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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, read-only, and idempotent operation. The description adds that the tool groups by configured goals and answers conversion questions, but does not describe any potential performance implications, data limitations, or auth requirements beyond the API key. It does not contradict annotations and provides some behavioral context, but does not note anything about handling missing goals or the effect of no goals configured.

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, concise sentence with a clear subject and verb, followed by a purpose-oriented question. No wasted words. It front-loads the core information (returns events, visitors, conversion rate grouped by goal) and then adds a practical framing. Could be slightly more structured with an example, but it is well within acceptable length.

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 moderate complexity with 4 parameters and no output schema, the description provides a clear purpose but lacks information about return value structure (e.g., how goals are listed, whether rows include goal names, and the exact shape of the response). It also does not mention error cases like invalid site_id or missing goals. Since the schema is fully documented and annotations cover safety, it is adequate but not exhaustive for a production agent.

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 the schema already describes all parameters (limit, _apiKey, site_id, date_range) with definitions. The description mentions grouping by goal and period, which partially aligns with site_id and date_range, but does not add significant new meaning beyond the schema. It does not discuss parameter interactions or provide additional context for the limit parameter. Baseline 3 is appropriate because the schema carries the load.

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 returns events, visitors, and conversion rate grouped by goal, and specifies the purpose of identifying conversions. It names the goal types (signup, activation, purchase). However, it does not explicitly differentiate from sibling tools like plausible_breakdown, plausible_overview, or plausible_timeseries, which are all analytics variants. The description is specific enough but lacks a direct comparison to those siblings.

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 (when you need goal-specific conversion data) but does not explicitly state when not to use it or mention alternatives such as plausible_breakdown for custom breakdowns or plausible_overview for general metrics. It provides some context (grouped by goal, conversion information) but lacks clear exclusion criteria.

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