get_keyword_trends

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

No annotations are provided, so the description carries the full burden. It accurately describes a read operation and its output, but does not disclose details like response format, granularity, rate limits, or data source specifics. It adds some context beyond the schema but is not rich.

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 concise sentences with no filler. It front-loads the verb and resource, then elaborates on purpose. Every word earns its place.

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?

There is no output schema or annotations, so the description is the only context. It explains the core purpose and output type ('search interest over time'), which is sufficient for a simple read-only tool. However, it lacks details like the time series format or that the data points are weekly/monthly, but the schema covers date range. It's adequate but not complete.

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?

The schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description does not add any extra meaning to the parameters; it merely mentions 'keywords' implicitly. Since the schema already documents each parameter well, this is adequate.

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 clearly states a specific action ('Get') and resource ('Google Trends data for keywords'), and adds the output type ('search interest over time') and intended use ('for seasonality and trend analysis'). This distinguishes it from sibling keyword tools like get_keyword_difficulty or get_keyword_suggestions.

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 context for when to use the tool: 'for seasonality and trend analysis'. This implies the use case without explicitly excluding alternatives or naming sibling tools. It's sufficient but lacks explicit when-not-to-use guidance.

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