jev_score

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

With no annotations provided, the description carries the full disclosure burden, and it does add value: the confidence caveat ('distribution concentration, not correctness') and the volatile cost default are genuinely useful non-obvious traits. It does not disclose return behavior or side effects, but the presence of an output schema partially covers the former.

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?

Three short declarative sentences with the core purpose front-loaded and the caveats kept compact. Nothing is redundant; both caveats earn their place even if terse.

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 output schema covers the return shape, but the tool has three required parameters with zero schema descriptions and no annotations, and the description is too sparse for an agent to confidently construct a valid levels array or phrase an effective question. Adequate but with clear gaps.

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% and the schema properties carry only titles, so the description must compensate. It loosely maps 'state' and 'levels' to the rubric idea but never explains what levels should contain, how ordering is determined, exactly what forms state may take, or how question drives the scoring.

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 names a specific operation — 'place state on an ordered situation rubric' — and adds negative scope ('not for text generation or numeric extraction'), which helps separate it from text-y siblings like jev_ask. It stops short of naming the exact sibling it competes with, so differentiation is partial rather than complete.

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 'not for text generation or numeric extraction' clause gives one exclusion, and 'ordered situation rubric' implies the intended context. But there is no positive when-to-use guidance and no explicit routing against siblings like jev_match, jev_screen, or jev_classify; the agent must infer the boundary.

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