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

No annotations are provided, so the description carries the full disclosure burden. It does add one genuinely useful behavioral fact — the billing cost of 1 credit per call — but says nothing about the return format (a list of suggestion strings), rate limits, or error behavior.

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 short sentences with no wasted words, and the core purpose is front-loaded before the secondary cost note.

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 simple two-parameter lookup with full schema coverage and no output schema, the description covers purpose and cost adequately. The only minor gap is that it does not characterize the response (suggestion list) or note any result limits.

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 both parameters (q and region) are already fully documented in the schema, including the region-code format. The phrase 'partial query' loosely reinforces q but adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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 states a specific resource (DuckDuckGo search suggestions) and the input condition (a partial query), so the agent immediately knows what the tool returns. It does not explicitly contrast itself with siblings like get or get_news, but the name and resource make the distinction obvious enough.

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?

There is no explicit when-to-use, when-not-to-use, or alternative routing guidance. The intended use case is only implied by 'partial query', leaving the agent to infer that this is for suggestion lookup rather than full search.

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