google_trends

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

With no annotations, the description carries the full burden. It discloses credit cost, multi-query constraints, region parameter dependencies, and a sample return format for TIMESERIES. However, it omits details like error handling, rate limits, and full structure for GEO_MAP data types, which would enhance transparency.

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 concise at a few sentences, front-loading the core purpose. It includes inline notes and return format, but the structure is dense and could be improved with bullet points for better readability. No wasted sentences.

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 9 parameters and no output schema, the description covers key behavioral constraints and a sample output for TIMESERIES. It omits full output structures for GEO_MAP types and does not differentiate from many siblings, but is adequate for a read tool with good parameter descriptions.

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%, baseline 3. The description adds value by clarifying relationships between data_type and query limits, and region parameter usage with GEO_MAP types. It also provides practical examples for date formats and topic IDs, going beyond the schema descriptions.

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 retrieves Google Trends search interest data, listing three specific data types (interest over time, comparative regional breakdown, interest by region) and the capacity for up to 5 queries. It distinguishes from siblings like google_trends_autocomplete and google_trends_trending_now by focusing on historical trends data.

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 description does not explicitly compare this tool to alternatives or state when to use it over siblings. It implies usage through data type descriptions but lacks direct guidance on tool selection, such as 'for autocomplete suggestions use google_trends_autocomplete'.

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