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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by enumerating the compared dimensions, telling the agent what content comes back from a tool with no output schema.

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?

A single front-loaded sentence with no filler; the compared fields are listed inline and every clause earns its place.

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?

With no output schema, the description carries the burden of describing return content, and it does so by naming the compared fields. It stops short of explaining structure or whether missing benchmark overlap is handled, which is a minor gap for a simple read-only 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?

Schema coverage is 100%, with both parameters documented as 'First/Second model slug or name'. The description adds no format, slug-vs-name resolution behavior, or ambiguity handling beyond the schema, so the baseline 3 applies.

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?

States a specific operation (side-by-side comparison) on a specific resource (two models) and enumerates exactly what is compared: BenchGecko score, list price, cheapest provider, context window, shared benchmark scores and Gecko Tests grades. This distinguishes it clearly from get_model (single model) and cheapest_provider (single dimension).

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 usage is implied by the shape of the tool ('for two models') but there is no explicit when-to-use guidance and no mention of alternatives such as calling get_model twice or using get_scorecard. An agent can infer the intent, but nothing routes it deliberately.

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