Set data validation

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

Beyond the annotations, the description discloses key behaviors: OMIT condition_type removes validation, overwrites any previous rule, one rule per cell, strict=true rejects vs false warns, and input_message provides help text. This is substantial behavioral context and aligns with destructiveHint=true.

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 dense but every sentence contributes operational value: setting, clearing, dropdown behavior, strict mode, input message, and overwrite semantics. The core set/clear behavior is front-loaded, with no filler.

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?

Given the rich schema, nested range object, and annotations, the description covers all decisions an agent needs: how to configure a rule, when to omit fields to clear, what strict does, and what gets overwritten. No output schema is needed for a mutation tool whose success response is standard.

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?

Although schema coverage is 100%, the description adds significant meaning: ONE_OF_LIST plus show_custom_ui=true creates the dropdown, ONE_OF_RANGE takes a formula reference, CUSTOM_FORMULA is evaluated per cell, and condition_values shapes are explained with examples. This goes well beyond the raw schema.

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 states a specific action ('Sets — or clears — a data-validation rule on a grid range') and names the exact resource and scope. It clearly distinguishes itself from formatting, conditional formats, and sheet-management siblings by focusing entirely on data validation rules.

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?

The description explains when to use different condition types and how to clear validation, which gives actionable usage guidance. It doesn't explicitly name alternatives, but no sibling tool covers data validation, so the omission is minor.

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