Jev Choice

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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the return shape (choice, probabilities, confidence), but it does not disclose how the model arrives at the choice, whether state/instructions influence the decision, or whether there are side effects or endpoint-specific behaviors. This is adequate but thin.

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 short and front-loads the core action and return value. The inline example JSON for criteria is awkward and unclear, but the overall length is appropriate and there is no filler.

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 five parameters, three required ones, nested objects, and no annotations, this description is incomplete. It omits parameter semantics and usage differentiation, although the output schema may cover return structure. The agent would need to infer too much about state, instructions, and criteria.

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, but it only mentions 'criteria' with a confusing example and never explains 'state', 'instructions', 'model', or 'endpoint'. Three of the five parameters are required, and the description provides almost no guidance on how to populate them correctly.

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 action ('Pick one option') and the output ('choice + probabilities + confidence'), which gives the agent a usable sense of the tool's function. However, it never explains where the options come from or how this tool differs from siblings like jev_evaluate and jev_score, and the inline 'criteria: {"option": "rubric..."}' is cryptic.

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 only implied: the agent should call this when a single option needs to be chosen. There is no explicit guidance about when not to use it, no mention of alternatives among the sibling tools, and no exclusion criteria, leaving the agent to infer the use case.

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