answer_box_position

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

With no annotations provided, the description fully discloses the tool's behavior: it calls check_citations, bins positions into early/middle/late thirds, and returns 'unknown' for certain engines. This is complete and transparent.

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 three concise sentences, each earning its place: first states the action, second explains the mechanism, third notes an edge case. No wasted words.

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 description covers what the tool does, how it works, and when it returns 'unknown'. It lacks explicit output format details (e.g., per-citation position), but the overall picture is sufficient for an agent to decide when to use it.

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?

Despite 100% schema coverage, the description adds context: it explains how each parameter is used (e.g., engine's effect on output, max_results limits citations), enhancing understanding beyond the schema.

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 provides a specific verb ('Locate') and resource ('where each cited URL appears'), clearly distinguishing the tool's purpose from siblings like check_citations by explaining how it bins positions into thirds.

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 implicitly guides usage by noting that engines without raw_answer (Bing, Brave) return 'unknown', advising against use in those cases. However, it does not explicitly compare to alternatives like directly using check_citations.

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