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

The description adds meaningful behavioral detail beyond the readOnlyHint: it clarifies the exact metric semantics, especially that 'conversations started' counts real replies and never Otto's openers. The 'Read-only' statement reinforces the annotation without contradicting it.

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 every clause contributes: the pipeline definition, windowing, delta calculation, and the critical caveat about openers. It is slightly long but remains focused and front-loads the core purpose early.

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 carries the burden of explaining what the tool returns, and it does so well by describing the screen contents and metric definitions. It does not specify the exact output shape, but for a single-parameter read-only stats tool the level of detail is sufficient.

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?

The input schema already describes playId as 'The play to report on' with 100% coverage. The description does not add parameter-specific details, which is acceptable under the baseline since the schema carries the semantic weight.

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 identifies the resource as 'the play's Stats screen' and enumerates the exact contents: the pipeline stages, four time windows, and percentage deltas. This distinguishes it from siblings such as gtm_show_play and gtm_list_plays, though the operation verb is implied rather than explicitly stated.

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 makes it clear the tool reports play statistics, so an agent can infer it is for metrics rather than general play management. However, it does not explicitly state when to use this tool versus alternatives like gtm_show_play, nor does it mention exclusions.

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