search

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

With no annotations, the description carries the burden and it does disclose core behavior: semantic search across academic databases, compact metadata rather than full text, and a dictionary under the 'results' key with id/title/snippet fields. It stops short of describing result limits, ordering, or error behavior, but the core behavioral contract is clear.

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 short and front-loaded: it states the purpose in the first sentence, then the workflow role, query guidance, and return format. There is minor redundancy between 'lightweight results' and 'compact metadata,' but no filler or irrelevant detail.

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?

For a simple one-parameter search tool with no output schema, the description covers the important parts: purpose, query semantics, and return structure. The main gaps are lack of differentiation from search_reference and no mention of result limits or pagination, but these are not critical for a lightweight recall tool.

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 0%, so the description must compensate. The Args section defines 'query' as search terms and gives concrete examples (paper titles, author names, keywords), adding real meaning beyond the bare string type. It does not document formatting constraints, but there is only one required parameter and its intent is clear.

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 a specific action ('Search academic literature') and a concrete output ('lightweight results for browsing'), so an agent understands what the tool does. It frames the tool as the 'recall step' returning compact metadata, which differentiates it from the fetch siblings, but it does not explicitly distinguish it from the similarly named sibling search_reference.

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 clearly situates the tool in a workflow: this is the recall step, meant to help decide which documents to fetch. It also advises that natural language queries work best, which is actionable guidance. It does not name explicit alternatives or state when not to use it, but the context is sufficient for most calls.

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