search_semantic_scholar

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

With no annotations, the description attempts to disclose behaviors like returning citations, PDFs, and author info. However, it omits details on rate limits, authentication, default sort behavior (though schema shows it), pagination, or potential limitations.

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 efficient sentences that front-load the primary function and key features. No redundant or extraneous words; every part adds value.

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 8 fully described parameters and no output schema, the description adequately outlines the tool's capabilities and return types (citations, PDFs, author info). Slightly incomplete for agents needing to understand the full return structure, but sufficient given the parameter richness.

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 100%, so parameters are fully described in the schema. The description adds no additional context about parameter usage beyond what is already in the schema, achieving the baseline of 3.

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?

Clearly states the tool searches academic papers on Semantic Scholar, highlighting AI-powered relevance, citation metrics, open access PDFs, and author information. This distinguishes it from siblings like get_arxiv_papers or search_paperswithcode by specifying the source and capabilities.

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?

Implies usage when needing Semantic Scholar data but does not explicitly compare with sibling tools or state when to avoid using it. No guidance on alternatives or context for selection.

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