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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful context that the reviews are published, human-signed, and include specific components, but it does not disclose additional behavioral traits such as error cases, pagination, or permission requirements. This is acceptable given the annotations.

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 focused sentences: the first enumerates the returned content, the second states when to use the tool. Every phrase earns its place, and the most important identifier ('published human signed reviews of one paper') is front-loaded. No redundant or vague wording.

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 simple one-parameter read-only lookup with a rich output schema and full annotations, the description is complete. It specifies the input form, the scope ('one paper'), the nature of the data, and the invocation condition. Nothing essential for selecting or calling this tool is missing.

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%, and the arxiv_id parameter description thoroughly explains accepted forms (bare arXiv id, abs/pdf URL, DOI, Pith Number). The tool description does not add parameter-level detail, but with full schema coverage the baseline of 3 is appropriate; no compensation is needed.

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 verb and resource: getting published human signed reviews for one paper, then enumerates the contents (reviewer identity, axis deltas, claim verdicts, defects, predictions, payment). It also distinguishes this from machine-review tooling by emphasizing 'human' and 'on top of the machine review.' This clearly separates it from sibling tools like get_review and get_claims.

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 gives an explicit trigger condition: 'Call this when the user asks what human experts said about a paper, on top of the machine review.' This tells an agent when to select the tool, though it does not explicitly name alternatives or state when not to use it. Clear context is present, but exclusion guidance is missing.

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