get_table_stats

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe read. The description adds value by highlighting that the row counts are 'approximate,' which is important behavioral context beyond the annotations, and specifies the scope ('for tables').

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, front-loaded sentence that immediately communicates the tool's purpose. No filler or redundancy. It earns its place perfectly.

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 simple optional-filter nature, the schema covers parameters, annotations cover safety, and an output schema exists, the description is sufficient. The main missing element is usage alternatives, but that is addressed in the usage_guidelines dimension. It is complete enough for a basic statistics 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 100% coverage with descriptions for both optional parameters (schema_name and database_name). The description does not add extra parameter details, but the schema already documents the parameters well. Baseline 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: 'Get approximate row counts and storage sizes for tables.' This is a specific verb+resource combination that distinguishes it from sibling stats tools like get_object_details or get_storage_diagnostics, which focus on other aspects.

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. There are many sibling tools for retrieving statistics, but the description does not mention any conditions, exclusions, or preferred scenarios. It simply states what the tool does.

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