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

The description adds substantial behavioral context beyond the annotations: candidate selection is based on title/abstract matching plus connected records, paraphrased claims can be missed, and an empty result is not evidence of absence. It also reports a validation statistic, giving the agent useful calibration information without contradicting the readOnly/openWorld 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?

Every sentence earns its place: the first defines the core behavior, the second gives usage triggers, the third explains candidate selection and a key limitation, and the fourth provides validation evidence. The most important information is front-loaded and there is no fluff.

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?

Given the tool's complexity, the rich output schema, and the annotations, the description is complete. It covers when to use it, what it returns, how candidates are selected, the open-world limitation, and evidence of reliability. Nothing needed for correct invocation 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%, so the parameters are already documented. The description adds context about what a 'statement' is used for, but it does not add new semantic detail about the limit parameter beyond the schema's range and default. This meets the baseline without exceeding it.

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, resource, and output: checking a scientific statement against arXiv papers and returning support, contradiction, or undecided verdicts with quoted claims and confidence. It clearly distinguishes the tool's question-answering role from sibling tools like search_claims or search_papers.

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 explicit trigger conditions: call before asserting a scientific result, when the user asks whether something is established/disputed, or when sources disagree. It does not explicitly name alternative sibling tools or state when not to use them, so it falls just short of a 5.

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