Answer multiple typed questions

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

The description goes well beyond the annotations by disclosing that input is sent to Jev AI, that account credits are consumed, that rate limits apply, and that there are no automatic retries. This is critical behavioral context for an agent deciding cost, side effects, and error-handling expectations.

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 compact and front-loads the core purpose, followed by behavioral and operational notes. Minor redundancy exists between "Returns answers keyed by your question names" and the later "Returns model, answers and usage," but overall every sentence contributes practical information.

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?

With no output schema, the description carries the full burden of explaining return values, and it does so by noting answers are keyed by question names and that model, answers, and usage are returned. It also covers authentication, rate limits, cost, and retry behavior, making the tool safely invocable without missing critical context.

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 coverage is 100%, so the schema already documents the parameters. The description adds useful semantic gloss by explaining that noul means yes/no, choice means a label map, and score means ordered levels, and by noting that answers will be keyed by question names. This adds meaning beyond raw schema constraints.

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 states a specific operation: evaluate 1–64 named questions in one API request. It further disambiguates the three question types and explicitly says it returns answers keyed by question names, which clearly separates it from the sibling tools focused on single decisions.

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 gives clear guidance: "Prefer this for several decisions on the same input," which signals when to choose this over sibling tools. It also states the API key prerequisite. It does not explicitly name alternative tools for single-question cases, so it stops short of full when-not guidance.

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