get_trends

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It explains the output type (day-by-day counts) but omits critical details such as response format, how trends are computed (e.g., unique users vs raw events), timezone handling, pagination, or any limits. This is a significant gap for a tool that an agent may invoke blindly.

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 a single, front-loaded sentence with no wasted words. It efficiently conveys the core functionality and the optional grouping, though it could have included a bit more usage context without becoming verbose.

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 and lack of annotations or output schema, the description is incomplete. It does not specify the response structure, how grouped results are returned, error cases, or any assumptions about the data. An agent would need to infer these details or make assumptions, which is risky for correct invocation.

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 75%, so most parameters have descriptions in the schema. The description adds meaning by clarifying that from/to define a date range and that group_by is an optional property for segmentation, which aligns with the schema. However, it does not explain event_name beyond what the schema provides, and the description does not fully compensate for the missing description on that parameter.

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 states a specific verb 'get' and resource 'event trends', clarifying it provides day-by-day counts over a date range with optional grouping. This clearly distinguishes it from siblings like get_event_count (which likely provides total counts) and get_realtime_counts (realtime data), so an agent can tell them apart.

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 implies when to use this tool (for time-series trends) but does not explicitly contrast it with alternatives or state when not to use it. There is no mention of choosing get_trends over get_event_count or other sibling tools, leaving the agent to infer the appropriate context from the semantics alone.

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