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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool searches and returns top N papers with metadata, implying a read-only operation. However, it omits details on result ordering, error handling, data freshness, and whether results are real-time or cached.

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 sentences, 16 words. Front-loaded with the action and result. Every word earns its place. No redundancy or 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?

Given the absence of output schema and annotations, the description is too brief. It does not explain what metadata is returned, how results are sorted, pagination, or constraints like the limit maximum. It leaves significant gaps for an agent to properly invoke and interpret results.

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 descriptions coverage is 0%, so the description must compensate. It explains the 'query' parameter via 'Search peer-reviewed evidence' and 'limit' via 'Returns top N papers', but does not detail the 'sources' parameter beyond 'academic sources', leaving the agent to infer from the enum list in the schema. It adds minimal semantic value.

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 states the verb 'Search' and the resource 'peer-reviewed evidence across academic sources', distinguishing it from the sibling tool 'autosearch_run_research' which initiates a full research run. It specifies the output: 'top N papers with metadata'.

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 sets context by stating 'without launching a full research run', implying when to use this lightweight search instead of the more thorough 'autosearch_run_research'. It lacks explicit when-not-to-use guidance but provides clear context for selection.

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