semantic_scholar_search_authors

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

Annotations already cover read-only/idempotent behavior, so the description adds value by disclosing Markdown default output, response_format='json' option, and pagination limits (max 100, default 10). It also warns about name ambiguity, offering extra operational context beyond 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 compact and well-structured: it opens with the core purpose, then supplies an example, caveats, alternatives, and paging/output details. Every sentence carries load, with 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?

The description covers primary usage, pagination, output formats, and points to relevant sibling tools. It does not detail the response structure, but given the schema and annotations, it is sufficient for selecting and invoking the 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?

The schema already contains descriptive text for each parameter, so the description's example and mention of offset/limit and response_format add only modest value. The concrete query example and clarification of default response format help, but the schema does most of the heavy lifting.

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 states 'Search for academic authors by name' with a concrete example ('Yoshua Bengio'). It distinguishes from sibling tools by explicitly naming semantic_scholar_paper_authors for a different use case (listing authors of a specific paper).

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 clearly says when to use this tool (search by name) and when to use alternatives: semantic_scholar_get_author for confirming identity and semantic_scholar_paper_authors for listing paper authors. It also provides pagination guidance and response format selection, fully covering usage context.

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