google_trends

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

No annotations exist, so the description must disclose behavioral traits. It does not mention rate limits, data freshness, authentication needs, or output structure (though an output schema exists). The description is too brief to compensate for missing annotations.

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 short and front-loaded with the core purpose followed by useful sample prompts. Each sentence adds value, though the sample prompts could be considered slightly redundant.

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?

Given the tool's simplicity (single input, output schema exists), the description is adequate but misses explanations of how to interpret interest over time or limitations. The samples partially compensate.

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?

With 0% schema coverage, the description adds a brief clarification: 'query: The topic or search term to check trends for.' This provides basic meaning but lacks details like expected format or examples beyond the provided prompts.

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 'Check Google Trends for a topic to see interest over time, related topics, and related queries.' This verb+resource construction provides a distinct purpose differentiated from sibling tools like google_search or google_news.

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?

Sample prompts illustrate appropriate use cases (e.g., trending tech, comparing Python vs JavaScript). While explicit when-not-to-use or alternative tools are not mentioned, the samples provide strong contextual guidance.

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