google_serp_events: GET /

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions pagination and the types of data returned (event title, date/time, venue, links), implying a read-only scraping operation. However, it does not explicitly state that the operation is non‑destructive, nor does it cover error behavior, rate limits, or authentication requirements. The disclosed behavior is sufficient for basic understanding but lacks depth.

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 structured with a clear opening statement followed by a detailed list of capabilities and use cases. It is front-loaded with the core purpose and efficiently conveys the tool's scope. The use case list adds value without being overly verbose, though a slightly tighter structure could improve conciseness.

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 has 8 parameters and no output schema, the description is quite complete. It explains the purpose, the parameters in a summarized way, the return fields, and the intended use cases. It lacks explicit notes on limitations (e.g., rate limits, authentication) but covers the essential information an agent needs to decide when to use the tool and what to expect. The presence of a comprehensive parameter schema also contributes to completeness.

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 all parameters are already well documented in the input schema. The description adds context by grouping parameters (e.g., date filters, virtual-event toggle) but does not introduce meaning beyond what the schema provides. It reinforces the purpose of the htichips parameter but does not compensate for any missing parameter details. Baseline of 3 is appropriate.

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 scrapes the Google Events vertical for a query and location, listing specific filters and return fields. It explicitly names the resource (Google Events results) and distinguishes from siblings by focusing on events. The title reinforces the purpose.

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 provides explicit use cases such as event-discovery chatbots, local aggregators, calendar sync, and competitive monitoring, giving clear context for when to use this tool. It does not explicitly mention alternatives or when not to use it, but the strong focus on events implicitly distinguishes it from sibling tools like general SERP or shopping searches.

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