Get Evergreen analytics

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive, so safety is covered. The description adds a genuinely useful behavioral trait beyond that: unavailable provider metrics are returned as null rather than zero, which directly affects how an agent should interpret missing data.

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 tight sentences, front-loaded with the metric inventory and ending on the high-value null-vs-zero caveat. The metric list is long but each item earns its place by telling the agent what is returned.

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 describing returns, and it does so by naming the metric families and clarifying null semantics. Only the queueId input semantics are left unaddressed, which is a minor gap for a one-parameter tool.

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?

There is a single required queueId parameter with 0% schema description coverage, and the description never explains what queueId refers to or its expected form. The name is largely self-explanatory given the queue-centric sibling set, but the description does not compensate for the coverage gap as required when coverage is below 50%.

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?

States a specific verb (Get) and enumerates the exact metric families returned: source metrics, queue-lifetime metrics, tracked clicks, attributed conversions, and recent run outcomes. The 'queue-lifetime' and 'run outcomes' framing ties it to the Evergreen queue domain well enough to separate it from generic get_analytics, though it never explicitly names that sibling.

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?

Usage is implied by the Evergreen/queue wording, but there is no explicit when-to-use or when-not-to-use guidance relative to get_analytics, list_post_analytics, or list_evergreen_runs, which an agent could easily confuse with this tool.

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