Add Dropdown Validation

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

Annotations provide no readOnly or destructive hints, so the description carries the full burden of behavioral disclosure. It states that the tool will restrict a range and return a JSON confirmation, but it does not disclose whether this replaces existing validation, mutates existing cell contents, or what error conditions may arise. That is minimal beyond the basic purpose.

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 front-loaded with a one-sentence purpose and then follows a tight Args/Returns structure. Every line adds a specification or an example, with no redundancy or 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?

For a mutation tool with no annotations and no output schema, the description covers purpose, all parameters, and the return shape, which is enough for an agent to make the call correctly. It does not explain side effects like overwriting existing validation, but that is an edge concern rather than a blocking gap.

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 description coverage is 0%, and the description fully compensates by documenting all four parameters with defaults, examples, and meaning. It clarifies workbook/sheet None meaning active objects, gives an A1-style range example, and explicitly marks values as required with an example, which is valuable because the schema shows ambiguous null defaults.

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 first sentence, 'Restrict a range to a dropdown list of allowed values,' is a specific verb+object statement that names the exact operation and result. It also inherently distinguishes this from the sibling add_number_validation by specifying a dropdown list, so an agent selecting a validation tool can tell them apart.

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 given on when to use this tool versus add_number_validation, get_validation, remove_validation, or other range-modification tools. The intended use case is implied by the purpose statement, but there is no explicit when-to-use, when-not-to-use, or alternative-routing guidance.

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