Search topics

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

No annotations are provided, but the description discloses key behavioral aspects: it aggregates spellings/translations, returns a `mid` and `type` field for disambiguation, and requires no cookie while working on rate-limited IPs. This is transparent about access and output semantics.

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 well-structured: a clear primary statement, followed by clarifying examples and a practical note about cost. Every sentence adds value without redundancy.

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 that no output schema is provided, the description sufficiently explains what the tool returns and how it fits into the broader workflow with the sibling tools. It covers when to use, what to pass, and what to expect.

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 fully describes the single parameter, and the description adds the crucial nuance that the parameter can be either a search term or an existing topic id. This enhances understanding beyond the schema alone.

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 the tool's purpose: looking up a Google Trends topic id. It explains the primary use case (first step for entity queries) and distinguishes it from literal phrase searches. It also explicitly tells when to call it relative to the sibling tools.

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?

Provides explicit guidance on when to use: call first whenever the user names an entity, and skip only when a literal phrase is intended. It also notes that this is the cheapest tool, helping the agent decide among alternatives.

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