web_research_tool

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

Annotations already declare readOnlyHint=true, so the safe-read nature is known. The description adds that results are 'synthesized findings' but does not disclose rate limits, source attribution, or whether external links are returned. No contradiction with annotations.

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 compact and front-loaded with the primary purpose. The Args section is concise, includes a useful example, and avoids redundant filler. Every sentence contributes value.

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 tool has no output schema, so the description should clarify return structure, but it only vaguely says 'synthesized findings.' The config parameter is unexplained, and research_type options lack elaboration. Adequate for a simple tool but with clear 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 description coverage is 0%, but the description manually documents query (with an example) and research_type (with allowed values). However, the config parameter is completely undocumented, and research_type values are not explained. Partial compensation for the schema gap.

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's function: 'Research a topic using AI-powered web search' and mentions it returns synthesized findings. This distinguishes it from more specialized siblings like keyword_research or competitor_analysis, though it could be more explicit about scope.

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 implies generic use for web research topics, but does not explicitly state when to choose this over sibling tools like serp_results or content_scrape. The research_type parameter offers some guidance on subtypes, but no exclusions or alternative recommendations are provided.

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