Search related papers

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive nature. The description adds important behavioral details: returns abstract, contexts, similarity score, and explains error conditions (unknown paper_id is error, empty list means no neighbors). No contradictions.

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 sentences with zero waste. The first sentence distinguishes the tool, the second provides usage context and sibling, the third explains return fields and error behavior. All essential 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 output schema exists (implied by description of return fields), the description is complete. It covers purpose, usage, parameters, return values, and edge cases (unknown paper_id, empty result). No gaps.

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 50%. The description clarifies that limit controls the number of returned papers (up to) and that paper_id must be valid (error if unknown). It adds meaning beyond the schema, which only provides type and constraints.

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 clearly names the tool as returning semantically similar papers by embedding distance, not citation links, and provides the use case 'more papers like this one'. It contrasts with sibling get_paper_citations, making the distinction unambiguous.

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?

Explicitly states when to use (for similar papers on the same topic) and when not to use (for citations, use get_paper_citations). This provides clear guidance for an agent to select the correct tool.

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