jev_choice

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It does mention the return format (choice, confidence, probability distribution), which is useful, but it omits critical context such as whether the tool has side effects, requires authentication (api_key is a parameter), has rate limits, or is read-only. The behavior is only partially described.

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 two sentences long, with the purpose front-loaded and no unnecessary detail. It efficiently conveys the core action and expected output. Slight deduction for not providing any usage context, but the structure itself is clean and focused.

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 tool with 6 parameters, nested objects (state, criteria), and an output schema, the description is incomplete. It does not explain how to structure state or criteria, when to override the model, or how to supply the api_key. While the output schema covers return values, the input construction is left ambiguous, so an agent would struggle to call it correctly.

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 0%, so the description must compensate by explaining parameters. It references a 'defined rubric' (likely criteria) and the act of categorizing, but does not explain the roles of state, instructions, model, api_key, or question_id. This leaves most parameters undocumented, making it hard for an agent to construct valid arguments.

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 the tool routes a single Choice question to Jev and performs categorization/selection from a rubric, with explicit output (choice, confidence, probability distribution). However, it does not explicitly differentiate from sibling tools like jev_score or jev_evaluate, leaving the distinction implied by the name rather than stated.

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 guidance on when to use this tool versus its siblings. The description only says what it does, not when it is appropriate or when to avoid it. No alternatives or exclusions are mentioned, so an agent cannot decide between jev_choice and similar tools.

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