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

No annotations are supplied, so the description carries the full disclosure burden. It does add real information beyond the name by saying the output pairs each judge with its agreement rate against its rater, which hints at a read-only listing. It says nothing about ordering, pagination, or what 'account' scoping means in practice.

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?

One short sentence with no filler, and the most important noun (trained judges) is front-loaded. It is slightly under-specified as a fragment rather than a complete sentence, which costs a point.

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 zero-parameter read tool with no annotations and no output schema, the description does give a rough sketch of the return contents (judges plus agreement frequency). It stops short of describing the response shape or whether the list is exhaustive, which the absence of an output schema makes more important.

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 tool takes zero parameters, so there is nothing for the description to disambiguate and it introduces no misleading parameter claims. Baseline 4 applies for a parameterless signature.

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 is a noun phrase naming the resource ('this account's trained judges') plus the extra data returned ('how often each agreed with its rater'), but it never states the verb 'list' explicitly. It is distinguishable from the sibling train_judge by framing judges as already trained, yet the phrasing reads as a data fragment rather than a stated action.

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?

There is no explicit when-to-use guidance, no mention of when not to call it, and no reference to alternatives. The only implied usage is that this is for inspecting judges after training via train_judge, which the agent must infer.

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