apps__beta_tester_usages__metrics

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

Annotations already communicate read-only and idempotent behavior. The description adds meaningful context beyond those annotations by stating that the result is aggregated time-series data rather than individual records, and by exposing the HTTP endpoint. No contradiction with 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?

The description is two tight sentences plus an endpoint reference, with the core behavior front-loaded and no filler. Every sentence contributes useful information.

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 metrics tool with complete schema parameter descriptions and clear annotations, the description covers the essential behavior and return type. It could have added pagination or response-shape details, but the aggregated time-series clarification and endpoint make it sufficiently complete for correct invocation.

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 schema already documents all five parameters, including the period enum and groupBy dimension. The free-text description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.

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 ('beta tester usages metrics'), scopes it to an app, and clarifies it returns aggregated time-series data rather than individual records. The endpoint path further pins down the exact operation, and the app-level scope distinguishes it from the beta_groups and beta_testers sibling metrics endpoints.

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 its app-level context clear and the endpoint path reinforces it, so an agent can infer this is the right tool for app-wide beta tester usage metrics. However, it never explicitly names alternative metrics endpoints or states when to use this one instead of the beta_groups or beta_testers variants.

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