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Sales Prep MCP

by r28ai
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Python
Remote

gsheets_spreadsheets_values_update

Write values to a specified spreadsheet range so sales workflows can update lead sheets, logs, or CRM data. Supports raw or user-entered input.

Instructions

Sets values in a range of a spreadsheet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesThe A1 notation of the values to update.
valueRangeYesThe request body contains an instance of ValueRange.
spreadsheetIdYesThe ID of the spreadsheet to update.
valueInputOptionYesHow the input data should be interpreted.
includeValuesInResponseNoDetermines if the update response should include the values of the cells that were updated. By default, responses do not include the updated values. If the range to write was larger than the range actually written, the response includes all values in the requested range (excluding trailing empty rows and columns).
responseValueRenderOptionNoDetermines how values in the response should be rendered. The default render option is FORMATTED_VALUE.
responseDateTimeRenderOptionNoDetermines how dates, times, and durations in the response should be rendered. This is ignored if responseValueRenderOption is FORMATTED_VALUE. The default dateTime render option is SERIAL_NUMBER.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, so the write nature is known. But the description adds nothing beyond the name – it does not disclose that existing cell values are overwritten, how valueInputOption affects interpretation, or what the update returns.

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

Conciseness3/5

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

A single front-loaded sentence with no filler, which is tight. But for a 7-parameter mutation tool it is under-specified rather than appropriately sized; conciseness here is closer to omission.

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?

For a write tool with 7 params and no output schema, the description omits overwrite semantics, auth requirements, and response behavior. An agent could call it, but not safely without reading the schema closely.

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% with 7 well-documented parameters, so the schema carries the meaning. The description adds no parameter detail beyond 'in a range', which is baseline 3 for fully documented schemas.

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

Purpose4/5

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

States a specific verb and resource (sets values in a range of a spreadsheet), which an agent can distinguish from gsheets_spreadsheets_values_get by direction of data flow. However it offers no explicit sibling differentiation and largely restates the tool name.

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 when-to-use guidance, no prerequisites, and no mention of the sibling gsheets_spreadsheets_values_get or when reading vs writing applies. The agent must infer context entirely.

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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