Rate on an ordered scale

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It states the tool returns a probability-weighted score, distribution, confidence, and a recommended action, which is valuable. However, it doesn't explain how the confidence thresholds (act_above, review_above) affect the recommended action or any edge cases. The description adds some behavioral context but not comprehensive detail.

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 three concise sentences with zero filler. The core purpose is front-loaded in the first sentence, followed by the return summary and usage guidance. Every sentence contributes value, and it's appropriately brief.

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 tool has a moderate complexity with 5 parameters and an output schema. The description covers the purpose, return behavior, and usage constraints. The output schema provides return structure, so the description doesn't need to repeat that. It's complete enough for an agent to understand when and how to use the tool, though it could benefit from a note on how to frame levels or question, but those are covered in the schema.

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 schema already documents all parameters thoroughly. The description adds minimal parameter-specific meaning beyond the schema. It mentions 'ordered scale you define' which loosely relates to levels, but doesn't elaborate on state, question, or threshold parameters. Given high coverage, a baseline of 3 is appropriate.

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 rates a state along an ordered scale defined by the user, which is a specific verb and resource. It also differentiates from sibling tools by explicitly stating 'not for picking a category', which suggests a contrast with jev_classify. However, it doesn't name the sibling explicitly, so it's clear but not maximally distinct.

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 provides explicit usage guidance: 'Use for degree or severity, not for picking a category.' This tells the agent when to use the tool and what not to use it for. It also implies the user must define the scale, which is useful. It doesn't mention alternatives by name, but the exclusion is clear enough.

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