Jev multi-primitive fan-out evaluation

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does reveal useful traits: parallel fan-out, no latency/cost increase with extra questions, and the semantics of the three primitives. However, it does not disclose side effects, output shape, error behavior, or whether the operation is safe/read-only, leaving an agent with incomplete behavioral context.

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 tight sentences with no filler. The core action, target, and key constraints are all front-loaded in the first sentence, and the second sentence conveys a relevant performance characteristic. Every word earns its place.

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 description adequately covers what to send (batch of primitive requests) and the supported kinds, and the rich schema covers parameters well. However, with no output schema and no mention of return values, ordering, batch size limits, or error handling, an agent cannot fully predict the tool's response. For a moderately complex fan-out tool, this is a noticeable gap.

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 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining the kind-specific semantics: 'score (fractional scale)' and 'noul (calibrated probability)' clarify enum values that the schema only lists without explanation. This is genuine added value, justifying a 4.

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 opens with a specific verb and resource: 'Evaluate a batch of decisions in ONE parallel pass.' It names the three supported primitives (choice, score, noul) with constraints, which makes the tool's function clear. It does not explicitly differentiate from siblings like jev_decide, but the emphasis on 'batch' and 'multi-primitive' provides implicit distinction.

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 clearly implies when to use this tool: when you have a batch of decisions to evaluate, since 'Extra questions do not increase latency or cost.' This is a strong contextual signal for batching. However, it does not name alternatives or explicitly state when *not* to use it, so it falls short of full routing guidance.

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