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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, lowering the burden on the description. The description adds useful behavioral context by specifying the argument ordering, the labeled statement roles, and that it covers one specific paper rather than search across papers.

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 front-loaded with the core object and scope, then provides a compact list of supported request types and output entry fields. The sentence is somewhat dense, but every clause contributes useful selection and expectation-setting information.

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?

With a single parameter, full schema coverage, strong annotations, and an output schema, the description covers the key invocation context: what the tool analyzes, what request phrasings trigger it, and what each returned entry contains. It does not address edge cases like missing papers, but that is not critical given the other structured metadata.

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 is already well documented, including accepted forms like bare arXiv ID, URLs, DOI, and Pith Number. The description does not need to add parameter details, so baseline 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 produces the structured argument of one specific paper: claims, premises, machinery, and falsifier, in argument order. It is more specific than the title and gives the output shape, but it does not explicitly differentiate itself from overlapping siblings like get_claims or get_falsifier.

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?

It explicitly says 'Use this for requests about...' and enumerates relevant topics: claims, premises, reasoning, logical structure, conclusion. This gives clear when-to-use context, though it does not state when not to use it or name alternatives for excluded cases.

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