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

Annotations already declare readOnly/idempotent/openWorld, but the description adds substantial operational context beyond them: ~30s latency, price of $0.03, that bad input is free while upstream errors and empty answers are still charged, and the x402 payment mechanism. This is exactly the kind of non-obvious behavior an agent needs before invoking a paid call.

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?

Front-loads the core purpose and scope before the pricing/latency details, and every sentence carries information. It is somewhat dense with billing caveats, but those are relevant and not padded.

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?

With no output schema, the description still explains the return scale (0-100 interest), the geographic granularity, and the empty-answer case, so an agent knows what to expect on success and failure. Nothing essential to correct invocation is 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 100%, so the baseline is 3, but the description reinforces meaningful parameter semantics — country vs. omitting for worldwide, and the full timeframe span from 7 days to 5 years. It maps to the schema fields and aids interpretation without fully duplicating syntax.

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+resource: Google Trends interest by region for one keyword, with the 0-100 subregion/country scale spelled out. This clearly distinguishes it from siblings like google_trends_related_queries and keyword_search_volume, which cover different data dimensions.

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?

Explicitly says when to use it — 'where a keyword is searched most, for geo-targeting or local market research' — which gives a clear decision context. It does not name an explicit alternative or when-not-to-use condition, so it stops short of a 5.

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