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dudegladiator

Google Sheets MCP Server

batch_write

Write values to multiple ranges in Google Sheets with one call. Provide a JSON list of range-value pairs to update cells across the spreadsheet.

Instructions

Write values to multiple ranges at once.

Args: spreadsheet_id: The ID of the spreadsheet. data: JSON array of objects with 'range' and 'values' keys. Example: '[{"range": "A1:B2", "values": [[1,2],[3,4]]}, {"range": "D1", "values": [["Hello"]]}]'

Returns: JSON with total cells, rows, columns updated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
spreadsheet_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return format and explains the data structure, but it does not explicitly state that this operation overwrites existing cell values or mention any side effects, permissions, or failure behaviors. The mutation is implied by 'write' but not elaborated.

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 concise and well-structured, with a purpose statement, Args section, and Returns section. It uses a clear example without excess text. Every sentence adds value, and the purpose is front-loaded.

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?

For a two-parameter tool, the description covers purpose, both parameters with format, and the return value. The presence of an output schema (per context) further reduces the need to describe return details. Missing are edge cases like error handling or atomicity, but the tool is simple enough that the description is sufficiently complete.

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

Parameters5/5

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

The schema has no descriptions (0% coverage), so the description must compensate fully. It does: it explains spreadsheet_id and data, includes the exact JSON structure with 'range' and 'values' keys, and provides a concrete example. This exceeds the schema's minimal type-only information.

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 'Write values to multiple ranges at once' with a specific verb and resource. This distinguishes it from sibling tools like batch_read (for reading) and write_cells (likely for a single range). The purpose is unambiguous.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: when writing to multiple ranges efficiently. It does not explicitly name alternatives or when-not-to-use, but the phrase 'at once' implies it is for batch operations, contrasting with repeated single writes. This is clear but lacks explicit 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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