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

Annotations already declare this as a safe, idempotent, non-open-world read, so the description is free to add value — and it does, revealing the resolved:false candidate-list behavior and what fields the result carries. That ambiguity handling is genuine behavioral context not present in the schema or 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?

Two sentences with no filler, leading with what is returned before the fallback case. Slightly dense packing of return fields, but nothing is wasted.

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 no output schema, the description carries the burden of explaining return values and does so — fields, study cards, and the candidate/resolved:false case. An agent knows both what it gets on success and what happens on ambiguity.

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 coverage is already 100%, so the baseline is 3; the description earns an extra point by listing accepted input forms including ORCID, which the schema's examples do not cover. It still doesn't clarify the id vs author distinction, which the schema only labels vaguely as 'Alias of author.'

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 a specific verb+resource: it returns 'one profiled author' and enumerates what comes back (lab, role, profile URL, study cards). This clearly separates it from list-style siblings like search_authors, though it never names search_authors explicitly as the alternative for browsing.

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 explains the ambiguous-name fallback ('If the name fits several people or has no profile page, the answer lists candidates (resolved: false)'), which tells the agent what to expect rather than when to pick a sibling. It lacks an explicit 'use search_authors when you want a list' rule, so it stops short of full routing guidance.

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