get_data_validation_info

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

The annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds that the tool returns a JSON string, providing helpful behavioral context beyond the annotations, though no additional side effects or permissions are disclosed.

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 concise, using a docstring format with an introductory line followed by explicit parameter descriptions. Every sentence adds value, and the structure is well-organized without redundancy.

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 tool has only two parameters with clear descriptions in the text, annotations covering safety, and an output schema (not shown but present), the description provides sufficient information for an AI agent to correctly invoke the tool.

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 input schema has 0% description coverage, so the description must compensate. The 'Args' section provides clear meanings for 'filepath' and 'sheet_name' ('Path to Excel file' and 'Name of worksheet'), adding value beyond the property names.

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 'Get all data validation rules in a worksheet', specifying the exact verb and resource. It distinguishes itself from sibling tools like validate_excel_range and validate_formula_syntax, which handle different validation tasks.

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 usage context by stating 'identify which cell ranges have validation rules and what types of validation are applied.' It does not explicitly mention when not to use or list alternatives, but the context is clear given the sibling set.

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