data_validation

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It discloses that 'remove' is destructive only for validation rules, not cell values, and notes the return type (str or dict). However, it omits other behavioral details such as permissions, error handling, or whether the file is saved/modified in place.

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 well-structured: a clear first sentence, an Args section that groups related parameters, a Returns line, and a Notes section. It is appropriately sized for 19 parameters, avoiding unnecessary verbosity while still being informative.

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 complex tool with 19 parameters and no annotations, the description provides a solid overview and parameter meanings. However, it does not explicitly map which parameters are required for each action (e.g., 'formula' action likely needs the formula parameter), and it misses 'show_error'. The output schema covers the return structure, so that part is acceptable.

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?

The schema has 0% description coverage, so the description compensates by listing and explaining most parameters. It clarifies action-specific semantics (e.g., options for dropdown, operator/value1/value2 for numeric, date1/date2 for date, formula for custom). However, it omits the 'show_error' parameter that appears in the schema, leaving a small but notable gap.

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 opens with 'Add or remove data validation rules on a cell range,' which is a specific verb+resource that clearly states the tool's function. However, it does not explicitly differentiate from sibling tools such as protection or conditional_format, so it stops short of a 5.

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 implies usage for data validation scenarios but provides no explicit guidance on when to use this tool versus alternatives. It includes a caution about the 'remove' action being destructive to validation rules, which is useful context, but it does not offer when/when-not direction or name alternative tools.

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