jev_score

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 add useful behavior: the input is rated along an ordered rubric of at least two descriptive levels datapoints and the result includes a weighted score and confidence. However, it omits important behavioral context such as whether an API key is required, how the weighting is determined, what confidence means, and failure/error behavior.

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 sentences with no filler. Every phrase earns its place: the resource, the routing action, the rubric constraint, and the returned values. It is tight, front-loaded, and quickly scannable.

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?

Although an output schema is presentasi and the return values are partially described, the description is incomplete for a tool with six parameters and three required fields. The agent still lacks enough detail to construct valid calls, especially for the required instructions and criteria, and receives no guidance about sibling distinctions. The overall context is too sparse for reliable invocation.

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 for six undocumented parameters. The terms 'input' and 'ordered rubric' vaguely map to state and criteria, but neither required parameters such as instructions and criteria nor optional ones like model, api_key, and question_id are explicitly explained. The description adds only a thin layer of meaning beyond the raw schema.

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 uses specific verbs ('Route', 'Rates') and identifies a concrete resource ('a single Score question'), a scoring mechanism ('ordered rubric'), and the output ('weighted score and confidence'). It implicitly separates this tool from siblings like jev_choice and jev_evaluate by focusing on rubric-based scoring, but it never names or contrasts them explicitly.

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 phrase 'a single Score question' hints at a narrow use case, but the description gives no explicit guidance on when to choose this tool over jev_evaluate, jev_choice, or jev_noul. It does not state conditions, exclusions, or alternatives, leaving the agent to infer the appropriate context.

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