Web Search

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the 'auto' path tries SearXNG then falls back to DuckDuckGo, and the response includes an optional 'error' field. Missing are any rate-limit, auth, or failure-mode details beyond the error key.

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?

Front-loaded with purpose, then parameter notes, then the return shape – an efficient ordering with no filler. The run-together sentences are dense but each carries distinct information.

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?

An output schema exists and the description still sketches the return shape, and four of five parameters are explained. A few words on num_results and selection from sibling search tools would close the remaining gap.

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 0%, so the description must compensate, and it does for three params: it enumerates engine values, gives concrete searx_engines examples ('google' or 'google, bing'), and lists time_range values (day|week|month|year). Only num_results is left undocumented.

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?

States a specific verb+resource ('General web search') and lists the backends (Google/Bing via SearXNG). 'General' implicitly distinguishes it from the specialized siblings like scholar_search and github_search, though it never names them.

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 word 'general' hints at when to use this over the specialized search siblings, but there is no explicit when/when-not statement or naming of alternatives. The agent must infer routing from sibling names alone.

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