List benchmarks

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

Given no annotations, the description carries the burden of behavioral disclosure. It indicates that the tool returns a catalog (read operation) and lists the attributes included. It does not contradict any implicit behaviors, though it could be more explicit about it being a pure read operation.

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 sentence that efficiently conveys the tool's output. Every word adds value, 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 simple listing tool with no parameters and no output schema, the description is sufficiently complete. It specifies the content of the catalog, which is all the agent needs to understand the tool's functionality.

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 zero parameters, so schema coverage is 100%. The description adds no parameter information because there are none to describe. Per the guidelines, 0 parameters yields a baseline score of 4.

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 that the tool returns a benchmark catalog with four specific attributes: descriptions, dimensions, directions, and units. It uses a specific verb (implicitly 'list') and resource ('benchmarks'), distinguishing it from sibling tools like list_models or get_ranking.

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 when to use the tool (to get a catalog of benchmarks), but does not explicitly state when not to use it or provide alternatives. However, with zero parameters and a straightforward purpose, the usage context is clear from the name and description alone.

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