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

With no annotations, the description carries the full behavioral burden and does well: it discloses that the judge is tested on unseen answers, only kept if it beats a common-verdict baseline, and consumes some credit. It does not explain permissions, failure behavior, or what is returned.

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?

Three short sentences, front-loaded with the main action, followed by the key validation and cost details. There is no redundant or wasted wording.

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 charged training operation with no annotations or output schema, the description covers the core mechanism and cost but leaves gaps around outputs, permissions, and failure conditions. It is adequate but not fully complete.

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 description coverage is only 50%: 'name' is described as whose opinions, but 'test_id' has no schema description. The description adds that training uses a test's ratings, which helps identify what test_id refers to, but it does not clarify the 'name' parameter or the relationship between the two parameters.

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 verb and resource: train a judge on a test's ratings. It adds useful scope about validation and cost, but does not explicitly differentiate this tool from siblings such as list_judges or test_prompt.

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?

Usage is implied by the purpose: use it when you want to train a judge from a test's ratings. There is no explicit guidance on when to choose this over related tools, nor any stated prerequisites or exclusions.

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