Search academic authors

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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond annotations: fuzzy name matching, common names returning many candidates, and the resulting need for disambiguation. This is meaningful behavioral disclosure that helps the agent set expectations.

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?

Three tightly written sentences each earn their place: purpose, routing guidance, and behavioral/usage tip. There is no filler or redundancy, and key information is front-loaded.

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 strong annotations, complete parameter schema, output schema presence, and explicit sibling comparisons, the description covers purpose, usage, behavior, and parameter semantics thoroughly. Nothing material is missing for an agent to select and invoke this tool correctly.

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 both query and limit are already documented. The description goes further by explaining that the query supports affiliation or field words and that matching is fuzzy, which adds semantic value beyond the bare schema. The guidance to keep limit small also clarifies how the limit parameter relates to the fuzzy matching behavior.

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 starts with a specific verb and resource: 'Search for researchers by name' and enumerates the returned fields (affiliations, paper counts, h-index, identifiers). It also differentiates itself from the sibling tools search_papers and paper_info, making its purpose clear.

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 explicitly states when to use this tool: 'Use this for people, not papers,' and names the alternatives for each different case: search_papers for papers and paper_info for a paper's own author list. It also gives concrete disambiguation advice: add an affiliation or field word and keep limit small.

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