beta_groups__beta_tester_usages__metrics

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context about the return format (aggregated time-series, not individual records) and the endpoint. Given the strong annotation coverage, this is sufficient.

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 concise sentences with no fluff. The first sentence states the purpose, the second clarifies the output shape and includes the endpoint. Every word earns its place.

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 simple read-only metrics tool with strong schema and annotations, the description covers the key contextual points: what it does, the return type, and the endpoint. It does not need to explain defaults or optional parameters since the schema provides these.

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% and all parameters have clear descriptions, so the schema does the heavy lifting. The description does not add syntax or format details beyond what the schema already provides, which is acceptable but not exceptional.

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 verb 'Read', the resource 'beta tester usages metrics for a beta group', and the scope 'aggregated time-series data, not individual records'. This distinguishes it from sibling tools like beta_testers__beta_tester_usages__metrics and builds__beta_build_usages__metrics.

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?

It provides clear context that this tool is for aggregated group-level metrics and explicitly notes it does not return individual records, which implies when not to use it. However, it does not explicitly name alternative tools for individual-level metrics, so it falls short of full alternative guidance.

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