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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description reveals how the answer is constructed: every factual statement is copied from validated evidence and linked to its source. This is significant behavioral context—users know the output is bounded, sourced, and not freely generated—which adds real value over the structured 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?

Two sentences with no wasted words: the first states the purpose, the second states the behavioral guarantee. The most important information is front-loaded.

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 single obviously named parameter, the presence of an output schema, and annotations covering safety, the description provides all necessary context. It even clarifies sourcing and linking behavior, leaving no critical gap for an agent deciding how to invoke the tool.

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%, so the description carries the burden of explaining the single 'question' parameter, and it does not explicitly do so. However, the parameter is self-evident from its name and the tool's 'generate an answer' purpose, and no additional formatting or scope details are strictly needed. The description provides indirect meaning but does not fully compensate for the absent schema description.

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 uses a specific verb-object pair: 'Generate a bounded answer' from 'retrieved public evidence.' This clearly distinguishes it from sibling tools like search_knowledge (searching), get_page (fetching a page), and compare_providers (comparing) without needing to open those definitions.

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 clearly communicates the intended use: produce a grounded, evidence-based answer rather than raw search results or page content. It does not explicitly name alternatives or provide when-not-to-use exclusions, but the purpose is contextually distinct enough for an agent to select it appropriately.

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