research

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

Without annotations, the description discloses the multi-step process (search, scrape, aggregate, cite), which is fairly transparent. However, specifics like number of results searched or citation format are omitted.

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 a single, clear sentence without superfluous words, front-loaded with the key action 'Search the web'.

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 tool's complexity and presence of an output schema, the description covers the essential workflow and output format, though it could mention limitations like the number of initial search 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 coverage is 100% with clear descriptions for query and depth. The tool's description adds no additional parameter meaning beyond the schema, so baseline score applies.

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 tool searches the web, scrapes top results, and returns an aggregated cited report, distinguishing it from sibling tools like web_search (search only) and scrape (scrape only).

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?

Usage is implied (for research tasks requiring aggregation), but there is no explicit guidance on when to use this tool versus alternatives like web_search or scrape.

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