Set data validation rules on spreadsheet cells to restrict input to specific values, numeric conditions, or text lengths, and display custom error messages.
Set data validation rules for cells
| Name | Required | Description | Default |
|---|---|---|---|
| range | Yes | The range to apply data validation | |
| values | No | Values for the validation rule | |
| message | No | Custom error message | |
| ruleType | Yes | Type of validation rule | |
| spreadsheetId | Yes | The ID of the spreadsheet |
Changes observed during successful MCP inspections.
v2.2.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does not disclose whether existing validation rules are overwritten, how invalid data is handled, if the rule applies to new cells, or any side effects. The reader is left without behavioral expectations beyond 'setting a rule'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the action. It is not bloated or redundant, though it omits important details that are captured in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with no output schema and only five parameters, but the description still feels incomplete. It lacks examples, explanation of rule types, or how the 'values' field interacts with different rule types. The contextual information needed for correct usage is mostly absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described. The description adds no extra semantic meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to set data validation rules on cells. The verb 'set' is specific, and the resource ('data validation rules') distinguishes it from sibling tools like set_formula or format_cells.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as conditional formatting or setting formulas. There is no mention of prerequisites, limitations, or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.