Search engine results (free DDG or paid SERP API)

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the fallback logic (free fetch with paid fallback on block), engine-specific pricing behavior, and output format flexibility (JSON vs raw HTML/Markdown). This is solid transparency, though it omits details on rate limits, authentication, or error handling.

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 two sentences, front-loaded with the core verb ('Run a web search'), and packs essential details about engine behavior and output modes without any repetition or fluff. Every word adds value, making it an exemplary concise description.

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?

For a search tool with 11 parameters and no output schema, the description covers the critical operational context: engine selection, cost implications, and output format. It does not detail all parameters or result structures, but the schema covers parameter semantics, and the description gives enough context for effective invocation. It is complete for the tool's complexity.

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 high (82%), so the parameters are already well-described in the schema. The description adds marginal semantic value by explaining the parse parameter's effect and the engine-specific cost implications, but it does not deeply elaborate on any parameter beyond what the schema already provides. This aligns with the baseline 3 for high schema coverage.

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 purpose with a specific verb ('Run a web search') and explicitly distinguishes it from sibling site-specific tools by covering multiple general search engines (Google, Bing, Yandex, DuckDuckGo). It also clarifies the difference between free and paid execution paths, leaving no ambiguity about its 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 explains when the tool uses free vs. paid backend ('tries a FREE direct fetch first' for DuckDuckGo, 'always uses the paid SERP API' for Google/Bing/Yandex) and how the parse parameter affects output. However, it doesn't explicitly state when to prefer this tool over sibling web_data_* tools, relying on the name and context to imply general search use.

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