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sheets_update_table

Idempotent

Update an existing Google Sheets table by its table ID, changing properties like name, range, or column definitions.

Instructions

Update an existing native Google Sheets table by tableId

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOptional new table name
rangeNoOptional new A1 notation range for the table, e.g. "A1:D20"
fieldsYesRequired field mask for the table update, e.g. "name", "range", "columnProperties", or "name,range"
columnsNoOptional replacement column definitions for the table
tableIdYesThe ID of the table to update
sheetNameNoName of the target sheet when updating the table range
spreadsheetIdYesThe ID of the spreadsheet (found in the URL after /d/)
Behavior2/5

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

Annotations already disclose idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context beyond the basic operation; it does not explain field mask semantics, that column definitions replace the entire table columns, or any side effects of the update.

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

Conciseness5/5

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

The description is a single, well-formed sentence with no filler. It is front-loaded with the verb 'Update' and clearly identifies the resource and key identifier (tableId). Every word adds value.

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

Completeness2/5

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

This is a moderately complex tool with 7 parameters and a required field mask, yet the description is only one sentence. It does not explain how the field mask selects which properties to update, nor that column definitions replace all columns. The schema provides parameter details, but the overall operation semantics are not conveyed, leaving the agent to infer critical behavior.

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 description coverage is 100%, so the schema already explains all parameters. The description itself adds no parameter-level meaning. Baseline of 3 is appropriate given complete schema coverage, but the description does not enhance understanding of field mask usage or parameter interactions.

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 uses a specific verb and resource: 'Update an existing native Google Sheets table by tableId'. This clearly distinguishes the tool from siblings like sheets_add_table, sheets_delete_table, and sheets_get_tables, which correspond to other lifecycle operations.

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

Usage Guidelines3/5

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

The word 'existing' indicates this is for modifying tables that already exist, which implicitly differentiates it from creation tools. However, there is no explicit guidance on when to use this versus alternatives like sheets_add_table or sheets_get_tables, nor any mention of prerequisites or exclusions.

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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