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vic08

Google Sheets Advanced MCP Server

by vic08

sheets_set_data_validation

Idempotent

Apply data validation rules like dropdowns, number ranges, or custom formulas to Google Sheets cells, restricting input to valid values and preventing entry errors.

Instructions

Sets data validation rules on a range of cells

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeYesThe A1 notation range to validate
strictNoWhether to reject invalid input (true) or show a warning (false)
valuesNoValidation values (dropdown options, number bounds, formula, etc.)
spreadsheet_idYesThe ID of the spreadsheet
validation_typeYesThe type of validation to apply

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds nothing beyond that: it does not say whether existing validation on the range is replaced, whether certain validation_type values require specific entries in `values`, or what happens when `strict` is false.

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?

A single front-loaded sentence with no filler; the operation and target are stated up front. It is efficient, though it borders on under-specification rather than deliberate brevity.

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

Completeness3/5

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

With full schema coverage and annotations covering the write-safety profile, the definition is minimally viable. It still omits the type-dependent semantics of `values` and the effect on pre-existing validation rules, which the schema does not capture either.

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 all five parameters are documented in the schema itself. The description adds no extra meaning about how `validation_type` drives the expected shape of `values` (dropdown options vs. number bounds vs. custom formula), so the baseline of 3 applies.

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?

The description names a specific verb ('Sets') and resource ('data validation rules on a range of cells'), so an agent immediately knows the operation. It does not, however, distinguish itself from adjacent write-style siblings like sheets_add_conditional_formatting or sheets_format_cells, which occupy similar spreadsheet-mutation space.

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?

There is no when-to-use guidance, no exclusions, and no alternatives named. Nothing tells the agent whether to reach for this tool versus conditional formatting or plain range writes when the goal is constraining input.

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