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

With no annotations, the description carries the full burden, and it does disclose valuable behavior: per-question cost of €0.008 billed to the Bearer API key, reading of top pages, numbered citations, and refusal instead of guessing. It omits latency, rate limits, and what happens when question is null despite both parameters being optional.

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?

Everything is packed into one front-loaded paragraph with no filler; purpose comes first, then pricing/auth, then parameters. It is slightly dense as a single run-on block but nothing is wasted.

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?

An output schema exists, so return structure need not be described, and the description still outlines the answer format (numbered citations). Cost, auth, fallback behavior, and both parameters are covered; only failure modes beyond 'not found' are missing.

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 0%, so the description must compensate, and it does: 'question' is defined as the question to answer and 'region' is explained as a ddgs region with concrete examples (de-de, us-en) and the default wt-wt, none of which appears in 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?

States a specific verb and resource: 'Answers a question grounded in live web search', and adds the mechanism (searches, reads top pages, numbered citations). This implicitly separates it from web_search (raw results vs. synthesized answer), but never names that sibling explicitly.

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 'grounded in live web search' framing implies when to use it (factual questions needing live sources), and the no-guess fallback sets expectations. There is no explicit when-not guidance and no named alternative such as web_search for raw result lists.

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