WebResearch

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

The description states the combined functionality and return type but does not cover failure modes, rate limits, or how parameters interact (e.g., if fetch_top_n exceeds count). Without annotations, more behavioral detail would be beneficial.

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 concise with no redundant information. The first sentence captures the core functionality, the second clarifies the output. Ideal length.

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?

The description covers the high-level behavior but does not specify the output format or how parameters interact. For a research tool combining two operations, users might want to know if the extracted content is plain text, if there are limits on total characters, etc. The description is sufficient for basic understanding but not fully comprehensive.

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?

While the schema describes each parameter individually, the tool description explains the interaction: it searches and then fetches the top N (fetch_top_n) of the search results. This clarifies the workflow and the relationship between count and fetch_top_n.

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 it performs a combined search and fetch operation, returning both search results and extracted content. This differentiates it from sibling tools like WebSearch (search only) and WebFetch (fetch only), as well as ImageSearch and PaperFetch.

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 recommends using this tool for research queries, implying it's best when both search and content extraction are needed. It doesn't explicitly exclude other use cases or mention alternatives, but the context is clear enough.

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