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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that results are 'ranked' and grouped by dimension, but it does not disclose details like sorting direction, whether results are aggregated totals only, or pagination behavior. This adds only marginal behavioral context beyond annotations.

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?

Two sentences, each earning its place: the first specifies the operation and supported dimensions, the second explains the use case. No redundancy, no filler, and the core action is front-loaded.

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?

For a read-only analytics lookup with full schema coverage and no output schema, the description conveys the core behavior and supported dimensions. It omits explicit return format details, but 'ranked metrics grouped by dimension' is sufficient for an agent to anticipate a list of dimension-value metrics. Default behaviors are documented in the schema.

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?

All six parameters have descriptions in the input schema (100% coverage), so the description need not repeat them. The description's dimension examples overlap with the schema's own examples (visit:source, event:page, etc.), adding no extra meaning beyond what is already structured. Baseline 3 is appropriate because the schema carries the full parameter burden.

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 action ('Return ranked Plausible metrics') and a clear resource scope: grouped by dimension, enumerating the supported dimension types (page, source, campaign, geography, device, browser, custom property). It distinguishes from sibling Plausible tools by emphasizing dimensional grouping rather than overview or time-series, though it does not explicitly name them.

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 second sentence frames when to use this tool: to answer which channels, content, audiences, or experiences drove results. This gives a clear contextual trigger, but it does not explicitly contrast with plausible_overview, plausible_timeseries, or plausible_goal_performance, nor provide exclusion criteria.

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