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

With no annotations, the description carries the full burden. It discloses the output (answer text plus sources) and grounding in live web sources, giving a solid mental model. It doesn't mention latency or async behavior, but those are covered by the schema's async parameter description.

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 purpose, and contains zero filler. Every word contributes to understanding.

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 is relatively simple with clear schema docs. The description covers purpose, output, and usage context. Combined with the 100% schema parameter descriptions, an agent has enough to select and invoke it correctly.

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 100%, so all three parameters are already well-documented. The description adds minimal semantic value beyond the schema, only implicitly connecting includeText to 'sources.' Baseline 3 is appropriate.

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 explicitly states it gets a 'direct, cited answer' grounded in live web sources, and distinguishes itself from 'a list of links' (web search). This clearly separates it from sibling tools like web_search or web_contents.

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?

It provides clear guidance on when to use: 'when you want a conclusion rather than a list of links.' This implies when not to use it, though it doesn't name specific alternative tools. Still, the context is clear enough for an agent to differentiate.

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