Jev Evaluate

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

No annotations are provided, so the description carries the burden. It reveals that questions run in parallel and returns usage information (part of the return object), which is useful. However, it does not disclose potential side effects, authentication requirements beyond the 'TYPESAFE_API_KEY' hint, or rate limits, which are important for an API call. It could be more transparent about error behavior or response schema details.

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, using a code-like format for the questions structure and front-loading the return type. It packs significant information into a few sentences, but the nested JSON notation in the description might be slightly cryptic for some agents, though it is efficiently structured.

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?

This is a complex tool with nested objects and an output schema, but the description covers key aspects: what it does, how to batch questions, and endpoint options. The output schema exists, so return values are documented separately. Gaps include lack of detail on 'state' formats and exact handling of 'zen' endpoint, but overall it is fairly complete for an agent to make basic calls 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?

The schema has 0% description coverage, so the description must compensate. It explains the 'questions' parameter structure with examples of types and nested fields, and mentions 'endpoint' values and 'model' default. However, it does not elaborate on 'state' beyond saying it can be various types, or provide detailed syntax for 'criteria' and 'instructions', leaving some gaps for complex usage.

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 evaluates state against typed questions and returns a structured result, which distinguishes it from siblings by focusing on batch evaluation rather than single-question tools. However, it does not explicitly differentiate from siblings like jev_noul, jev_choice, or jev_score, relying on the name 'evaluate' to convey the aggregated nature.

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?

It provides clear usage guidance: batch independent questions in one call for parallel execution, and mentions endpoint options ('direct' vs 'zen') with a hint about API key for 'direct'. It does not explicitly say when not to use it or name alternatives, but the batching advice implies it is for multi-question scenarios, which are better handled here than with single-question siblings.

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