judge

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

Given no annotations, the description carries the full burden. It discloses auto-selection of diverse judges, structured output enforcement, retry logic, and inter-rater agreement computation. It does not mention destructive actions (likely none) or rate limits, but these are not critical for a query tool. The description is informative enough.

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 concise and well-structured: it starts with a clear purpose sentence, then lists features, then usage, then parameter details. Every sentence adds value with no redundancy or fluff. It is appropriately sized for a tool with 9 parameters.

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?

The tool has an output schema (not shown) but the description mentions aggregate scores and inter-rater agreement metrics, giving a good idea of output. With 9 parameters and 2 required, the description covers all essential aspects: purpose, features, usage, and parameter details. It is complete for an evaluation 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 has 0% description coverage, but the tool description explains all parameters: prompt, rubric, scale, count, min_tier, free_only, output_format, max_tokens, temperature. It adds meaning beyond the schema by describing their purpose and defaults. This fully compensates for the lack of schema descriptions.

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?

Clearly states the tool rates a single item using multiple judge models and returns aggregate scores. The verb 'rate' and the resource 'single item using judge models' are specific. Distinguishes from siblings like 'batch_judge' (likely for multiple items) and 'compare' (likely for comparing two items).

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?

Explicitly states 'Use this for evaluation tasks: rating translations, code quality, content accuracy, or any rubric-based assessment.' This provides clear when-to-use guidance. However, it does not mention when not to use or direct alternatives, so it loses a point for not excluding sibling tools like 'batch_judge' for multi-item scenarios.

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