top_custom_events

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

With no annotations, the description carries the behavioral burden and does so well: it gives the exact JSON shape and defines both metrics ('events' as raw occurrence count, 'visitors' as unique users). It also discloses that pageview/engagement are excluded. It could add sort direction or side-effect note, but for a read-style reporting tool it is transparent enough.

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 dense but compact, opening with the core purpose and using the embedded JSON to convey the return format efficiently. The parenthetical 'data-statable-event' is slightly jargon-heavy, but every clause contributes value.

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?

With no output schema, the description compensates by specifying the response structure and metric meanings, and the schema covers all parameter constraints. Missing an explicit statement of sort order and edge-case behavior (e.g., empty results), but overall an agent has enough to call it correctly.

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 description coverage is 100%, so the parameters are already fully documented and the description does not need to repeat them. The description's metric definitions relate to the output rather than parameter semantics, so it adds no extra parameter-level meaning beyond the baseline.

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 names a specific resource (custom events, 'data-statable-event'), a specific aggregation (top by count for a site), and explicitly excludes pageview/engagement, which separates it from sibling top_pages. The verb 'Returns' plus the example makes the purpose unambiguous.

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 'pageview/engagement excluded' detail implies when this is appropriate, but there is no explicit statement of when to use top_custom_events versus alternatives such as top_pages or top_goals. The tool name and phrase 'for a site' provide context, but the agent must infer selection criteria.

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