column_type_tool and update_table_title_tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. While the name and description imply column renaming, it does not mention when not to use it or suggest other tools for adding/deleting columns.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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